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1、Towards a new age of economic enlightenment2Data:Towards a new age of economic enlightenmentPhil MooreContributing EditorMausi OwolabaniPolicy Analyst Clive HorwoodManaging Editor and Deputy Chief Executive Officer Simon HadleyDirector,ProductionFergus McKeownSubeditorSarah MoloneySubeditorWilliam C
2、oningsby-Brown Production ManagerKat Usita Managing Director,Research 2021 OMFIF Limited.All Rights Reserved.Strictly no photocopying is permitted.It is illegal to reproduce,store in a central retrieval system or transmit,electronically or otherwise,any of the content of this publication without the
3、 prior consent of the publisher.While every care is taken to provide accurate information,the publisher cannot accept liability for any errors or omissions.No responsibility will be accepted for any loss occurred by any individual due to acting or not acting as a result of any content in this public
4、ation.On any specific matter reference should be made to an appropriate adviser.Company Number:7032533.ISSN:2398-4236Official Monetary and Financial Institutions Forum 6-9 Snow Hill,London,EC1A 2AY,T:+44(0)20 700 27898 omfif.org omfif.orgAbout OMFIFWith a presence in London,Singapore,Washington and
5、New York,OMFIF is an independent forum for central banking,economic policy and public investment a neutral platform for best practice in worldwide public-private sector exchanges.For more information visit omfif.org or email AcknowledgmentsOMFIF thanks the many associates and colleagues from co-oper
6、ating institutions for their assistance and guidance in helping creating this report.3omfif.orgContentsForeword Lets have a dispassionate debate about dataBy John Orchard,CEO OMFIFIntroduction Data:Towards a new era of economic enlightenmentChapter 2 The fundamental role of dataChapter 3 Data and di
7、gitalisation can drive SME growthChapter 4 How data can address policy challengesChapter 5 Ensuring safety in dataChapter 1 Regulators grapple with the role of dataChapter 6 Data flows in a digital economy policy considerations5405666168304Data:Towards a new age of economic enlightenmentForeword Let
8、s have a dispassionate debate about dataOMFIF sets out to be the place where public and private sectors meet to shape finance and economics.Nowhere is that more complex,fast-moving and impactful than the intersection of technology and money.OMFIF has had some of its liveliest discussions in the last
9、 18 months about digital currency.The technology itself is a subject for wide-ranging discussion,the policies it obliges us to reconsider even more so.Collecting and applying data is at the heart of that discussion.Regulators are working out how to reconcile the competing needs of supervision and pr
10、ivacy.They know that technological and data-driven innovation can potentially bring enormous benefits and efficiencies to businesses,financial institutions and most of all citizens,but not without risks.They also need to consider resilience.As a central banker recently pointed out to us,the room for
11、 failure,especially in the realm of sovereign money is very small.There are no easy answers to any of these challenges,though technology itself may generate some of the best.This reports aims to set a neutral course through what is often a polarised and emotional debate about the use of data.But it
12、also unashamedly looks at areas where appropriate application of data has provided or could provide enormous benefits,not just in the financial sector but also in other sectors such as healthcare.The official sector,regulators and technology companies are in the process of understanding one another
13、better and evolving with their respective needs and competencies in mind.The application of data to the world of money and business is still relatively new,but,with appropriate checks and balances,it offers increasing levels of productivity,capital efficiency and financial inclusion,among other bene
14、fits.The benefits to people,businesses,societies and economies could be transformational.OMFIF is pleased to convene this discussionThe application of data to the world of money and business is still relatively new,but,with appropriate checks and balances,it offers increasing levels of productivity,
15、capital efficiency and financial inclusion,among other benefits.Public and private sectors need to engage constructively to deliver the undoubted benefits of appropriate data usage.By John Orchard,CEO,OMFIF5omfif.orgFINANCIAL inclusion is a significant catalyst for economic development.However,more
16、than one-third of adults in our country remain unbanked.Because of this deplorable state of financial services,unbanked individuals miss out on the opportunities brought about by convenient digital payments.More importantly,because of the high unbanked rate,opportunities to distribute social benefit
17、s in a more efficient way cannot be achieved by the government.This is the reason why the government has intensified its campaign for financial inclusion.Financial inclusion cannot be achieved without necessarily collecting,processing and sharing personal data to comply with our central banks policy
18、 on customer due diligence.So said a senior data regulator for one of Asia Pacifics most populous countries.If ever there was a call to arms to ensure that the data that pervades our lives,our businesses and our economies can be used to enhance our collective wellbeing,this plea would serve it well.
19、An African data regulator told OMFIF:Financial inclusion is one of our governments main objectives.However,one of the main barriers is the lack of proper identity.Means of identifying unbanked persons which are innovative and respect privacy would enhance the rate of financial inclusion and reduce p
20、overty.Theres little doubt that digital transformation could turbocharge mass inclusion.But that cant be achieved if the ability to verify your identity because of a lack of documentation remains out of reach.Could a social identification be the solution?It could complement digital or biometric IDs
21、and use social activity to establish identity and verify patterns that enhance a users profile.Each individual would own their social ID,but it would be portable across platforms and jurisdictions.Would this assuage competition concerns?What guardrails would need to be in place to allow for data por
22、tability?How would security and privacy standards adapt?Relying on data to facilitate a greater number of the unbanked and underbanked gaining access to financial services is just one area where data could be used to improve policy decisions to meet policy objectives.The collection and use of data s
23、hould be enabled and celebrated as a means to help tackle our biggest societal issues.Instead,it is increasingly weaponised.The earlier part of this century had a big focus on how data can be a force for good.In recent years,discussion around data has coalesced around methods for guarding and limiti
24、ng collection and use of personal data and the potential harm that the abuse of data collected on individuals can cause.Big data has Data have the potential to bring transformational benefits to public policy,societies and economies.This will require a diverse group of regulators to work closely wit
25、h businesses which collect and disseminate data.Data:Towards a new age of economic enlightenmentIntroduction6Data:Towards a new age of economic enlightenmentbecome synonymous with bad data.At the centre of this dialogue are the myriad regulators trying to plot a path through a fast-changing,hard-to-
26、understand,difficult-to-reconcile set of requirements and responsibilities around data.Technological advances and Covid-19 have demonstrated that data can unlock key understandings to help with the worlds biggest problems and that this can be done in a way that protects peoples fundamental right to
27、privacy.This report sets out to present a view of the positive use cases for data and how they could be used for greater economic benefit,while complying with the essential need to protect the individual and prevent the illegal.It does not shy away from well-documented concerns about the misuse of d
28、ata.But it argues that such incidents should not detract from the benefits an enlightened approach to the collection and application of data will bring for policy objectives.In researching this report,OMFIF spoke to a diverse group of public sector bodies that play an important role in regulating th
29、e use of data.They come from the Americas,Europe,Africa and Asia Pacific.And they have differing approaches and attitudes to this crucial area of regulation.Many of the regulators interviewed by OMFIF take a protectionist stance.They focus on the needs and rights of consumers almost to the exclusion
30、 of all other considerations.Data localisation the practice of keeping data in the region it is generated within-is another area of concern which hampers the sharing of information.Often this falls under the auspices of national security or the fear that a nations sovereignty is threatened if it is
31、unable to exert full control over data that is stored outside its borders.Others recognise the tensions between privacy concerns and the appropriate use of aggregated and anonymised data by both the public and private sectors,and have yet to solve them.A small number actively embrace the use of data
32、 appropriately monitored for economic benefit.In the latter case look as is often the case in digital matters to Singapore for an example.The country recently amended its Personal Data Protection Act to update the list of legitimate purposes for which businesses may collect,use or disclose personal
33、data.These include the following:if it is in the legitimate interest of the business,for example,if it is for the purpose of detecting or preventing fraud or money laundering or to ensure the integrity and safety of systems;if it is for business improvement purposes,for example,improving,enhancing o
34、r developing new goods or services;or if it is for the performance of contractual obligations,for example,where the organisation needs to sub-contract or disclose the personal data to another organisation for the performance of a contractual obligation to the individual or a transaction sanctioned b
35、y the individual.Underpinning all of this is the fundamental principle of accountability.Accountability is an organisation exercising responsibility over personal data in their care and being answerable to individuals who have entrusted these organisations with their data.This entails protecting per
36、sonal data and using it for not just lawful but ethical purposes to benefit consumers.While any kind of global standard will be hard to achieve,accountability as the baseline is a logical and important starting point.Governance and regulation of data is fragmented and inconsistent.It is notoriously
37、difficult to provide common frameworks in any part of the global economy.The Basel banking accords came close,but in the end failed to generate universal adoption.Finding a common framework will be extremely difficult,for all that many regulators see the European Unions general data protection regul
38、ation as a gold standard.Thats at least in part because how data are regulated,where the mandate for regulation resides and what powers those regulators have differ markedly from country to country.Some jurisdictions have adopted a centralised approach in regulating the use of data.In these cases,on
39、e agency usually a data privacy commission has the overarching responsibility for data protection regardless of the sector in which the data is being used,whether it be financial services,health,social welfare or others.In other cases,countries have adopted a more sector-specific approach,with diffe
40、rent regulators assuming responsibility and issuing guidance for aspects of data privacy within their remits.In some jurisdictions,for example,a central bank or financial regulator is responsible for regulating the use of data.The governance structure of the jurisdiction plays a key role in determin
41、ing the responsible body or agency.For instance,the European Parliament and Council of the European Union issued the GDPR to regulate the protection of individuals with regard to the processing of their personal data and on the free movement of such data within the EU.Each member state set up their
42、own respective data protection agencies,as well as national laws,to implement the GDPR and monitor compliance with the requirements of the regulation by data processors and controllers.Although the specifics vary for each country,data privacy commissions are usually responsible for enforcing data pr
