1、Fintechsector update Important disclosures appear at the end of this reportGP Bullhound Corporate Finance Ltd and GP Bullhound Asset Management Limited are authorised and regulated by the Financial Conduct Authority GP Bullhound Inc is a member of FINRAGP Bullhound Luxembourg S.R.L.is regulated by t

2、he CSSF in LuxembourgQualitative insights into broader Fintech trends and public and private valuations across the transaction spectrum,and interviews with todays leaders transforming the sector.Q4 20222Takeaways114 countries globally,representing over 95%of global GDP,are exploring Central Bank Dig

3、ital CurrenciesIncreased adoption of blockchain-enabled solutions and mass transition to a cashless ecosystem is catalysing the proliferation of digital currenciesWith multiple pilot programmes being held by both the Bank of England and the European Central Bank,implementation and dynamics are under

4、 questionNote:Please see following slides for sourcesTHE VIEWQ4 Fintech perspectives from GP BullhoundPay by Bank leverages open banking to facilitate payments between trusted parties without the need for a card.The payment method has several benefits including improved security,automated customer o

5、nboarding for merchants and reduced processing costsRecently,banks have established partnerships,with and without fintechs,to roll-out a Pay by Bank solution to ensure their payments offering remains competitiveBANKS INNOVATE AUTOMATED CLEARING HOUSE PAYMENTS TO REMAIN COMPETITIVETakeawaysTHE FUTURE

6、 OF CENTRAL BANKS IS IT DIGITAL?Artificial intelligence and machine learning have become increasingly popular in credit scoring processes within the fintech industry in recent yearsBy using alternative data sources,improving efficiency and speed,and personalising credit decisions,fintech companies c

7、an make more accurate and efficient credit decisions and improve the customer experienceAI AND ML ADOPTION IN CREDIT SCORING PROCESSES IS ON THE RISE3GP Bullhounds recent Fintech activityA LEADING TECHNOLOGY ADVISORY AND INVESTMENT FIRM,PROVIDING TRANSACTION ADVICE AND CAPITALInvestment BankingInves

8、tmentManagementTakeawaysINVESTMENT BYFund IINVESTMENT BYFund IIIINVESTMENT BYFund IIIINVESTMENT BYFund IVINVESTMENT BYFund IVACQUIRED BYINVESTMENT BYINVESTMENT BYACQUIRED BYINVESTMENT BYACQUIRED BYINVESTMENT BYACQUIRED BYINVESTMENT BYACQUIRED BYACQUIRED BYINVESTMENT BYACQUIRED BYINVESTMENT BY4Pressu

9、re from nimble fintechs is encouraging banks to innovate ACH payments via Pay by BankGP BULLHOUNDS SECTOR TAKEAWAYS TakeawaysSources:NACHA,Mastercard,Bank of AmericaOpen banking is modernising the ACH network to enable seamless payments via Pay by BankBanks are steadily establishing partnerships to

10、stay competitive against fintechsDuring the third quarter of 2022,the Automated Clearing House(ACH)payment network processed 7.6 billion transactions representing$19.2tn in value.P2P ACH payments grew 10%YoY to 2.4 billion in Q3 as ACH payments become increasingly secureOpen banking has catalysed th

11、e adoption of ACH payments as it enables individuals to share financial data between trusted parties and facilitate payments directly from the users bank account with improved speeds and without the need for a cardACH payments are typically inexpensive as they remove card processing fees and take th

12、e pain out of recurring payments for consumers.Popular use cases include utilities payments,rent,pension payments from the government and insurance For merchants,the Pay by Bank value proposition includes automated consumer onboarding,via open banking,and streamlined payment reconciliation.Additiona

13、lly,Pay by Bank leverages the banks payment authentication network to improve security andlowers customer data storage costs since cards are not required and the payment is made account-to-accountIn November 2022,Mastercard announced its partnership with JP Morgan to roll-out an account-based(Pay by

14、 Bank)payment solution.The solution is currently in its pilot phase with a small number of US-based billers and merchants but is expected to expand significantly in 2023Roll-out of the solution highlights JP Morgans aim of remaining at the forefront of payments innovation and aligns with the banks w

15、ider strategy of accepting payments anytime,anywhereJP Morgan is not alone in seeing the value of open-banking enabled ACH payments.Bank of America delivered their Pay by Bank solution in conjunction with Banked,a UK-based fintech.The partnership demonstrates how banks are now working with Fintechst

16、o remain competitiveBank of of Americas Pay by Bank solution is currently only available in the United Kingdom,but is expected to roll out into new regions soonSelect newsDEAL DATE:JAN-21TTV:$3.4NEV/REV:N/AFEB-22:LAUNCH OF PAY BY BANK SOLUTIONDEAL DATE:NOV-22 RAISED:$15MDEAL DATE:MAY-22 RAISED:$40MN

