1、Advanced analytics and the future: Insurers boldly explore new frontiers 2017/2018 P faster, easier information access (65%); more personalized experiences (61%); and more mobile-friendly applications (53%), with relatively minor differences in priorities among small, midsize and larger carriers. On
2、e area receiving closer attention from larger insurers, however, is the introduction of more product options. To help them achieve these goals, many insurers recognize the need to broaden their data horizons (Figure 2). This is exemplified by big jumps in proposed data usage for both auto and home t
3、elematics and web scraping in the next two years. Similarly, Figure 2 also shows a strong appetite for and belief in the benefits of telematics data, both for auto policies, where it is already established, and as an increasingly important factor for homeowners policies. We cover this in more detail
4、 below. Claim management The perceived potential of advanced analytics to transform claim management is evident from the dramatic expansion of data applications planned in the next two years (Figure 3). Closer attention to major sources of potential fraud is a high priority (e.g., excessive treatmen
5、t, the activities of fraud rings and inaccurate applications). Specific triage applications are likely to focus on analyses of claim amount (70%) and potential complexity (50%). It is recognized, however, that some lines of business are more inherently suited to more in-depth claims analysis. Person
6、al lines auto and home carriers alike anticipate large increases in advanced analytics use for claims over the next two years: from 23% to 68% of those surveyed for personal auto coverage, and from 18% to 54% for homeowners coverage. In commercial lines, existing claim analytics usage is highest in
7、the workers compensation class (27%) and is expected to grow to 65% in two years. Other commercial and specialty lines where carriers are looking to make big claim analytics gains in the next two years include commercial auto, accident and health, general liability, business owners and medical malpr
8、actice. In near orbit Customer focus, claims and telematics data Figure 2: Top data sources that insurers plan to use two years from now for customer centricity Figure 3: How advanced analytics will transform claim management NowTwo years Internal customer data 49%76% Customer interactions/ surveys
9、43%69% Auto telematics 24%57% Social media 18%45% Web scraping 6%37% Clickstream data 14%35% Home telematics 0%29% NowTwo years Evaluation of claims for fraud potential 26%82% Claim triage (identify complex claims to triage workflow) 26%80% Evaluation of claims for litigation potential 15%74% Evalua
10、tion of claims for subrogation potential 13%62% Advanced analytics and the future: Insurers boldly explore new frontiers 7 Telematics Usage-based insurance (UBI) programs have brought the benefits of telematics data in personalization and pricing to a significant proportion of U.S. personal auto car
11、riers, but also to around 30% of commercial auto insurers. Survey respondents expect UBIs influence to grow in the auto market, with 78% maintaining that UBI will play an important or driving role in rating plans within five years. Opportunities to use telematics and the technologies associated with
12、 the IoT to personalize risk assessment in the household and commercial property markets are following closely behind. Two years time is expected to make a marked difference from a position where very few carriers currently use telematics data (Figure 4). And telematics data use is also expected to
13、impact farm/crop insurance. Telematics data are expected to more heavily influence pricing and underwriting than other functions but are also seen as having wider applications from customer behavior modification (e.g., to tackle distracted driving) to claim triage and loss control (Figure 5). Figure
14、 4. Telematics data use by company size (auto and homeowners carriers) LargeMidsizeSmall NowTwo yearsNowTwo yearsNowTwo years Personal auto 50%94%13%50%0%71% Commercial auto 29%67% 0%22%0%33% Homeowners 0%65% 0%22%0% 0% Commercial property 0%38%13%38%0% 0% Figure 5. Five-year outlook for increased t
15、elematics impact on insurance business functions 90% Rating and pricing 51% Claim triage and analytics 61% Customer behavior modification 39% Loss control 80% Underwriting and risk selection Figure 6. Which internal and external data are most valuable to your company? Insurers stated advanced analyt
16、ics intentions and ambitions clearly affect the systems and technologies used to manage and move data, the analytical methods that will reveal insights from that data, and the technical resources and capabilities at their disposal. The range of internal and external data that companies say they find
17、 valuable is substantial and growing (Figure 6). As a result, the volumes and variability associated with such an array of data types and sources are becoming increasingly difficult to manage using internal capacity, networks and processing systems. So insurers are actively exploring technologies to
18、 help them manage big data principally, the cloud and Hadoop (Figure 7). Inner space The analytics environment 0%50%100%0%50%100%0%50%100% None of these Loss control/Premium audit Geographic crime information Vehicle history Sociodemographic information Additional non-credit attributes specifi c to
19、policyholders Account/Household penetration Account experience Internal billing information for existing business Geodemographic information Vehicle characteristics Property characteristics Weather information Prior claim attributes (CLUE) External credit/Financial attributes PrimarySecondaryTertiar
20、y Personal linesStandard commercial linesSpecialty lines 96 89 89 85 85 82 82 70 63 59 59 59 56 24 4 71 68 46 64 68 68 57 82 29 75 50 43 50 54 7 91 55 64 55 36 64 36 91 36 73 36 18 55 46 0 8 Advanced analytics and the future: Insurers boldly explore new frontiers 9 Figure 7. Evolving approaches to m
21、anaging big data (by company size) LargeMidsizeSmall NowExploringNowExploringNowExploring Cloud-based (Amazon Web Services, Azure) 19%48%7%50%0%40% Hadoop 19%37%7%14%0%20% NowTwo years Reduce time spent by humans 8%49% Identify high-risk cases 10%45% Build risk models for better decision making 8%45