43、ivacy laws,protecting the fundamental rights to personal data,investigating and prosecuting data breaches,and handling consumer complaints.However,in some jurisdictions,the responsibility for data protection may sit within agencies responsible for information technology,trade and industry,or consume
44、r protection more broadly.In the US,the Federal Trade Commission has been the chief federal agency on This report sets out to present a view of the positive use cases for data,and how they could be used for greater economic benefit,while complying with the essential need to protect the individual an
45、d prevent the illegal.7omfif.orgprivacy policy and enforcement since the 1970s,when it began enforcing one of the first federal privacy laws the Fair Credit Reporting Act.Since then,rapid changes in technology have raised new privacy challenges.Meanwhile,some states have legislated their own data pr
46、otection laws and assigned agencies within those states to regulate data privacy issues.This report aims to open a discussion among this diverse group of regulators to explore themes of common interest.It does so by telling a story about how data has benefited economies and societies in the past,pre
47、sent and will do in the future.It looks at the fundamental role of data in all organisations,from governments to healthcare providers and even travel companies.It puts focus on the special case of small-and medium-sized enterprises,in providing them with better credit through data and spurring innov
48、ation.It examines how to garner safety in data,solving the tension between privacy and data sharing.And it speaks in detail of the different approaches taken by regulators,in particular in financial services.It is clear that unlocking the benefits of data at both a country and international level wi
49、ll require co-operation and coordination across different regulatory bodies,including those that oversee privacy,the financial sector,economies and indeed the state as a whole.The report does not pretend it is in a position to make detailed policy proposals.Rather,it aims to encourage dialogue among
50、 all stakeholders in the data universe to promote best practice.OMFIF thanks all of the regulators who took the time to speak to us about these vital issues.We welcome your feedback on our report and hope that it adds an important new aspect to the debate on data.Key findings of interviews with regu
51、latorsData regulators broadly fall into one of three camps:-Those that put an emphasis on consumer protection ahead of all other considerations;-Those that recognise the tension between privacy concerns and the appropriate use of aggregate data by both public and private sectors;-Those that embrace
52、the widespread use of anonymised data for the benefit of state,businesses and the economy as a whole.Many of the regulators that took part in the OMFIF study expressed confidence that the economic and societal advantages of the responsible use of data are extensive.These include:-Financial inclusion
53、,especially the ability to provide tailored financial services to the unbanked and those with limited access to credit;-Businesses,in providing better consumer insights for SMEs enabling them to scale up their operations;-Social services,including improving the quality and delivery of healthcare and
54、 education.Of the regulators interviewed,76%said that existing regulations on data privacy in financial services and other sectors are sufficient,with some of these stating that they need to remain proactive and keep up with the pace of innovation.The majority of policy-makers(69%)do not see a confl
55、ict between anti-money laundering or compliance considerations and data protection policies.Among those that do recognise tensions,one respondent noted that they tend to arise from a lack of understanding and co-operation among the regulatory authorities.There must be flexibility in the application
56、of rules,especially where public interest needs to be demonstrated.Inter-agency collaboration is important,especially between central banks and data protection agencies.The use of data by governments is the primary focus of those regulators considering how data can be used for economic and social be
57、nefits.Very few are considering the positive use of data by the private sector,which they largely regard as a group to be limited,rather than encouraged.Continuous education and engagement with the public and industry must raise awareness of the role of data:-Consumers need to be aware of their righ
58、ts;-Businesses need to be aware of their legal and ethical obligations;-All institutions,including governments,need to be aware of the ways through with they can maximise the use of data to improve services and grow.8Data:Towards a new age of economic enlightenmentChapter 1Regulators grapple with th
59、e role of dataInterviews conducted by OMFIF with global data regulators show widely differing approaches to oversight and a need for greater understanding of the role of data.AT a regulatory level,there is no such thing as one size fits all in the datasphere.An OMFIF study of regulators views on dat
60、a privacy suggests these authorities fall into three broad camps.In the first are those that emphasise consumer protection above all other objectives.The second is made up of those that recognise the tension between privacy concerns and the appropriate use of aggregate data by both public and privat
61、e sectors.And the third is characterised by regulators that embrace the widespread use of anonymised data for the benefit of state,businesses and the economy as a whole.There are a number of factors explaining this diverse range of regulatory attitudes to data privacy.Some regulators are relatively
62、new to the notion of data protection,with governments in countries such as Egypt,India and Saudi Arabia having recently introduced data protection laws for the first time.In some cases,this has been driven by a recognition that clear regulation governing the datasphere is a prerequisite if they are
63、to attract the investment they need to build a digital economy.Others,which were quicker to identify digitalisation as a national economic strategy,have a much longer track record of data protection legislation.Singapore,for example,enacted its Personal Data Protection Act in 2012.In the narrower sp
64、here of the financial services industry,regulatory attitudes towards data privacy are shaped by varying levels in local financial literacy and inclusion,technological and human resources capability,idiosyncrasies of legal systems and natural regulatory caution.Responses to OMFIFs study of regulators
65、 suggest that the majority recognise that their principal objective is to address the tension potentially arising from the need to respect privacy without hampering innovation.One European Union-based respondent to the OMFIF study addressed the regulatory conundrum presented by data privacy by 9omfi
66、f.orgNon-bank third parties holding and aggregating data is not necessarily inappropriate,but it may increase opacity and create new points of vulnerability from a systemic perspective.Our major challenge is that because data is such a broad term,we dont have enough people working in this agency to
67、investigate all the cases that are presented to us.The advent of new financial technology twinned with the increased volume,velocity and variety of data is creating issues with data menting that it should be noted that in a democratic society,it is necessary to constantly reconcile different interes
68、ts and not to upset their balance.One way of reconciling interests is to restrict the rights and freedoms of the individual,for example,by enacting legislation that allows for the processing of personal data.The evolution of systems like open banking have been driven mainly by a focus on competition
69、 as a policy goal,said a regulator from a G7 central bank in response to a question about the tension between the use of data and sensitivities about individuals privacy.In this and other areas,we have been focusing for a while on encouraging an increase in the flow of data to enable innovation and
70、financial well-being,balancing this with the goals of maintaining high levels of consumer protection,cybersecurity and safety and soundness.The growth of our fintech ecosystem has generated a new set of opportunities,but the challenge is to manage the shift towards new forms of innovation that requi
71、re more of a focus on privacy without limiting economic activity.This regulator reports that,to date,a number of use cases suggest that access to aggregated user data is having a positive societal impact.Take,for example,the contribution it has made to the promotion of financial inclusion,which mean
72、s different things in different societies.A respondent from the central bank of an emerging economy said that with more than one-third of its adult population unbanked,access to basic banking services in his country was deplorable.This would be an inappropriate way to describe official calculations
73、of the unbanked populations of highly developed economies.But financial exclusion estimates of 7%in the US and 6%in Spain,France and Italy all remain unacceptably high.So too does the level in the UK:Today,there are currently 1.2m unbanked people in the UK,who by and large rely on cash and cannot ac
74、cess digital payments or can access them only at disproportionate cost,said Jon Cunliffe,deputy governor of the Bank of England,in May 2021.The regulator at a G7 central bank explained that its priority is on addressing access to financial services across the broader subsection of society that is le
75、ss narrowly defined as underbanked or underserved,rather than unbanked.Leveraging data-driven opportunities,said this regulator,can play a decisive role in widening and improving the availability of financial products among consumers and small businesses with limited access to credit.Increased digit
76、al access and more efficient identification and authentication can benefit thin-file or no-file individuals,or those with low credit scores that might not have been able to access loans under traditional underwriting approaches,said the regulator.Accelerated and more accurate decision-making means t
77、hat personalised,customer-tailored and competitively-priced products can be made available to more consumers outside the mainstream credit system.This regulator said that another example of an initiative supported by enhanced data use is earned wage access,which is helping consumers to receive and r
78、edeploy their wages prior to payday.Even in this highly developed economy,40%of households are estimated to be struggling to pay unexpected bills,and 38%report a timing mismatch between the receipt of their wages and the due date for their household bills.Data-driven earned wage access throws a fina
79、ncial lifeline to those unable to make these ends meet.It also provides a useful societal purpose by discouraging predatory payday lending.Solutions such as these may appear beguilingly straightforward.But as this regulator noted,the tsunami of data being generated in todays society is generating fo
80、rmidable challenges as well as opportunities for the financial services industry and the regulators overseeing them.The advent of new financial technology twinned with the increased volume,velocity and variety of data is creating issues with data governance,he said.This is something we are looking a
81、t carefully,because we need to ensure that our banks have the right systems and governance in place to manage the new technologies,especially those that are more data-intensive.For example,the use of new third party providers and processors of data and connectivity is an area where some of the small
82、er institutions in particular may need guidance.Non-bank third parties holding and aggregating data is not necessarily inappropriate,but it may increase opacity and create new points of vulnerability from a systemic perspective.A practical example of a relatively new vulnerability,this regulator add
83、ed,is banks use of artificial intelligence:Most of this AI uses involve large volumes of data often coming in at a much higher frequency than traditional data and also sometimes with entirely new types of data.For example,banks are now more likely to process audio data for fraud prevention and detec
84、tion purposes.The degree to which banks have 10Data:Towards a new age of economic enlightenmentThe legal entities responsible for complying with GDPR are also much more familiar with the regulation.Three years ago,they asked very basic questions,such as“what is personal data?”.Now theyre posing more