17、OV-22:PARTNERSHIP TO LAUNCH PAY BY BANK5CBDCs:Are Central Bank Digital Currencies arriving sooner than expected?GP BULLHOUNDS SECTOR TAKEAWAYS TakeawaysSources:Bank of England,EDPS,Bank for International Settlements(BIS),Atlantic CouncilOver half of the worlds central banks are considering digital c

18、urrencies(CBDCs)Why would a CBDC be warranted?CBDCs are digital tokens or electronic records that represent a nations currency in virtual form allowing for facilitation of digital transactions and simplification of monetary transfers,backed by central governments114 countries,representing over 95%of

19、 global GDP,are now exploring CBDCs with 11 countries having already launched their own state-owned digital currencySpeculation around the introduction of CBDCs has been accelerated post Covid-19 due to the global shift towards digital,contactless and ecommerce payments reducing the need and use for

20、 cashImplementation of CBDCs can be implemented in a centralised or decentralised fashion.A centralised approach much like the current fiat mechanics would have all transactions recorded in ledgers that are controlled by a central bank.Decentralising a CBDC would require the bank to set regulation a

21、round the settlement of CBDC transactions that are then recorded by financial institutionsA CBDC would look no different to how we use money or cryptocurrencies today,delivered through the private sector allowing payments through card or mobile.With the surge in private sector companies accepting cr

22、yptocurrencies already,public sector digitalisation is following closely behindClear benefits arise around the topic of data protection and security with adoption of CBDCs.Increased control over personaldata and anonymity,but with a clearer and more robust structure for initiating the audit process

23、for AML,terrorism financing,fraud and taxThe hurdle that faces a widespread adoption of digital currencies by central banks is the current state of private sector finance and how the implementation of a centralised,digitalised currency would undermine traditional business models.Additionally,increas

24、ed risk of bank runs and lower deposits in commercial banks,which make private sector products more expensive,and other consumer-incurred costs also give rise to concernsSelect newsDEAL DATE:JAN-21TTV:$3.4NEV/REV:N/ASEP-22:ANNOUNCES DIGITAL EURO LEGISLATION PLANNINGJUN-22:PROJECT ROSALIND LAUNCHED E

25、XPLORING PRIVATE SECTOR LEDGERSJAN-22:RELEASED CBDC SOLUTIONS WHITEPAPER SUPPORTING CENTRAL BANKSDEAL DATE:JAN-21TTV:$3.4NEV/REV:N/ASEP-22:LAUNCHED E-HKD TRIALS6AI and ML adoption in credit scoring processes is on the riseGP BULLHOUNDS SECTOR TAKEAWAYS TakeawaysSource:Datrics.aiThe availability of d

26、ata and sophistication of AI&ML have opened many opportunities for credit scoring processesArtificial intelligence and machine learning have become increasingly popular in credit scoring processes within the fintech industry in recent yearsCredit scoring is the process of evaluating the creditworthi

27、ness of an individual or business,which involves analysing various financial and non-financial factors to predict the likelihood of default on a loanTraditionally,credit scoring has relied on humans to manually review and assess credit applications.However,the rise of fintech and advances in AI and

28、ML have the potential to revolutionise the underwriting process of potential borrowers and credit decision-making.Here are some of the key trends in the adoption of AI and ML in credit scoring processes in fintech:Greater accuracy:AI and ML algorithms can analyse vast amounts of data and make predic

29、tions with a high degree of accuracy.This can help lenders to more accurately assess the creditworthiness of potential borrowers and make better lending decisionsIncreased efficiency:The use of AI and ML in credit scoring processes can help to streamline the process,reducing the time and resources r

30、equired to assess applications.This can make the lending process faster and more efficient for both lenders and borrowersEnhanced risk assessment:AI and ML algorithms can analyse data from a variety of sources,including social media and public records,to provide a more comprehensive view of a borrow

31、ers financial situation and creditworthiness.This can help lendersto better assess the risk of lending to a particular borrowerGreater access to credit:By enabling lenders to more accurately assess the creditworthiness of potential borrowers,AI and ML can help to make credit more accessible to under

32、served or traditionally underrepresented groups,such as those with limited credit historiesRegulatory considerations:The use of AI and ML in credit scoring processes has raised concerns about potential bias and discrimination.As a result,regulatory agencies are increasingly focusing on the use of th

33、ese technologies in lending,with an emphasis on ensuring that they are used ethically and in a way that promotes fairness and equal access to creditThe adoption of AI and ML in credit scoring processes in fintech is likely to continue to grow in the coming years,as lenders look to leverage these tec