22、% Help humans identify appropriate risk attributes 6%43% Better understand risk drivers 20%41% Identify patterns of fraudulent claims 6%39% Augment human-performed underwriting 6%37% Figure 8. How AI and machine learning are expected to streamline processes In tandem, attitudes toward the modeling t
23、echniques that are useful for pricing, claims and marketing are also evolving. While generalized linear models and one-way analyses used by about three-quarters of companies are still seen as the primary methods that will carry them forward, around a quarter of companies surveyed are looking to augm
24、ent their modeling capability over the next two years with such methods as decision trees, random forest and neural networks. AI, machine learning and the role of InsurTech AI and machine learning are associated with some of the techniques now considered by many companies, often fueled by the growin
25、g band of InsurTech businesses and start-ups that want to secure a place in the insurance value chain. Recent trends elevate a greater collaborative focus on back- office operations support* among InsurTech businesses, and have moved away from market-disruptive, customer-facing applications that oft
26、en entail high market entry barriers. Typically, greater automation that enhances business models and substantially cuts costs across product portfolios is the underlying operational goal. This is reflected in the ways that companies say they currently use and expect to use AI and machine learning t
27、echnologies in the next two years (Figure 8). *Willis Towers Watson Q4 2017 InsurTech Briefing: Greater automation that enhances business models and substantially cuts costs across product portfolios is the underlying operational goal. Analytics asteroids Potential obstacles to progress Experience s
28、hows that top-notch analytics draw as much from culture and strategy as the tools and people that make them possible. Organizations will and ability to be data- driven are important drivers. Often, as our survey confirms, IT networks and connectivity are the biggest obstacles to overcome (Figure 9).
29、 Many also concede, however, that work is still needed to improve the levels of understanding of advanced analytics outputs of those that use them within the business, with 83% of respondents categorizing their current capabilities as either “moderate” or “limited.” The benefits of advanced analytic
30、s will likely be hard to attain if companies cant access and use data at the right time, in the right place and deploy data to the right people, including the end customer, in a comprehensible way. Figure 9. What are the three biggest challenges preventing your company from becoming more data-driven
31、? 0%10%20%30%40%50%60% None of these being data-driven is not important to us Other Technology concerns (e.g., cyber risk, systems failure) Privacy concerns Regulatory concerns Lack of tools to analyze data Lack of clarity on strategy Lack of expertise to analyze data Lack of sufcient staf to analyz
32、e data Data capture/availability Data volume/quality/reliability Confl icting priorities/Executive buy-in IT/Information services bottlenecks/Lack of coordination Data accessibility/not easily integrated Infrastructure/Data warehouse constraints 51 41 33 31 31 28 26 24 12 6 4 2 2 2 0 The benefits of
33、 advanced analytics will likely be hard to attain if companies cant access and use data at the right time, in the right place and deploy data to the right people, including the end customer, in a comprehensible way. 10 Advanced analytics and the future: Insurers boldly explore new frontiers 11 This
34、research finds that insurers are quite positive about the potential business benefits of big data and advanced analytics. Accordingly, insurers seem poised to use them to better quantify risk, streamline processes and improve customer experiences or, more likely, a combination of all three. Our expe
35、rience suggests that the new analytics universe will be within closer and more immediate reach if companies recognize and follow three guiding principles. Data are the primary source of value in analytics. New analytical methods, including AI and machine learning, are justifiably getting a lot of at
36、tention in quantitative circles right now, but we believe insurers should focus the most significant initial effort on their sources of data. Why? Because new (or better) experience data, predictors and customer response information will always trump new methods being thrown at the same data. More d
37、ata, in-depth analysis and new insights arent the end game. They have to translate into something the business can understand, implement and monitor, from which it can derive and offer value. Otherwise, the work done is simply a technical modeling exercise. Stay on top of the technology. Legacy comp
38、any systems and networks will make it increasingly difficult to conduct business effectively in the advanced analytics age. At the extreme, the way some companies have done business will become more challenging in the near future, so new technologies that enhance analytical capability and system con
39、nectivity, including those coming out of the InsurTech movement, will have a greater role to play. Next steps for insurers Bringing the new analytics universe within reach Further information For more information about survey results, or to discuss the findings and our observations, contact: J.J. Ih
40、rke +1 952 842 6692 Nathalie Bgin +1 416 960 7429 About Willis Towers Watson Willis Towers Watson (NASDAQ: WLTW) is a leading global advisory, broking and solutions company that helps clients around the world turn risk into a path for growth. With roots dating to 1828, Willis Towers Watson has over
41、40,000 employees serving more than 140 countries. We design and deliver solutions that manage risk, optimize benefits, cultivate talent, and expand the power of capital to protect and strengthen institutions and individuals. Our unique perspective allows us to see the critical intersections between talent, assets and ideas the dynamic formula that drives business performance. Together, we unlock potential. Learn more at Copyright 2018 Willis Towers Watson. All rights reserved. WTW-US-17-RES-8382f
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