85、 specific and complex questions about the role of data controllers and data protection officers.One respondent suspected that it is fear of financial sanctions rather than respect for consumers privacy that is the main driver of regulatory compliance:I think these entities are nervous about the big
86、fines that can be levied under GDPR.Theyre not necessarily complying because they believe data protection is an important human right.modified,upgraded or enhanced their systems to accommodate this higher volume,velocity and variety of data is something we are monitoring closely.Another example of a
87、 potential data-related vulnerability arises from consolidation in the financial services space.Combining IT systems linked to merger and acquisition activity can also create challenges in the data governance area,said this respondent.There is no indication to date that any systemic risk to the bank
88、ing industry is building up as a result of complications associated with the volume,variety and velocity of data.This may be a function of the fact that the data revolution is probably still in its formative stage;it may be a by-product of the vigilance and natural caution of regulators.There are de
89、finitely risks arising from open banking and from inadequate data governance and poor data management processes,said one regulator.But I dont see these as being among the most important risk issues worrying bank supervisors.This is not to suggest that regulators themselves are underestimating the po
90、tential risks that may be embedded in the data revolution.Many of these have already been well-documented.As a result,strong defences have been constructed against technological vulnerabilities such as data breaches.Provisions have also been written into data protection acts aimed at preventing frau
91、d,money laundering and the financing of terrorism.Some potential vulnerabilities are more theoretical.One of these is the opportunity cost that may be incurred by banks unable or unwilling to allocate sufficient financial or human resources to data collection and analysis.Another,paradoxically,may s
92、pring from the emergence in the digital age of a more uniform approach to risk management.As you move towards a more data-driven approach to lending,there will probably be an element of business model convergence,where banks adopt an increasingly uniform view of risk,said one regulator.The emergence
93、 of a financial monoculture may increase banks aggregate exposure to the same potential shocks.The potential data-driven complications raised by this central banker are inevitably specific to the financial services industry.But all sectors of the global economy are impacted by the speed with which t
94、he creation,capture,storage and sharing of data is growing,and by the breathless pace of innovation that has been encouraged by this expansion.This is creating challenges for regulators across the public and private sectors,many of which are constrained by limited financial and human resources.Our m
95、ajor challenge is that because data is such a broad term,we dont have enough people working in this agency to investigate all the cases that are presented to us,said a representative of a European data protection agency with a staff of around 35 people.This was in response to one of eight questions
96、put to regulators by OMFIF to gauge their views on the use of data and digital technology in financial services and across the public sector.The same regulator reported that understanding of the issues raised by general data protection regulation,for example,has improved markedly over recent years a
97、mong consumers and regulators alike.Much of our role is educative,and I see a big difference between three years ago and today,said this respondent.Members of the public are now more familiar with their rights and are addressing their concerns to us more frequently.The legal entities responsible for
98、 complying with GDPR are also much more familiar with the regulation.Three years ago,they asked very basic questions,such as“what is personal data?”.Now theyre posing more specific and complex questions about the role of data controllers and data protection officers.Theyre looking at impact assessme
99、nts and other ways of reducing the risks associated with data protection.Less positively,this respondent suspected that it is fear of financial sanctions rather than respect for consumers privacy that is the main driver of regulatory compliance:I think these entities are nervous about the big fines
100、that can be levied under GDPR.Theyre not necessarily complying because they believe data protection is an important human right.The interplay between leveraging the benefits of data and building defences against its risks and dangers was a recurrent theme in regulators responses to the questions put
101、 to them by OMFIF.A well-diversified spread of 16 data protection authorities and other overseers from Europe,the Americas,Africa and the Asia-Pacific region participated in this survey,either verbally or in writing,which was conducted in the last quarter of 2021.11omfif.orgQuestion 1Are there polic
102、y outcomes or objectives that could be attained through the collection,processing and sharing of data?What are the policy areas or issues that user data can help address?Regulators from across the world told OMFIF that there was a range of notable public policy objectives that could be attained thro
103、ugh the efficient collection,processing and sharing of personal data.In the words of one Asian regulator,like land,labour and capital,data has become a primary factor of production.The lawful and responsible use of data,with due respect to consumer privacy,is indispensable for gaining the necessary
104、trust from consumers and unleashing its full value.A number of respondents indicated that data sharing is an essential building block for the promotion of broader financial inclusion,which is a core government priority in many countries.A regulator in one emerging southeast Asian economy described t
105、he state of local financial inclusion as deplorable,adding that large sections of the unbanked populations are being denied the opportunities created by digital payments.More importantly,this respondent reported,because of the high unbanked rate,opportunities to distribute social benefits more effic
106、iently cannot be harnessed by the government.This explains why the government has intensified its campaign for financial inclusion.The success of this campaign,added this regulator,is predicated on the efficient collection,processing and sharing of personal data.This is also crucial in the day-to-da
107、y operations of financial institutions to identify,verify and mitigate any risk of fraud and money laundering which our country is faced with,this respondent noted.It also emphasised the significance of the role data sharing plays in curbing corruption and organised crime.An African regulator echoed
108、 the view that data sharing is a prerequisite for wider financial inclusion.In the absence of the necessary data,individuals will continue to be denied access to digital IDs which are increasingly necessary to open the doors to basic financial services.One of the major barriers to financial inclusio
109、n is lack of proper identity,this regulator observed.Innovative and privacy-respecting means of identifying unbanked persons would enhance the rate of financial inclusion and reduce the poverty level.Other respondents agreed that data is making a notable contribution to supporting increased efficien
110、cies in financial services by sharpening lenders insights into creditworthiness.One EU regulator pointed to the role played by its central credit information system,which stores data under strict and clearly prescribed legal conditions.This allows for the creation of a so-called negative list based
111、on data on overdue loans,with positive data on repaid credit included only when explicit consent is provided by data subjects.A Latin American respondent made a similar point about the constructive use of personal data for credit scoring,which can support product development:This is used not just to
112、 track the credit history and debt profiles of data subjects,but also to provide tailored financial services to individuals based on the data collected for each person.Another regulator in Latin America shared the view that the use of personal data can make a notable contribution to product innovati
113、on:The massive analysis of information-big data-the implementation of mechanisms with artificial intelligence,blockchain or smart contracts are examples of aspects that could benefit from(and even depend on)the collection and processing of users personal data.This regulator added the rider that thos
114、e who create,design or use technological innovations must comply with all the rules on the processing of personal data.Question 2 Which groups in your jurisdiction do you think could most benefit from enhancement of services from use of data in the financial services industry and in the public secto
115、r?Many of the regulators that were interviewed as part of the OMFIF study expressed confidence that the economic and societal advantages of the responsible use of data are extensive.One EU regulator highlighted its potential for supporting start-ups and fintech companies.This was echoed by a respond
116、ent which flagged the broader economic benefits of efficient data management:Generally,consumers may stand to benefit from improvements to services provided by businesses.Small and medium enterprises may also gain deeper consumer insights and scale up their businesses through greater use of data in
117、a responsible and accountable manner.Beyond SMEs,unbanked individuals and other financially disenfranchised groups,respondents indicated that data analysis is already making a notable contribution to the protection of vulnerable sections of society.One Asia-Pacific regulator commented that its priva
118、cy commissions human services dataset is an increasingly granular and detailed source of information on areas such as health,education and justice.One of the major barriers to financial inclusion is lack of proper identity,this regulator observed.Innovative and privacy-respecting means of identifyin
119、g unbanked persons would enhance the rate of financial inclusion and reduce the poverty level.Consumers may stand to benefit from improvements to services provided by businesses.Small and medium enterprises may also gain deeper consumer insights and scale up their businesses through greater use of d
120、ata in a responsible and accountable manner.12Data:Towards a new age of economic enlightenmentAnalysis of its dataset is now being used by this privacy commission to provide insights aimed at supporting vulnerable children and families.It is,for example,giving the government a new perspective on the
121、 degree to which children from foster homes are being provided with access to the same opportunities as more privileged youngsters.This privacy commission reported that the results of its initiative are measurable,and that key performance indicators to date suggest is that it is already generating p
122、ositive results.Question 3 What are your(or your constituents)priorities around the use of personal data?Many regulators responding to the OMFIF survey indicated that their foremost priority around the use of personal data is ensuring that their oversight combines systemic resilience with respect fo
123、r public interest and human rights.This caution was emphasised by one EU agency which observed that its priority regarding personal data in the financial(or any other)sector is to ensure compliance with the general rules of personal data processing set out in legal acts.such as GDPR.This is designed
124、 to ensure that personal data should be processed only in accordance with the principles relating to the processing of personal data set out in article 5 of the GDPR.This processing,it added,must be justified by at least one lawful processing condition under articles 6 and/or 9 of the GDPR.Similar c
125、aution was expressed by an Asian regulator.This commissions primary aim is to ensure that personal information controllers,especially in the financial sector,are resilient and are able to comply with global standards when it comes to data protection,it reported.The commission does this by ensuring t
126、hat we provide interventions through the creation of policies,giving advice and information,opening dialogues and engagements,and providing standards and support.Safety-first was emphasised by a number of other regulators(these are explored in more detail in the responses to question 4,below).But th