34、hnologies to improve their operations and better serve their customersSelect newsDEAL DATE:NOV-22 RAISED:UNDISCLOSEDDEAL DATE:AUG-22 RAISED:$23MDEAL DATE:JUL-22 RAISED:$122MDEAL DATE:DEC-22 RAISED:$54M7Dealmaking activity continues to remain low,driven by the corrections in valuation and weak econom

35、ic sentimentM&A AND FUNDRAISING ACTIVITY BY QUARTERSources:Pitchbook(as of 31 December 2022);Note:(1)Spike in value in Q3 2019 due to four extraordinarily large transactions with an aggregate value of c.$185bn:Ant Group/Alibaba($66bn),Worldpay/FIS($48bn),First Data/Fiserv($46bn),and Total Systems Se

36、rvices/Global Payments($24bn);(2)Spike in value in Q4 2020 due to an extraordinarily large transaction of$22bn(TD Ameritrade/Charles Schwab&Co);(3)Unusual deal value in Oceania due to Squares acquisition of Afterpay($28.5bn);(4)Spike in Asia fundraises value in Q2 2018 was caused by an extraordinari

37、ly large investment in Ant Financial($14bn)CEO commentary05001,0001,5002,0002,5003,00001020304050Q1 2018Q2 2018Q3 2018Q4 2018Q1 2019Q2 2019Q3 2019Q4 2019Q1 2020Q2 2020Q3 2020Q4 2020Q1 2021Q2 2021Q3 2021Q4 2021Q1 2022Q2 2022Q3 2022Q4 2022Total capital invested(LHS)Volume(RHS)00500600050100

38、150200250Q1 2018Q2 2018Q3 2018Q4 2018Q1 2019Q2 2019Q3 2019Q4 2019Q1 2020Q2 2020Q3 2020Q4 2020Q1 2021Q2 2021Q3 2021Q4 2021Q1 2022Q2 2022Q3 2022Q4 2022Value(LHS)Volume(RHS)0%20%40%60%80%100%Q1 2018Q2 2018Q3 2018Q4 2018Q1 2019Q2 2019Q3 2019Q4 2019Q1 2020Q2 2020Q3 2020Q4 2020Q1 2021Q2 2021Q3 2021Q4 2021

39、Q1 2022Q2 2022Q3 2022Q4 2022AmericasEuropeAsiaOtherM&A deal value by regionFundraising deal value by region$bn,number of deals$bn,number of deals0%20%40%60%80%100%Q1 2018Q2 2018Q3 2018Q4 2018Q1 2019Q2 2019Q3 2019Q4 2019Q1 2020Q2 2020Q3 2020Q4 2020Q1 2021Q2 2021Q3 2021Q4 2021Q1 2022Q2 2022Q3 2022Q4 2

40、022AmericasEuropeAsiaOtherTransaction M&A deal value and volumeFundraising deal value and volume(1)(2)(4)Transaction trends(3)(3)(4)8As European equity capital markets remain shut,several companies have opted for SPACs as a route to go publicNOTABLE FINTECH M&ATransaction trends30-Dec-22Embedded Fin

41、ance-as-a-Service platform600 n.a.19-Dec-22Operator of a crypto currency lender1,022 n.a.15-Dec-22Developer of blockchain-enabled digital wallet software320 n.a.12-Dec-22Provider of business spend management software8,000 9.8x12-Dec-22Mobile-based payments provider and gateway126 n.a.21-Nov-22Provid

42、er of front,middle and back-office software101 n.a.18-Nov-22Provider of digital payroll solutions33 n.a.17-Nov-22Provider of mobile payments for telecom and merchants513 1.1x16-Nov-22Provider of technology-enabled trading,clearing and settlement622 n.a.16-Nov-22Provider of online credit solutions fo

43、r sub-prime consumers67 n.a.11-Nov-22Provider of tax automation software500 8.3x10-Nov-22End-to-end digital commerce platform and payment processor375 n.a.10-Nov-22Platform that digitises assets and transactions622 n.a.02-Nov-22Provider of payments and trading solutions for digital assets200 n.a.01-

44、Nov-22Provider of tax management solutions720 2.9x01-Nov-22Provider of cloud-based benefits management software570 2.3x19-Oct-22Provider of payments technology solutions1,100 n.a.15-Oct-22Developer of blockchain infrastructure163 n.a.11-Oct-22Provider of currency risk management solutions118 n.a.10-

45、Oct-22Operator of a digital challenger bank200 n.a.Deal dateTargetBuyerTarget descriptionEV($m)Implied EV/LTM RevSources:Pitchbook,Capital IQ,Mergermarket*Denotes SPAC transactions908-Nov-22Digital challenger bank415 104-Nov-22Crypto liquidity platform75 02-Nov-22Alternative investment platform90 02