127、ere is also a growing recognition that safeguarding individuals privacy and leveraging the opportunities that are being unlocked by data analysis need not be mutually exclusive.Singapores Personal Data Protection Commission reported that its priority is to achieve strong data protection while also f
128、acilitating use of data by businesses to drive innovation and growth.To this end,Singapore has recently amended the Personal Data Protection Act to update the list of legitimate purposes for which businesses may collect,use or disclose personal data.Permissible purposes range from those intended to
129、detect or prevent fraud to those supporting business innovation and meeting contractual obligations.Underpinning all of this,the Singapore commission explained,is the fundamental principle of accountability.This is defined as the exercise by organisations of responsibility over personal data in thei
130、r care and being answerable to individuals who have entrusted these organisations with their data.This entails protecting personal data and using it for not just lawful but ethical purposes to benefit consumers.Singapore noted that it had taken a number of steps to foster an accountability-driven cu
131、lture through,for example,the introduction of tools to help organisations protect data,such as guides on accountability and data protection risk assessments.Singapore has also implemented a data protection trustmark certification as a form of recognition for entities that demonstrate accountable dat
132、a protection practices.Question 4 Do you believe that your jurisdiction has sufficient rules in place to safeguard individuals privacy with respect to the use of data in financial and other services?What specific data privacy regulations or policies do you have in place(or think should be in place)t
133、hat are most important to protect users with respect to the collection of their personal data?Respondents to the OMFIF survey were generally confident that they have ensured that sufficient rules have been applied to their data management to protect individuals privacy.Again,Singapore appears to hav
134、e been at the forefront in this respect.Frequently updating its regulation has helped it to apply a judicious combination of carrot and stick designed to safeguard consumers rights without hampering data-driven innovation.An amendment to Singapores Personal Data Protection Act in 2020 has required l
135、ocal organisations to appoint data protection officers to cultivate an accountability culture.Another recent amendment calls for them to notify the Personal Data Protection Commission of data breaches if they are likely to result in significant harm to the individual or if they affect more than 500
136、individuals.The maximum fine for violation of PDPA obligations,meanwhile,is being increased to 10%of local annual turnover for organisations at which this exceeds$10m.Elsewhere in the Asia Pacific region,one regulator noted that it aims to maximise consumer protection through the rigorous applicatio
137、n of the five-safes framework to the management of its dataset.This is an internationally recognised approach to considering strategic,privacy,security,ethical and operational risks as part of a holistic assessment of the risks This commissions primary aim is to ensure that personal information cont
138、rollers,especially in the financial sector,are resilient and are able to comply with global standards when it comes to data protection,The process of granting the consent and the extent of usage needs to be determined not just by data subjects who may not be fully aware of their rights,but by govern
139、ment regulation.13omfif.orgassociated with data sharing or release.Combating re-identification risk was mentioned as an important part of regulators toolbox for protecting consumers privacy.The information in our datasets is de-identified,said one respondent in the Asia Pacific region.But as you add
140、 more datasets the risk of re-identification rises.So,it is essential that the data is kept secure and accessed only by those who are permitted to do so.Other respondents suggested that because the data revolution is still in its early stages,it is unlikely that the full implications of data storage
141、 and sharing will be fully understood by the general public.This means that responsibility for personal data security must not be heaped entirely on to the shoulders of data subjects themselves.It is not enough for data subjects themselves to grant consent for the sharing of their data,said one Lati
142、n American respondent.The process of granting the consent and the extent of usage needs to be determined not just by data subjects who may not be fully aware of their rights,but by government regulation.This implies that public education about data storage,usage and sharing needs to be a core compon
143、ent of regulators broader responsibilities.Education of the public and industry is important to raise awareness of the obligations in the PDPA for organisations and the safeguards in place for individuals,Singapores commission reported.The PDPC holds regular events,which are open to the public,to hi
144、ghlight the importance of the data protection obligations and how they may be implemented.Advisory guidelines are also issued to help businesses interpret how the PDPA may apply in certain situations.Respondents shared the Singaporean view that the protection of data privacy is a fluid process which
145、 should be adaptable and updatable in response to market innovation.One European authority was confident that its national data protection law and GDPR combined to create powerful legislation for data privacy.But it added that it is keeping a watchful eye on the evolution of cryptocurrencies based o
146、n distributed ledger technology which could present a challenge to the guarantee of data subjects rights as stipulated in GDPR.Discussions on how to deal with this challenge are ongoing,this regulator noted.Others said they were confident that GDPR has raised the bar close to the highest possible le
147、vel in the pursuit of data privacy.The overarching application of the GDPR to controllers carrying out any kind of activity involving the processing of personal data is considered to be a gold standard,sufficient to guarantee the protection of data subjects in respect of the collection,use and event
148、ual retention of their personal data,said one EU-based respondent.Question 5 Do you perceive tension between meeting Anti Money Laundering and Combating the Financing of Terrorism compliance obligations and fraud detection and data privacy regulations?How can compliance policies evolve to reflect th
149、e increased reliance of consumers on digital information in the financial sector(and more broadly)?Few of the respondents to the OMFIF survey believed there was any tension between AML/CFT compliance obligations and the protection of data privacy under GDPR or other local regulations.The provisions
150、of our national AML act are applied in accordance with the provisions and principles of the GDPR,in particular the requirements of necessity and proportionality,said one EU regulator.In practice,these require case-by-case consideration and monitoring.One Asian respondent went a step further,arguing
151、that AML and CFT compliance requirements should be regarded as complementary to data privacy obligations:We believe that the backbone of strong law enforcement surveillance is the implementation of relevant data privacy regulation.Effective,efficient,and accurate surveillance and law enforcement can
152、 only be possible if there is integrity in the personal data being shared by law enforcement authorities.Clearly the concepts of data privacy and AML/CFT strengthen each other,resulting in a more holistic approach towards protecting the financial sector.While most respondents indicated that they dis
153、cern no tension between data privacy regulation and compliance obligations in areas such as anti-money laundering,a handful acknowledged that this is unavoidable.Tension does indeed exist between the two pieces of legislation,said another EU regulator.Having said that,one must surely and equally rec
154、ognise that there are certain common elements found in both AML/CFT and GDPR,including but not limited to,the risk-based approach and the requirement to have in place a proper and effective compliance programme(accountability).Moreover,obliged entities should ensure that they do not adopt a one size
155、 fits all approach in relation to the processing of personal data for the purpose of fulfilling their AML/CFT obligations.Question 6Do you see any tension in the policy-making space between the application and use of user data in financial services and privacy considerations?Similarly,few of the reg
156、ulators interviewed by OMFIF believed that there was any tension between the harnessing of individuals data and privacy considerations in the financial services sector.Some noted,however,that minimising these tensions can be a delicate balancing act,calling for what one European regulator described
157、as continuous political discourse.Others added that as this ongoing discourse should involve the general public,policy needs to be communicated clearly and free of technical jargon or impenetrable small print.Restrictions on data subjects Clearly the concepts of data privacy and AML/CFT strengthen e
158、ach other,resulting in a more holistic approach towards protecting the financial sector.14Data:Towards a new age of economic enlightenmentrights,such as the processing of personal data,must be proportionate to the objectives pursued,said one EU-based respondent.In setting a policy on the processing
159、of users personal data in financial services,it is important that the legal provisions are worded in a sufficiently comprehensible and predictable manner to make clear the extent to which and the conditions under which the right to restrict the privacy of data subjects is exercised.The need for cons
160、istent and clear communication stripped of jargon is perhaps more pressing in emerging than in developed economies.Our priorities are to ensure that financial service providers properly and consistently communicate the data use proposition to customers despite the possibility of having adequate lega
161、l basis for the processing,said one African regulator.Due to the low rate of literacy around data,the burden is on the data controller to show it has expended sufficient efforts and resources to educate the data subject.As with their responses to the first question in the survey on public policy out
162、comes,regulators suggested that their ultimate objective is to respect consumers privacy without discouraging innovation in financial services.This is a combination which has allowed open banking to thrive in a number of countries and is a blueprint which could be applied to other sectors.Some belie
163、ve that encouraging innovation has the potential to generate tensions between data privacy laws and the regulation of financial services.Yes,there is some tension between these parties because two divergent interests are at play,said a regulator in a leading African economy.Financial service provide
164、rs are innovators who seek to use the available data to create new valuable products.Privacy regulators principally seek to protect the privacy rights of the data subject,hence,the divergence of philosophy and approach.We see that this conflict can be moderated by having a comprehensive data policy
165、and strategy that addresses the various interest points.It is the policy of the state to promote the free flow of information that will benefit our society,said one Asian regulator.In line with this policy,this authority explained that it is planning to experiment on alternative regulatory approache
166、s that would allow innovation to flourish while ensuring data protection such as the conduct of innovation hubs or regulatory sandboxes.It added that it was empowering developers and coders of applications to ensure that privacy-by-design is met at the onset of the software development.Question 7Are
167、 there instances or specific use cases where you believe it is important to allow an entity(individual,business or government)to access aggregated user data?It is clear from the responses to this question that the efficient aggregation of data is already having a substantial and often measurable pos
168、itive impact across wide cross-sections of society.Beyond its use to combat money laundering,the financing of terrorism and other criminal activities,aggregated data use was mentioned by respondents as having a constructive supporting role to play in the delivery of government services and research.
169、For example,one respondent pointed to the extensive analysis that data-based research has underpinned in areas such as domestic violence and the protection of vulnerable children.Data analysis has also been used by this government,for example,to conduct more granular research into the impact on soci
170、ety of penal financial measures such as traffic fines.For young people aged 18 or 19,fines for minor traffic infringements can be disproportionately large,this interviewee explained.Financial penalties of this size can kickstart a cycle of problems.The benign use of data of this kind is valuable,thi
171、s regulator noted,because of their potential to strengthen public buy-in for the collection,storage and analysis of personal data.More broadly,some regulators were again eager to emphasise that there are tangible economic gains to be generated from the analysis of aggregated user data.We see allowin
172、g businesses to access data,particularly business data(which may or may not encompass aggregated user data)as being important to drive economic growth,but we want to balance that with the responsible use of data,said one respondent.Our approach goes beyond just supporting the disclosure of aggregate
173、d data,which is limited to specific use cases,to supporting the disclosure of anonymised data.Financial service providers are innovators who seek to use the available data to create new valuable products.Privacy regulators principally seek to protect the privacy rights of the data subject,hence,the
174、divergence of philosophy and approach.We see that this conflict can be moderated by having a comprehensive data policy and strategy that addresses the various interest points.Our approach goes beyond just supporting the disclosure of aggregated data,which is limited to specific use cases,to supporti
175、ng the disclosure of anonymised data.Aggregation of the user data is just one means of anonymisation of the data.We believe a more holistic approach that supports disclosure and use of anonymised data in a responsible manner will be more useful for businesses.15omfif.orgAggregation of the user data
176、is just one means of anonymisation of the data.We believe a more holistic approach that supports disclosure and use of anonymised data in a responsible manner will be more useful for businesses.In the financial services industry,meanwhile,some respondents identified open banking as an area which cou
177、ld not have flourished without access to aggregated user data.A private-sector initiated open banking scheme has been approved by our central bank,said a regulator in Africa.This allows financial sector players to share customer data within the industry based on compliance with national data privacy
178、 regulation and other relevant laws.We foresee instances like these growing in the future.Question 8Do you have a view on data sharing between companies and data portability?Data portability is defined as the ability for users to access and move their personal data across different applications,prog
179、rammes and platforms.Regulators interviewed by OMFIF were generally positive about data sharing,although some confusion appears to exist at a grass roots level about the meaning and potential benefits of data portability.One EU interviewee,for example,noted that data subjects are still unfamiliar wi
180、th the concept of data portability and their right to it,and that there is room for improvement in this area.Another added that although article 20 of GDPR requires data controllers to respect consumers data portability,the right to portability is still not widely applied,meaning that its full poten
181、tial remains to be seen.This view was shared by an African regulator,who expressed the view that data portability remains inadequately defined,especially in developing countries.This may represent a missed opportunity,because others emphasised that in some areas,most notably open banking,data portab
182、ility is a prerequisite.As one Asian regulator explained,with the advent of financial and digital service platforms,there is a need to ensure that there is seamless availability of personal data between these entities to effectively provide said services.This can only be achieved if data portability
183、 is unimpeded.This respondent added that should such data portability be allowed,it is crucial for joint controllers of personal information to comply with all relevant data protection laws,rules and policies and be made aware of their joint responsibilities to their data subjects.Moreover,the shari
184、ng and porting of data from one platform to another may create risks,especially during the data transfer process.In this context,all the parties or institutions that control or process the data throughout its lifecycle have a role to play in ensuring that the data is protected.Several respondents st
185、ressed that promoting public trust in data sharing is of paramount importance if its full economic and social benefits are to be harnessed.This was emphasised by the Personal Data Protection Commission in Singapore,which has established a trusted data sharing framework.This is a distillation of the
186、experience from our engagement with companies who are collaborating on data sharing,it explained.The purpose of the framework is to guide companies intending to share data,and to provide a common language and resources to help companies to share data in a responsible manner.This is applicable both t
187、o domestic and cross-border data sharing.This will promote good practice standards and build consumer trust,which can act as a competitive differentiator.As an example of how Singapore is applying data sharing to support economic development,the Commission pointed to the launch in September of the b
188、etter data driven business programme.This initiative aims to support SMEs that are starting to learn to use data to generate insights and those that seek to apply and share data for more complex purposes.The programme is designed to help businesses learn how to collect data safely,combine data acros
189、s systems with adequate data protection measures,and share data externally with partners and suppliers in line with the PDPA obligations.With the advent of financial and digital service platforms,there is a need to ensure that there is seamless availability of personal data between these entities to
190、 effectively provide said services.This can only be achieved if data portability is unimpeded.16Data:Towards a new age of economic enlightenmentWERE going to get the world flying again,British Airways pledged in two-page advertisements which it placed in broadsheets such as The New York Times in mor
191、e than 70 countries a tactic which ultimately showed the airlines prescience in harvesting data,long before the use of such data became the vital business tool it has become today.It was 22 March,1991 and BA had had a terrible year.Following Saddam Husseins invasion of Kuwait in August 1990,passenge
192、r numbers for international airlines plummeted.The engine of consumer demand did not just idle in neutral,said Lord King,chairman of BA,in March 1991.It spluttered to a complete halt1.But BA had other worries besides Iraqs warmongering,which had left one of its Boeing-747s smouldering on the tarmac
193、at Kuwaits international airport.A precocious rival,Richard Bransons Virgin Atlantic,was eating into BAs share of the lucrative transatlantic route.Britains flag carrier decided to fight back.British Airways doesnt make money by helping old biddies to the gate,one of the airlines trouble-shooters is
194、 alleged to have told staff in the late summer of 1990.From now on we must get more passengers from other airlines2.BAs first response to sinking passenger demand and the threat from Branson was its disastrous dirty tricks campaign.This involved tapping into Virgins computer system to access confide
195、ntial information about its rivals passengers,who were then offered inducements such as seats on Concorde to switch their bookings to BA flights.In other words,data theft.When Branson complained to the European Commission in January 1991,BA changed tack.With the help of Saatchi&Saatchi,it launched w
196、hat it called“The Worlds Biggest Offer”,promising to give away every single seat,in all cabin classes,across its entire network on 23 April,1991.Will it be Hong Kong?Rome?Sydney?Rio de Janeiro?Moscow?the BA advertisement asked.The choice is yours.BAs bold gambit had three aims.First,an image makeove
197、r:it had to convince the public that far from being the wicked stepsister that the dirty tricks campaign had suggested,BA was everybodys favourite uncle.Second,by dangling the lure of romantic and far-flung destinations,it reminded customers of the thrill of travel.But third,and probably most import
198、ant,BA gained an instant database of potential customers which was larger,more international,more detailed and more legitimate than anything it could pinch from a competitors computer system.Entrants in BAs sweepstake provided their addresses and telephone numbers,named three destinations they would
199、 choose to fly to if they won,and were asked to provide details of their various frequent-flier schemes.Readers of the ad in The New York Times were asked how often they had flown to Europe on business or for pleasure,and to say whether they had done so on Concorde,or in First,Business or Economy cl
200、ass.BA estimated that 500m people read about its campaign,and that Chapter 2The fundamental role of dataHarnessing the potential of data is a discipline still in relative infancy.But it will be crucial to future economic performance and lessons for the financial sector can be learned from other sect
201、ors.17omfif.org200m saw it advertised on television.More to the point,5.7m entered the ballot for free flights.In other words,at a stroke,BA had built a rich dataset of almost 6m prospective customers,complete with details about where they wanted to travel,which cabin they expected to fly in,and whi
202、ch competing airlines they favoured.In the short term,it was an expensive database.The New York Times reported that it cost BA about$18m in lost revenue alone3.But BA was ahead of its time in recognising the commercial importance and value of data.Three decades later,Ryanair made no secret of its am
203、bition to become the Amazon of the travel industry;more broadly,according to Accenture,airlines regard big data as more of a priority than companies in the manufacturing,power generation and oil and gas sectors4.Not that the notion of big data would have meant much to the general public in the early
204、 1990s.At the time of BAs offer,Mark Zuckerberg was only six years old while Jeff Bezos was still only crunching numbers at the New York-based hedge fund,D.E.Shaw.There was nothing intrinsically new about the data BA was so eager to lay its hands on in 1991.It knew that there was a vast reservoir of
205、 potential customers in the various countries it serviced around the world.But it did not have their names,addresses,or profiles.That meant that to BA,their data was like oil.Useless if it remained undiscovered and untouched below the surface;of inestimable value if it could be extracted,refined,and
206、 magically transformed into an asset that could be monetised.Anecdotally,it would be four years after BAs excavation of this rich seam of information that the term data is the new oil was coined reportedly by the data scientist who was behind UK supermarket Tescos loyalty card,which was introduced i
207、n 1995.What is data.?The tools used by the airlines and supermarkets of the 1990s to excavate the data they needed were rudimentary.Today,the raw data that is the lifeblood of their business is broadly similar to the information they valued so highly in the 1990s,but with two important differences.T
208、he first is that thanks to digitalisation,there is far more data available than the architects of the Worlds Biggeest Offer or the Tesco loyalty card would have dreamed possible.The marketing gurus of the 1990s may not have known the difference between a brontobyte and a zettabyte,but nowadays,those
209、 with a grasp of byte nomenclature will tell you that what IDC describes as the global datasphere will grow from 33 zettabytes in 2018 to 175 zettabytes by 20255(1 ZB is 10 to the power of 21 bytes).Figure 400200Zetabytes2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 20