46、-Nov-22ML-powered credit underwriting platform50 26-Oct-22Spend management software and payments40 125-Oct-22Online payment platform110 20-Oct-22Online consumer lending platform123 117-Oct-22AI-driven insurance platform50 11-Oct-22BNPL platform140 11-Oct-22Cross-border payments platform100 04-Oct-22

47、Embedded banking platform46 103-Oct-22Automated credit card debt payment platform80 Online lenders and credit providers successfully managed to raise capital SELECT FINTECH FUNDRAISINGSTransaction trendsSources:Pitchbook,Capital IQ,MergermarketNote:(1)Debt and equity raised29-Dec-22AI-driven lending

48、 platform54 19-Dec-22Financial wellness platform131119-Dec-22Open finance,open data and payments platform67 15-Dec-22Digital currency exchange platform300 15-Dec-22Developer of a privacy layer for Web3100 14-Dec-22BNPL and consumer financing platform200 07-Dec-22Online consumer lending platform250 1

49、02-Dec-22Online micro-lending platform100 02-Dec-22Instant credit at checkout61 29-Nov-22Digital challenger bank45 22-Nov-22Checking account platform125 15-Nov-22Open-banking enabled Pay by Bank payments15 DateTargetLeadinvestor(s)Target descriptionCapital raised($m)DateTargetLeadinvestor(s)Target d

50、escriptionCapital raised($m)10(18.3)9.9 3.1 4.8(1.5)2.1 0.1(0.6)(1.5)(0.2)0.4 1.0(0.6)(0.2)(0.3)(0.2)(0.2)0.1 81.2 44.2 42.7 37.6 19.1 10.5 7.2 6.9 4.6 4.3 4.0 3.4 3.3 1.9 1.5 0.9 0.8 0.3Market Cap at 31 December 2022Change in Market Cap vs prior quarterMacroeconomic factors have now been priced in,

51、resulting in fintech equities being relatively stable in Q4 2022GP BULLHOUND FINTECH INDEX BY MARKET CAPITALISATIONSource:Capital IQ(as of 31 December 2022)Note:Presented on a logarithmic scalePublic company analysesGP Bullhound Fintech index by market capitalisation($bn)110 x5x10 x15x20 x25x30 xDec

52、-20Mar-21Jun-21Sep-21Dec-21Mar-22Jun-22Sep-22Dec-22GPB Fintech Index-TEV/LTM RevenuesGPB Fintech Index-TEV/NTM RevenuesMultiples have stabilised at c.5x,as rising rates and weak macroeconomic sentiment resulted in valuation re-ratingsGP BULLHOUND FINTECH INDEX VALUATIONSSource:Capital IQ(as of 31 De

53、cember 2022);Note:EV/Rev multiples except for online lenders,which are computed as Market Cap/Rev multiples.Fintech Index constituents are Adyen,Affirm,Blackline,Block,Dlocal,Envestnet,Funding Circle,Lending Club,Market Axess,Marqeta,Nubank,Payoneer,PayPal,Paysafe,Q3 e-banking,Shopify,Wise,XeroMean:

54、13.9xMean:12.9xAs of 31 December 2022,the Fintech index is trading at 5.0 x trailing 12-month revenues,which is 63.6%below the 2-year averageAs of 31 December 2022,the Fintech index is trading at 5.4x next 12-month revenues,which is 58.3%below the 2-year averagePublic company analysesContinued volat

55、ility tech sell-off due to market fears of rising interest rates that the Fed could lose a grip onRising treasury yield expectations due to inflation have put pressure on tech valuationsConflict in Ukraine exacerbates weak macroeconomic climateTechnology stocks continued to fall given vulnerability

56、to higher interest rates and slow economic growth12-20406080100120140 Dec-20 Mar-21 Jun-21 Sep-21 Dec-21 Mar-22 Jun-22 Sep-22 Dec-2210.7%Financial Data&Analytics4.0%HR&PayrollFintech equities performance remained more stable in Q4 2022,with Financial Data&Analytics being the best performerSHARE PRIC

57、E PERFORMANCE LAST TWO YEARSSource:Capital IQ(as of 31 December 2022)Performance1 Month3 Months6 Months1 Year2 YearsBanking Technology(4.8%)(6.4%)(14.1%)(39.4%)(54.8%)Nasdaq(8.7%)(1.0%)(5.1%)(33.1%)(18.8%)Financial Data&Analytics(5.0%)10.7%5.3%(24.5%)(14.2%)HR&Payroll(4.8%)4.0%9.0%(21.0%)(7.5%)Payme

58、nts(4.8%)(1.6%)9.2%(32.4%)(49.0%)Public company analysesL3M Performance(1.0%)Nasdaq(1.6%)Payments(6.4%)Banking Technology1335.4xOnline Lenders7.5x25.5x30.9%Financial Data&Analytics9.0%7.0 x25.6x30.1%HR&Payroll10.0%6.0 x26.4x16.3%Banking Technology5.0%6.2x17.6x26.5%Payments58.6%3.9x10.7%201.9%GP Bull

59、hound Fintech indices valuation benchmarksGP BULLHOUND FINTECH INDICES INDICATIVE TRADING VALUATION BENCHMARKSPublic company analysesSource:Capital IQ(as of 31 December 2022)Note:Only select logos shown;(1)MeanEV/2022E revenue(1)EV/2022E EBITDA(1)2022E EBITDA margin(1)Select companiesVerticals 2022E

60、 revenue growth(1)14LEADING COMPANIES AND CEOS TRANSFORMING THE SECTORFounded in 2020,Fido is a customer scoring and analytics platform that detects hundreds of data points from digital footprints such as phone numbers,email addresses,IP addresses,devices,and browsers.Through proprietary machine lea

61、rning algorithms,Fido provides companies with raw data and customer scorecards for different applications:credit risk assessment,fraud prevention,KYC,AML,and lead qualification.CEO commentaryInvestorsCEO commentaryMarko Maras,Founder&CEOOrganisations across industries are facing increasing pressures

62、 to accurately assess risk when acquiring new customers.Traditional financial and transactional datasets are not always sufficient,so Fido helps businesses to leverage alternative digital data,assessing risk effectively when onboarding new customers without interfering with the user experience.Fido

63、is a cloud-based platform that allows organisations to capture hundreds of digital footprints with a single API.We are continuously expanding our product portfolio adding new signals and developing new and more sophisticated algorithms to solve even greater challenges for our clients.FOUNDER&CEO,FID

64、OMARKO MARAS15LEADING COMPANIES AND CEOS TRANSFORMING THE SECTORLaunched in 2012,GoHenry is a prepaid debit card and financial education app designed exclusively for six-to 18-year-olds.Parent and child apps provide tools to help kids and teens learn about money in the real world,all with parental o

65、versight.In-app gamified money lessons,Money Missions,offer the theory behind the practice providing a rewarding and fun way for kids to build their financial literacy skills.GoHenry now has over two million members in the UK and USA,and in France and Spain via Pixpay.CEO commentaryInvestorsCEO comm

66、entaryLouise Hill,Co-Founder&Chief Operating Officer“Im a firm believer that learning by doing is the best way to teach life skills.You cant just teach the theory of swimming you need to get into the water and do it for yourself.Its the same with money management.But financial education isnt as exci

67、ting to a child as swimming,so you need to find a way to make them want to get in the pool to continue my analogy and keep training.This is where GoHenry comes in.For kids and teens to understand the value of money and how to manage it,they need real-life experience in the digital economy.We give ki

68、ds a way to experience financial independence,think critically about money,and the means to spend digitally in a safe way.Ultimately,we make financial education fun and true to real life to help with the transition into adulthood because kids who cant manage money become adults who cant manage money

69、.”CO-FOUNDER&COO,GOHENRYLOUISE HILL16LEADING COMPANIES AND CEOS TRANSFORMING THE SECTORPillar helps people build their global credit score,break down credit borders and unlock access to financial services globally.The company has developed a financial platform that provides immigrants with access to

70、 credit products when moving to a new country.Pillar is built on a proprietary data and analytics engine that incorporates a combination of international credit data and Open Banking,powering the global scalability of the platform.CEO commentaryCEO commentaryAsh Bhatt and Adam Lewis,Co-Founders“When

71、 I arrived in the UK,I couldnt access any of the everyday products I had in India,and this has been a problem Ive been passionate about solving.The world of credit still hasnt changed,so we have set upon building a globally scalable platform that breaks down data silos and credit borders,solving the

72、 problems faced by financially secure people when moving to a new country.Through Pillar,anyone moving to the UK from abroad can have a credit card in their pocket before even boarding their flight.However,we arent stopping with this use case,we want to make this service global.The UK and Europe are

73、 just the beginning,and we are building infrastructure across the US,Africa,and Asia.Its time that credit products and data systems,are redeveloped from scratch,as there has been no real innovation in this space in the past half a century.”CO-FOUNDERS,PILLARASH BHATT,ADAM LEWISInvestors17Public comp