210、21 2022 2023 2024 2025ChinaEMEAAPJxCUSROW2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 202500Zetabytes175 ZB1.Size and growth of the global datasphere annually and by region,ZetabytesSource:IDCs Data Age 2025 studyAt a stroke,BA had built a rich dat
211、aset of almost 6m prospective customers,complete with details about where they wanted to travel,which cabin they expected to fly in,and which competing airlines they favoured.18Data:Towards a new age of economic enlightenmentA helpful starting point to grasp the significance of this colossal resourc
212、e is to understand what is meant by data.In the age of digitalisation,data is generally understood to refer to the raw information embedded in the text,audio,video and web-generated records that have proliferated over the last two decades.The magnitude of this expansion has called for a more precise
213、 term to describe data larger than a terabyte.To illustrate the size of a terabyte,think of 250m double-sided,single-spaced,printed pages,said Scott W.Bauguess,the acting director and acting chief economist of the division of economic and risk analysis at the US Securities and Exchange Commission,in
214、 a speech6 in 2017.This mountain of virtual paper and spreadsheets is now commonly(if unimaginatively)referred to as big data.Amazon Web Services defines this as data management challenges that due to increasing volume,velocity and variety of data cannot be solved with traditional databases7.Much of
215、 this data is derived from three primary sources,generally labelled social,machine and transactional data.Social data refers to information derived from sources generated by humans such as blogs,videos,internet searches and media shared on social networks.Machine data,or the Internet of Things(IoT),
216、includes computers,sensors and any other device capable of transmitting data across a network without human intervention.An example of this is the Apple Mobility Trend reports tracking the number of requests for directions made by users on Apple maps.Finally,transactional data is the footprint left
217、by anything that digitalises a purchase or sale.Simple examples include bills,invoices,credit card receipts and bank statements.Figure 2.and how is it stored?The size and ubiquity of this data,plus the speed at which it is mushrooming,have led to increasingly demanding requirements for its collectio
218、n and secure storage.This,in turn,has driven the growth of cloud object storage(COS)services capable of storing hundreds of petabytes of data on a highly cost-effective basis.Leading cloud storage providers offer a continuously evolving suite of related services allowing users to address their data
219、growth,data resilience,and cloud migration strategies through a platform of tools and services,which go well beyond storage capacity8.Our data is estimated to be growing at an annual rate of 30%while at the same time,enterprises in the public and private sectors face an increasingly unpredictable ra
220、nge of influences on their storage requirements,and rising pressures on their IT budgets.As a result,the market for COS services is expected to grow at double-digit annual rates over the next few years,from$16.3bn in 2020 to approximately$40bn by 2024,according to projections made by International D
221、ata Corporation9.Figure 3All the right notes,but not necessarily in the right order?A powerful driver of the evolution of 2.Big data sourcesStructure(high to low)and size(small to big)Source:Dell Technologies0000224($bn)3.Cloud-Based Object Storage Market,
222、20152024IDCs Public Cloud Object Storage Services Growth and Forecast,20152024,$bnSource:IDCs Worldwide Semiannual Public Cloud Services Tracker,1H20BigAlternativeTraditional Weather forecastingStructure(high to low)Size(small to large)Earnings call transcripts Corporate geographic movements Corpora
223、te ESG disclosures Crowdsourced reviews Online search trends Product patents Shipping data SEC filings Transportation data Mature Semi-mature Least mature Brand and trademark data Expert networks Short interest data Fundamental data Macroeconomic data Trade data Daily market data Product reviews Ven
224、ture capital data Supply chains Corporate inventories Analyst estimates Satellite image data Company director data Geo location data Machine readable news Employee data Social media data Point of sale transactions Online browsing Credit card transactions Ownership data Intraday marketing data Tick d
225、ata Product approvals19omfif.orgcloud storage services is that while gathering and warehousing data is one thing,turning it into a usable and profitable resource is quite another.The agents of this alchemy are artificial intelligence(AI)and machine learning(ML),used to translate this reservoir of da
226、tasets into information which is accessible and comprehensible to individuals,businesses and governments.The alchemists themselves are those who,as the Harvard Business Review put it in 2012,can coax treasure out of messy,unstructured data.This,the publication said,makes data science the sexiest job
227、 of the 21st century10.Sexy,and lucrative.In a report published in 2016,McKinsey noted that with demand far outstripping supply,salaries for data scientists in the US were rising at well above the national average,and companies that wanted to buy data expertise were paying up to do so.The scarcity o
228、f elite data scientists has even been a factor in some acquisitions of cutting-edge artificial intelligence(AI)start-ups;deals can command around$5m to$10m per employee,McKinsey reported11.The dynamics of the so-called data revolution raise two overarching and closely related questions.The first add
229、resses whether increased efficiencies and technological innovation in the harnessing of data generates proven and measurable social and/or economic benefits.The second asks whether the way in which data is now being leveraged is sufficiently regulated or ethically desirable.Neither of these question
230、s is likely to be answered decisively in the short term.But each will be explored in the course of this paper because they are at the heart of a debate that has become increasingly animated over the last decade.A data success story:Harnessing the power of data-driven innovation in healthcareThe heal
231、thcare sector provides some of the most compelling and demonstrable proof of the benefits that data science and AI can generate.It is also a sector in which trust in data science is paramount.After all,terms such as everolimus and vandetanib are probably as incomprehensible to those outside the medi
232、cal profession as zettabytes are to data laymen.But to children suffering from diffuse intrinsic pontine glioma(or DIPG)these two drugs may be life-savers,thanks to advanced oncological research supported by artificial intelligence.In September 2021,the London-based Institute of Cancer Research anno
233、unced the results of its research into how the combination of everolimus and vandetanib could be used to treat a rare and previously incurable childhood brain cancer.As survival rates among DIPG patients have remained unchanged for the last 50 years,data-crunching appears to have succeeded where fiv
234、e decades of medical research have failed in countering this disease.Our study demonstrates just how much AI can bring to drug discovery for cancers like DIPG,in proposing new treatment combinations that would not have been obvious to people,said Chris Jones,the ICR professor who led the study12.The
235、 initial hypothesis for the breakthrough DIPG study came from the company BenevolentAI,which has mined data to build a leading AI drug discovery platform and an in-house pipeline of drug discovery programmes to treat certain medical conditions.These range from atopic dermatitis to inflammatory bowel
236、 disease and neurodegenerative disease as well as several types of cancer.At the core of this initiative is BenevolentAIs Knowledge Graph,which is its tool for capturing the interconnectivity of all relevant data and scientific literature.Given that more than a million scientific articles are publis
237、hed every year in the biomedical domain alone,this is a formidable task.As BenevolentAI explains in a blog aimed at demystifying the application of AI and ML in drug discovery13,biological data is messy and incomplete.It may contain conflicting or contradicting evidence,suppositions,biases,uncertain
238、ty,gaps in knowledge or misclassifications.True enough.But making sense of this mountain of information amounts almost to childs play alongside the analysis of biological interactions and the efficacy of molecule drugs.BenevolentAI describes the number of possible The healthcare sector provides some
239、 of the most compelling and demonstrable proof of the benefits that data science and AI can generate.20Data:Towards a new age of economic enlightenmentmolecules as staggering,adding that there are more possible molecules than there are particles in the universe.Beyond its contribution to medical res
240、earch,data is considered the key to unlocking increased efficiencies and cost savings in public health systems that in many countries account for a considerable chunk of government spending.The UK,for example,spends close to 10%of its GDP on healthcare.This is a similar level to economies such as Au
241、stria and Australia,but slightly below that in other high-income countries including Germany,France and Sweden,where healthcare expenditure equates to 11%or more of GDP14.AI can be deployed in just about any facet or activity of the health sector,from clinical decision-making and public health,to bi
242、omedical research and drug development,to health system administration and service redesign,noted an OECD working paper published in June 202115.There is particularly promising potential to:tackle unwarranted variation in care;reduce avoidable medical errors;lessen inequalities in access,health and
243、healthcare;and cut down on waste and low-value care.Estimating the direct and indirect socioeconomic impact that data-driven technological innovation has or may have on health systems is imprecise.But in a report commissioned by MedTech Europe in 202016,Deloitte came up with the following:that 400,0
244、00 lives could be saved annually through wearable AI apps,monitoring apps and imaging,generating annual savings of some 200bn.This equates to about 12%of total European healthcare expenditure in 2018.The estimate takes into account the opportunity costs arising from AIs potential to free up 1.8bn ho
245、urs per year of healthcare professionals time equivalent to adding 500,000 full-time healthcare workers.This suggests that the harnessing of data and the use of AI and ML has the potential to generate extensive productivity gains,cost savings and tangible social benefits.But there are several proble
246、ms that will need to be addressed by public and private stakeholders if these outcomes are to be achieved.The Deloitte report identifies four of these,most of which are equally relevant to other areas in which data is being applied to improve efficiencies.The first of these is the challenge associat
247、ed with the fragmented data landscape and interoperability,as well as those presented by data quality,data privacy and protection,and cybersecurity.The second is the legal and regulatory challenge created by the plethora of different frameworks governing AI in healthcare.The third embraces the organ
248、isational and financial requirements arising from the digitalisation of European healthcare systems,requiring substantial investments in areas ranging from infrastructure to technology and training.Finally,social challenges need to be addressed regarding trust,governance and patient empowerment.The
249、UK is an example of a country with a stretched public sector healthcare system that has already had experience of tackling some or all of these challenges.The results to date have been disappointing,but have provided some useful benchmarks for large healthcare systems burdened with legacy infrastruc
250、ture.As long ago as 1998,the UKs National Health Service(NHS)identified the importance of seamless sharing of data between IT systems in supporting much-needed efficiency enhancements across the service.But according to a report published by the National Audit Office(NAO)in May 2020,the digital tran
251、sformation programme originally launched in 2002 was both expensive and largely unsuccessful17.A new unit,NHSX,set up in July 2019,is the UKs most recent initiative aimed at leading the digital transformation of the NHS based on giving NHS trusts more autonomy over the development of their IT system