74、arables PaymentsPUBLIC COMPARABLES BY CATEGORY Source:Capital IQ(as of 31 December 2022);Note:EV/Revenue multiples in excess of 75.0 x,EV/EBITDA multiples in excess of 100.0 x and P/E multiples in excess of 150.0 x are considered not-material(NM)and are not included in average calculationPublic comp

75、arablesPaymentsHigh Growth Omnichannel PaymentsFiserv64,18283,0063%7%32%8%33.9%43.2%43.4%5.1x5.0 x4.6x15.1x11.5x10.7x18.2x15.6x13.8x(3%)PayPal81,19381,7219%10%28%14%20.6%24.2%25.1%3.2x3.0 x2.7x15.7x12.3x10.7x15.5x17.6x14.9x(62%)FIS40,26157,4325%4%60%5%28.1%43.0%43.5%4.1x4.0 x3.8x14.7x9.2x8.7x10.4x10

76、.2x10.0 x(38%)Shopify44,15440,51219%21%n.a.n.a.17.3%(0.9%)0.8%8.8x7.4x6.1x50.7xn.m.n.m.54.7x n.m n.m(75%)Block37,58337,748(1%)15%176%40%1.9%5.3%6.4%2.1x2.2x1.9xn.m.41.1x29.4x37.7x56.3x36.2x(61%)Adyen42,66036,88036%33%31%35%62.5%60.5%61.5%35.2x25.9x19.5x56.2x42.8x31.7x81.0 x64.5x49.0 x(44%)Nubank19,0

77、7028,797574%46%n.a.n.a.n.a.(2.5%)11.6%44.2x6.6x4.5xn.a.n.m.38.9x n.m 119.1x38.8x(57%)Toast9,3898,43059%33%n.a.n.a.(12.5%)(4.4%)(0.6%)4.9x3.1x2.3xn.m.n.m.n.m.n.m n.m n.m(48%)Wise6,9486,59438%46%n.a.36%n.a.24.5%22.9%10.6x7.7x5.3xn.a.31.4x23.0 x n.a 81.3x46.0 x(26%)Affirm2,8065,358123%24%n.a.n.a.(83.5%

78、)(55.3%)(3.3%)8.0 x3.6x2.9xn.m.n.m.n.m.n.m n.m n.m(90%)Dlocal4,6084,08473%50%87%50%34.2%37.1%37.1%16.7x9.7x6.5x48.9x26.1x17.4x61.3x36.8x23.9x(56%)Paysafe8423,262(0%)5%24%9%22.2%27.5%28.7%2.2x2.2x2.1x9.9x8.0 x7.3x12.0 x5.0 x5.5x(70%)StoneCo2,9513,131253%21%209%36%53.2%46.7%52.3%6.2x1.8x1.5x11.7x3.8x2

79、.8x65.2x29.6x16.1x(44%)PagSeguro2,8512,814130%17%1%30%42.4%18.6%20.6%2.2x1.0 x0.8x5.3x5.2x4.0 x10.7x9.4x8.3x(67%)Marqeta3,3311,69844%27%n.a.n.a.(30.6%)(6.3%)(3.5%)3.3x2.3x1.8xn.m.n.m.n.m.n.m n.m n.m(64%)Payoneer1,9161,43230%20%n.a.39%(4.1%)7.2%8.3%3.0 x2.3x1.9xn.m.32.5x23.4x n.m n.m 70.2x(26%)Fawry7

80、0059137%39%51%44%27.8%30.6%31.6%9.7x7.1x5.1x34.9x23.1x16.0 x30.4x45.2x34.0 x(59%)Mean84.2%24.6%70.0%28.8%14.2%17.6%22.7%10.0 x5.6x4.3x26.3x20.6x17.2x36.1x40.9x28.2x(52.4%)Median37.3%21.4%41.4%35.6%22.2%24.2%22.9%5.1x3.6x2.9x15.4x17.7x16.0 x30.4x33.2x23.9x(56.6%)General Payments&ServicesGlobal Paymen

81、ts26,85638,963(5%)6%13%7%40.4%48.5%49.0%4.6x4.8x4.6x11.3x10.0 x9.3x12.2x10.6x9.5x(27%)Nexi10,32317,9907%6%170%11%19.5%49.0%51.3%5.6x5.2x4.9x28.7x10.6x9.6x15.7x13.8x12.1x(47%)Worldline11,00016,40718%9%67%15%18.1%25.7%27.1%4.2x3.6x3.3x23.4x14.0 x12.1x16.7x17.5x14.7x(25%)Cielo2,6713,844(2%)6%104%9%17.5

82、%36.5%37.6%1.8x1.8x1.7x10.1x5.0 x4.6x16.9x10.0 x8.3x130%ACI Worldwide2,5853,5232%3%32%7%20.5%26.5%27.5%2.6x2.5x2.5x12.5x9.5x8.9x12.4x13.2x12.0 x(34%)EVO Payments1,6343,08212%13%32%15%31.2%36.8%37.5%6.2x5.6x4.9x19.9x15.1x13.1x38.9x29.9x26.3x32%Network International1,9732,16926%18%84%23%27.6%40.4%42.3

83、%6.2x4.9x4.2x22.3x12.1x9.9x34.2x24.4x18.0 x2%Mean8.1%8.7%71.6%12.6%25.0%37.6%38.9%4.4x4.1x3.7x18.3x10.9x9.6x21.0 x17.1x14.4x4.4%Median7.4%6.1%67.2%11.1%20.5%36.8%37.6%4.6x4.8x4.2x19.9x10.6x9.6x16.7x13.8x12.1x(25.5%)Payment NetworksVisa428,271435,36518%10%13%15%70.2%67.5%70.7%20.5x18.5x20.3x24.3x21.6

84、x18.8x33.6x27.0 x24.1x(4%)Mastercard334,328340,51817%13%21%14%58.2%60.2%61.0%22.8x20.2x22.3x31.0 x25.5x22.3x42.1x32.9x28.5x(3%)Mean17.5%11.2%17.2%14.7%64.2%63.8%65.9%21.6x19.3x21.3x27.7x23.5x20.5x37.8x29.9x26.3x(3.7%)Median17.5%11.2%17.2%14.7%64.2%63.8%65.9%21.6x19.3x21.3x27.7x23.5x20.5x37.8x29.9x26

85、.3x(3.7%)Mean(ALL)58.6%19.3%65.0%22.0%21.5%26.5%30.4%9.4x6.2x5.5x23.5x17.6x15.1x31.0 x31.9x23.6x(33.3%)Median(ALL)18.6%16.3%31.8%15.3%24.9%29.1%30.1%5.4x4.4x4.0 x19.9x12.3x11.4x24.3x24.4x17.0 x(44.1%)Market Cap(USDm)EV(USDm)Revenue GrowthEBITDA GrowthEBITDA MarginEV/RevenueEV/EBITDAP/EShare Price Pe

86、rformanceCompany31/Dec/2231/Dec/2221/2222/2321/2222/23CY2021CY2022CY2023CY2021CY2022CY2023CY2021CY2022CY2023CY2021CY2022CY2023LTM18Public comparables Financial Data&AnalyticsPUBLIC COMPARABLES BY CATEGORY Public comparablesSource:Capital IQ(as of 31 December 2022);Note:EV/Revenue multiples in excess

87、 of 75.0 x,EV/EBITDA multiples in excess of 100.0 x and P/E multiples in excess of 150.0 x are considered not-material(NM)and are not included in average calculationMarket Cap(USDm)EV(USDm)Revenue GrowthEBITDA GrowthEBITDA MarginEV/RevenueEV/EBITDAP/EShare Price PerformanceCompany31/Dec/2231/Dec/222

88、1/2222/2321/2222/23CY2021CY2022CY2023CY2021CY2022CY2023CY2021CY2022CY2023CY2021CY2022CY2023LTMFinancial data&AnalyticsS&P Global109,123122,46442%6%15%10%56.8%45.8%47.7%14.8x10.4x9.8x26.0 x22.7x20.6x24.5x30.1x26.7x(29%)Thomson Reuters54,88258,2214%4%45%16%25.1%34.9%38.8%9.2x8.8x8.4x36.5x25.2x21.7x57.

89、9x46.2x36.2x2%Moodys51,03357,669(13%)7%(27%)12%50.1%41.8%43.9%9.3x10.6x9.9x18.5x25.4x22.6x22.5x33.3x29.9x(29%)MSCI37,19440,99910%9%13%10%57.4%59.1%59.5%20.1x18.3x16.8x35.0 x31.0 x28.2x47.0 x41.0 x36.9x(24%)Experian31,22535,38510%7%8%7%35.1%34.7%34.9%6.0 x5.4x5.1x17.0 x15.7x14.6x29.7x26.0 x23.6x(23%)

90、Verisk Analytics27,59030,991(4%)(11%)5%(5%)46.1%50.2%53.3%10.3x10.8x12.0 x22.4x21.4x22.5x33.5x32.1x31.7x(23%)Equifax23,79829,4554%3%6%6%33.1%33.8%34.7%6.0 x5.8x5.6x18.1x17.1x16.1x25.5x25.8x25.2x(34%)FactSet15,28516,90619%10%27%11%33.4%35.9%36.2%10.4x8.8x7.9x31.1x24.4x22.0 x35.5x29.1x26.7x(17%)FICO14