252、s.The UK recognises that leveraging data in order to enhance efficiencies will be an uphill battle.Digital transformation of the NHS is a huge challenge,says the NAO report.The need for large-scale process and behavioural change and for substantial financial investment in IT systems mean that digita
253、l transformation is inherently difficult.In the NHS,transformation is further complicated by major challenges including aged(legacy)IT systems,the nature of healthcare information,the large number of organisations and stakeholders,complex governance arrangements,and existing commercial arrangements
254、with technology suppliers.Datanomics:The impact of data on macroeconomic performanceWhile the jury is still out on the overall contribution made by digitalisation to measurable improvements in the efficiency of public healthcare systems,much of the impact of data science and AI on macroeconomic perf
255、ormance remains unproven.Data access and sharing is more important today than ever before,noted the OECD in November 2019.The effective use of data can help boost productivity and improve or foster new products,processes,organisational methods and markets.This is particularly evident in data-rich se
256、ctors such as healthcare,transportation and public administration,as well as in new production platforms in manufacturing and services.With the increasing adoption of artificial intelligence and the Internet of Things across economies,the supply of,and demand for,data will grow even in traditionally
257、 less data-intensive fields.One self-driving car,for example,can generate up to 5 terabytes of data per hour,but requires access to additional third-party data to operate securely in different traffic,weather and street conditions.Access to data is therefore crucial for competition and innovation in
258、 the digital economy not only for businesses,but also for governments and individuals,added the OECD.Overall,data access and sharing is estimated to generate social and economic benefits worth between 0.1%and 1.5%of gross domestic product(GDP),in the case of public-sector data,and between 1%and 2.5%
259、of GDP when also including private-sector data18.Other industry specialists sharing this view on the potential contribution 21omfif.orgof data and AI to the global economy include the McKinsey Global Institute.In a study in 2018,it projected that AI could lead to additional economic output of about$
260、13tn by 2030,or about 1.2%additional GDP growth a year,although it warned that the benefits are unlikely to be evenly distributed.A key challenge is that adoption of AI could widen gaps between countries,companies,and workers,said MGI.AI may widen performance gaps between countries.Those that establ
261、ish themselves as AI leaders(mostly developed economies)could capture an additional 20%to 25%in economic benefits compared with today,while emerging economies may capture only half their upside.There could also be a widening gap between companies,with frontrunners potentially doubling their returns
262、by 2030 and companies that delay adoption falling behind.For individual workers,too,demand and wages may grow for those with digital and cognitive skills and with expertise in tasks that are hard to automate,but shrink for workers performing repetitive tasks19.Harnessing the data delugeTransportatio
263、n and logistics are two sectors in which data-driven innovation was identified early on as having considerable potential to drive added value.These sectors grease the wheels of commerce and international trade,playing an important role in supporting economic growth,elevated productivity and job crea
264、tion.Almost a decade ago,Oracle was making enthusiastic forecasts about the potential of data to underpin productivity improvements across the logistics sector.2012 will see the true emergence of the“data deluge”the flood of near real-time data that businesses are collecting through a variety of sou
265、rces,ranging from sensors and smart phones to business-to-business data exchanges,Oracle predicted.We are also entering an era of unprecedented levels of real-time visibility to new data through mobile devices in the logistics industry,Oracle added.There are new data sources supplying real-time supp
266、ly-chain data everywhere we look.Electronic On Board Recorders(EOBRs)in trucks,sensors and RF(Radio Frequency)tags in trailers,RF readers in distribution centres,and the massive numbers of new handheld devices(smart phones and tablet PCs)are all sending,receiving and processing huge amounts of data
267、that have not been part of our business world until now.Positive train control,EOBRs,RF tags,and mobile devices will have an increasing impact on the amount of data that shippers,logistics service providers,and carriers need to process to manage logistics.For shippers,especially retailers,social net
268、works and personalised websites will offer whole new ways of reaching customers,and will consequently impact logistics as customer demand spurs orders,said Oracle.The impact on costs was expected to be dramatic.As Oracle noted,the US alone spent over$1.1tn on logistics,representing about 10.2%of gro
269、ss domestic product(GDP).Logistics costs represented an even greater share of the GDP in developing economies,accounting for 15%to 16%of GDP in China,and 11%to 13%in India.In the shipping sector,the data deluge foreseen by Oracle failed to prevent a spike in costs which rose to unprecedented levels
270、during the pandemic.The industry,which is responsible for transporting about 80%of global trade,appears to have been slow to respond to some of the data-driven opportunities that have arisen over the decade.This suggests that shipping will need to sharpen its focus on digitalisation The(shipping)ind
271、ustry,which is responsible for transporting about 80%of global trade,appears to have been slow to respond to some of the data-driven opportunities that have arisen over the decade.This suggests that shipping will need to sharpen its focus on digitalisation if it is to support an accelerated recovery
272、 from the global public health crisis.22Data:Towards a new age of economic enlightenmentif it is to support an accelerated recovery from the global public health crisis.Go paperless was one of 10 recommendations made in an UNCTAD policy brief on the shipping sector in April 202020.Although goods sti
273、ll need to be moved physically,clearance operations and the exchange of information should make use of existing electronic data interchange as much as possible.Electronic alternatives to traditional,paper-based negotiable bills of lading should be used by contracting parties where possible,UNCTAD re
274、commended.Data-driven efficiency gains in transportation can mean substantial savings for companies with a global reach such as Unilever.Household staples such as its detergents,washing powders and tea bags are sold to some 2.5bn customers in 190 countries.Unilever says that to keep these products f
275、lowing freely across the world,at any given time it has approximately 12,000 containers on 1,500 ships criss-crossing the seas with raw materials,packaging and finished goods.With a view to ensuring that the multitude of information systems involved in this labyrinthine network communicate more effi
276、ciently with one another,Unilever has developed a Virtual Ocean Control Tower.This connects 25 shipping lines and uses satellite data to track more than 2,000 vessels and 400 ports.It is,says Unilever,a first-of-its-kind digital innovation that has transformed how we manage our sea freight logistics
277、.This unmanned system seamlessly connects all parties in the chain through a real-time electronic data interchange(EDI)information flow,Unilever says.That means we have at our fingertips highly accurate,continually updated data on the status of each shipment at every stage of its journey,from its po
278、int of departure to when it reaches the distributor,store or factory.Crucially,the system uses machine learning and predictive analytics,so every potential issue along the way from port congestion to demurrage and detention charges,temperature deviation and ETA changes is proactively identified and
279、an alert automatically sent to everyone who needs to know21.The Productivity paradoxThe Unilever project sounds impressive,not least because it has environmental as well as productivity advantages.Theoretically,if initiatives of this kind could be replicated across the global transportation sector,a
280、nd if the benefits foreshadowed by Oracle a decade ago could be applied to logistics,the data deluge it predicted in 2011 could result in substantial gains in productivity.The same is true across a wide cross-section of industries.In the oil exploration sector,for example,Schlumberger has long been
281、a leader in data-driven innovation.It has recently expanded its digital drilling planning and operations portfolio through the acquisition of Independent Data Services(IDS),a provider of cloud-delivered reporting and analytical services to the upstream oil and gas industry.Schlumberger says that IDS
282、s automated software transforms the daily reporting and monitoring of rig site operations from a time-consuming,labour-intensive and costly activity into a steady flow of relevant data which is processed and stored in near real time.An analysis published in 2019 by the energy research and consultanc
283、y company,Wood Mackenzie,concluded that companies that embrace digitalisation could potentially make operational cost savings of as much as$150bn per annum:it added that at a time when the oil and gas industry is facing an existential crisis because of the transition to other forms of energy,digital
284、isation could be key to the industrys survival22.As early as 2011,McKinsey identified five ways in which big data could be used directly or indirectly to create value.First,it could make information transparent and usable at much higher frequency.Second,by creating and storing transactional data in
285、digital form,organisations could collect more accurate and detailed performance information on topics ranging from product inventories to sick days,and therefore expose variability and boost performance.Third,by allowing for ever-narrower segmentation of customers,products and services could be more
286、 precisely tailored to meet demand.Fourth,sophisticated data analytics could improve decision-making.And fifth,big data could be deployed to improve the development of the next generation of products and services.Based on these drivers of value,McKinsey selected five domains representing close to 40
287、%of global GDP which had the potential to be transformed by big data23.These were healthcare and retail in the US,the public sector in Europe,and manufacturing and personal location At a time when the oil and gas industry is facing an existential crisis because of the transition to other forms of en
288、ergy,digitalisation could be key to the industrys survival.23omfif.orgdata globally.McKinseys findings were eye-catching:describing big data as the next frontier for innovation,competition and productivity,it calculated that a retailer maximising this powerful new resource could increase its operati
289、ng margin by more than 60%.Harnessing big data in the public sector has enormous potential,too,McKinsey added.If US healthcare were to use big data creatively and effectively to drive efficiency and quality,the sector could create more than$300bn in value every year.Two-thirds of that would be in th
290、e form of reducing US healthcare expenditure by about 8%.In the developed economies of Europe,government administrators could save more than 100bn($149bn)in operational efficiency improvements alone by using big data,not including using big data to reduce fraud and errors and boost the collection of
291、 tax revenues.And users of services enabled by personal-location data could capture$600bn in consumer surplus.These were seductive numbers.But when the McKinsey Global Institute looked back on the forecasts it made in 2011 five years later24,it found that although the volume of available data had in
292、creased exponentially,companies were capturing no more than a fraction of the potential value embedded within.The greatest progress had been made in location-based services and retail,McKinsey reported in 2016:In contrast,manufacturing,the public sector and healthcare have captured less than 30%of t
293、he potential value we highlighted five years ago.Figure 4A more recent survey,conducted in late 2018 by the independent market analysis firm,BARC,suggested that much of the corporate sector in Europe had yet to implement the strategies required to generate as much tangible value from data as some of
294、 the early forecasts had projected.Only 17%of the 200+European companies BARC polled had established data monetisation initiatives,while a further 12%were building prototypes and another 10%were still at the concept development stage25.This was echoed in a PwC report released in 202026 which stated
295、that the data revolution was still in the earliest of innings.Quoting OECD figures saying that only 12%of companies in the EU had ever performed a big data analysis,PwC noted that the business world was barely skimming the surface of the ocean of data.Against this backdrop,it is not surprising that
296、little if any evidence has emerged to date to suggest that advances in data science and other technological breakthroughs over the last decade have had a significant quantifiable impact on productivity growth.As the OECD explained in its 2021 Compendium of Productivity Indicators,this is generally r
297、eferred to as the productivity paradox27.The increasing diffusion of digital technologies in the 2000s,this commented,was expected to unleash a new wave of productivity growth,similar to those that followed the advent of electrification in the mid-1880s and,to a lesser extent,Information and Communi
298、cations Technology(ICT)investments in the 1990s.However,said the OCED,this has not yet materialised,raising a number of still largely open questions,ranging from the potential lagged effects of these new technologies,to structural factors,right through to measurement.The OECD says that several expla
299、nations have been put forward for the persistence of this paradox.The first of these is that todays technological breakthroughs,while transformative in their nature and scale,pale into insignificance compared with those that took place in the past.The economic benefits from innovations such as elect
300、ricity,internal combustion engines,telephone and radio were all diffused over many years,the OECD says.ICT although revolutionary showed more rapid adoption and therefore may have had a shorter-lived impact on productivity and growth.The second is that the pace of technological progress has not slow
301、ed,but its adoption calls for parallel innovation in organisational structures and business models.The result may 24840348323566High2024 demand2024 supply4736Low3142014 supply2New graduates34.The expected number of trained data scientists would not be sufficient to meet demand in a high-case scenari
302、oSupply and demand of data scientists in the United States1,0,000s1.The calculation is across all Standard Occupational Classifications except the ones that are clear false positive hits.2.2014 fraction per occupation times the 2014 BLS EP employment per occupation,assuming the job market is in equi
303、librium and supply equals demand.Including 355 occupations.3.Graduates from US universities during ten years who are estimated to have the skill set required to be data scientists.Includes removing the retirement of 2.1%from current supply.4.For each industry we calculate the share individually for
304、the top five US companies based on their market capitalization.Professional services is an exception;there we use consulting companies irrespective of their home country.NOTE:Numbers may not sum due to rounding.SOURCE:US Bureau of Labor Statistics;Burning Glass;McKinsey Global Institute analysis24Da
305、ta:Towards a new age of economic enlightenmentbe that the next wave of productivity growth driven by technology breakthroughs in artificial intelligence,robotics,the Internet of Things,Big Data,3D printing,nanotechnology and biotechnology,may lag the innovations and take time to be fully deployed.Th
306、is dovetails with the findings of MGIs 2018 analysis on AI,which forecast that the economic impact may emerge gradually and be visible only over time.Our simulation suggests that the adoption of AI by firms may follow an S-curve pattern a slow start given the investment associated with learning and
307、deploying the technology,and then acceleration driven by competition and improvements in complementary capabilities,noted MGI.This projection is likely to be supported by believers in the powerful longer-term economic impact of AI,who argue that research into its potential is still in its infancy.On
308、e area where new opportunities are expected to proliferate is visual AI,the branch of computer science which trains machines to make sense of images in the same way that people do.As the advertising giant,WPP,explained in September 2021,visual AI works because its engines are trained by looking at h
309、undreds of thousands of categorised and labelled images:The visual AI engine then processes and learns from every pixel,so it can refine and expand its understanding of different objects.This matters because it enables retailers to enrich their product data with additional details that can be used t
310、o improve anything from site search to personalisation.Other explanations advanced by the OECD for the failure of data innovation to fuel economic growth include low managerial quality and inadequate workers skills which continue to curb the adoption of digital technologies,as well as demographic sh
311、ifts and changes in the way that productivity is measured.As the OECD puts it,new forms of doing business,driven in particular by digitalisation and the sharing economy,as well as the increasing importance of knowledge-based assets,have added new measurement challenges and exacerbated the long-stand
312、ing ones.The conclusions reached by the OECD on the relationship between digitalisation and quantifiable economic growth are similar to those outlined by the World Bank in an exhaustive analysis of global productivity trends,drivers and policies published in 202128.Critically,this emphasised that in
313、vestment in areas such as AI and ML can seldom be expected to generate short-term results.On the one hand,this advised,the impact on productivity growth of modern innovations seems to be reduced compared to those of the twentieth century.On the other,recently introduced new digital technologies and
314、those on the horizon such as artificial intelligence and innovations in ICT sectors may begin to feed through to measured productivity.Some of these innovations may require time to be widely adopted into production processes,resulting in an acceleration of productivity growth only after a long lag.T
315、his process may be accelerated as some innovations have been utilised and adopted more intensively because of social distancing measures to restrain Covid-19.The global corporate sector appears to share the view that the benefits of investment in digitalisation and AI will be incontestable over the
316、long term.As early as 2011,an MIT study of 179 large companies found that those adopting data-driven decision-making achieved productivity levels that were 5%to 6%higher than could be explained by other factors29.More recently,in a report published in 2017,PwC forecast that AI could contribute as mu
317、ch as$15.7tn to the global economy by 2030.To put this figure into context,it is more than the output of China and India combined at the time the report was written.Of this total,$6.6tn is likely to come from increased productivity,with the remaining$9.1tn generated through consumption side-effects.
318、The new heroes of data analyticsEvangelists of the data revolution believe that companies which are unable or unwilling to explore beneath the surface of this ocean of data will suffer.Simply put,argued Martina Koederitz of IBM Germany in a persuasive piece published by Forbes in February 2020,as mo
319、dern enterprises evolve,capitalising on breakthroughs in Internet of Things,artificial intelligence,robotics and blockchain to create new opportunities,the most successful among them are increasingly being built around data.She added:These companies recognise that the information generated from acro
320、ss daily operations will fundamentally change the way business is conducted.To thrive,they must become expert at identifying important data,applying the correct analytics to derive meaningful insights and using those insights to pursue new avenues for growth30.A striking indication of how attuned th
321、e corporate sector across the world is becoming to the competitive potential of big data has been the rise in importance of the chief data officer(CDO).In 2014,an IBM Global Business Services report described the CDO as the new hero of big data and analytics.By then,the job description already dated
322、 back over a decade:Capital One appointed Cathryne Clay Doss the worlds first CDO in 2002.Her responsibilities,and those of the CDOs who followed her,included defining,developing and implementing the strategy and methods by which the organisation acquires,manages and Capital One appointed Cathryne C
323、lay Doss the worlds first CDO in 200225omfif.orggoverns data,according to the IBM primer.This added that the CDOs job carried the strategic responsibility to drive the identification of new business opportunities through more effective and creative use of data.In 2012,only 12%of mainstream companies
324、 participating in an Executive Survey on big data and AI undertaken by advisory firm NewVantage Partners had firmly adopted the CDO role.By 2021,this had risen to 65%31.This increase is a telling barometer of the progress boardrooms worldwide have made towards enshrining big data and AI as a driver
325、of strategy and innovation.Looking back a decade to when this survey was first launched at the behest of a group of corporate executives,the interceding decade has represented a period of meaningful transformation for mainstream companies,NewVantage reports.Big data and AI were nascent capabilities
326、which received minimal investment.Firms had begun to think about what it would mean to be data-driven,but few had developed formalised programmes and articulated a corporate commitment.Today,the report adds,firms are deeply engaged in this transformation and there will be no turning back.The less po
327、sitive news is that it is questionable how well-defined the role of CDOs is.Just under half of the respondents to NewVantages 2021 Executive Survey on big data and AI feel that this role is still nascent and evolving.Data leaders whose views were polled by NewVantage indicated that they believe stro
328、ngly in the value of data,analytics and AI.But according to NewVantage,these leaders appear to be unconvinced that their role has been sufficiently well structured.And they are even less convinced that their company is on the right path toward data-driven cultures and organisations.It is this cultur
329、al underdevelopment,notes NewVantage,that presents bigger impediments for companies than technological challenges.The findings of the 2021 survey underline the challenges that data officers are facing:while 48.5%of respondents said that they were using data to drive innovation,only 39.3%indicated th
330、at their companies were managing data as a business asset,and less than one third had a well-articulated data strategy.As NewVantage observes,making a commitment to data-driven transformation is one thing;executing on that commitment is quite another.The global health crisis of 2020-21 appears to ha
331、ve strengthened companies commitment to harnessing big data as an asset.According to NewVantage,under 10%of respondents to its 2021 executive survey on big data and AI indicated that their company intended to reduce their investments because of the pandemic.More than 30%reported that they would be s
332、tepping up their investment.Aladdins cave or Pandoras box?A second question posed by the rise of digitalisation,data-driven innovation and AI centres around the controversial issue of its ethical and social utility.This in turn raises the topical question of whether current regulation of the data,AI
333、 and social media sectors is fit for purpose.This is a multi-layered question.At one level it addresses the relationship between technological progress and employment which has been the subject of debate since the industrial revolution.The question was asked again in the preamble to a Societe Generale research bulletin released in October 2021.As Artificial Intelligence unfolds and pervades every