91、,95016,7296%8%44%16%35.0%47.8%51.0%12.6x11.9x11.0 x36.0 x24.9x21.6x43.6x33.6x29.1x38%TransUnion10,93616,47225%3%30%6%34.9%36.1%37.0%5.6x4.4x4.3x15.9x12.3x11.6x14.9x15.5x15.1x(52%)Black Knight9,53912,2766%6%46%8%35.0%48.1%49.1%8.3x7.8x7.4x23.8x16.3x15.1x26.3x25.2x23.8x(26%)Morningstar9,19310,14411%13

92、%10%14%22.1%21.8%22.0%6.0 x5.4x4.8x27.1x24.6x21.6x n.a 46.9x36.9x(37%)BlackLine4,0214,40023%17%n.a.17%(5.1%)10.9%10.9%10.3x8.4x7.2xn.m.77.5x66.0 x109.4x148.0 x124.2x(35%)Envestnet3,4144,1465%5%49%16%12.4%17.6%19.4%3.5x3.3x3.2x28.2x18.9x16.3x25.6x33.3x29.1x(22%)LiveRamp1,5581,11616%8%n.a.84%(12.4%)8.

93、7%14.8%2.2x1.9x1.8xn.m.21.9x11.9x44.7x44.4x24.5x(51%)Riskified78233913%18%n.a.n.a.(23.1%)(17.5%)(10.3%)1.5x1.3x1.1xn.m.n.m.n.m.n.m n.m n.m(41%)Mean9.0%7.2%21.4%15.6%25.3%30.9%33.0%8.1x7.5x7.1x25.8x25.5x22.3x39.7x41.4x35.2x(24.9%)Median9.6%6.9%20.1%11.6%33.4%34.9%36.2%8.3x7.8x7.2x25.4x23.1x21.6x33.5x

94、33.3x29.1x(25.5%)19Public comparables HR&PayrollPUBLIC COMPARABLES BY CATEGORY Public comparablesSource:Capital IQ(as of 31 December 2022);Note:EV/Revenue multiples in excess of 75.0 x,EV/EBITDA multiples in excess of 100.0 x and P/E multiples in excess of 150.0 x are considered not-material(NM)and

95、are not included in average calculationMarket Cap(USDm)EV(USDm)Revenue GrowthEBITDA GrowthEBITDA MarginEV/RevenueEV/EBITDAP/EShare Price PerformanceCompany31/Dec/2231/Dec/2221/2222/2321/2222/23CY2021CY2022CY2023CY2021CY2022CY2023CY2021CY2022CY2023CY2021CY2022CY2023LTMHR&PayrollIntuit109,342114,21919

96、%9%53%20%27.4%35.2%38.7%10.0 x8.4x7.7x36.5x23.9x19.9x34.2x32.8x26.7x(39%)ADP99,086101,44813%6%11%12%26.8%26.3%27.6%6.6x5.9x5.5x24.8x22.4x20.0 x37.5x31.8x28.1x(3%)Paychex41,65641,26812%7%12%9%43.7%43.7%44.5%9.7x8.6x8.0 x22.1x19.7x18.0 x34.3x29.2x26.4x(15%)Workday43,00640,77621%17%6%23%28.7%25.2%26.6%

97、7.9x6.6x5.6x27.6x26.1x21.1x42.8x47.3x35.8x(39%)SS&C13,11420,2325%4%7%7%37.1%37.9%39.3%4.0 x3.8x3.7x10.8x10.1x9.4x10.5x11.1x10.4x(36%)Paycom17,95717,66830%23%36%24%39.2%40.9%41.3%16.7x12.9x10.5x42.7x31.5x25.4x69.7x52.5x42.1x(25%)Paylocity10,81510,82536%26%216%36%12.1%28.0%30.4%14.9x11.0 x8.7xn.m.39.1

98、x28.7x82.7x52.1x44.0 x(18%)The Sage Group9,16110,0447%10%(1%)9%26.0%24.1%23.9%4.6x4.3x3.9x17.5x17.7x16.2x28.6x27.6x25.3x(13%)Coupa Software6,0297,38616%17%n.a.12%(14.8%)15.5%14.8%10.2x8.8x7.5xn.m.56.4x50.5x114.7x n.m 113.4x(50%)Xero7,1707,23929%31%61%32%17.3%21.7%21.9%12.1x9.4x7.2x69.7x43.3x32.8x n.

99、m n.m n.m(50%)TriNet4,0974,100(70%)(3%)21%(19%)11.3%45.4%38.0%0.9x3.0 x3.1x8.0 x6.7x8.2x13.4x10.8x13.0 x(29%)Blucora1,2221,6893%8%57%38%11.1%16.9%21.5%1.9x1.9x1.7x17.2x11.0 x8.0 x15.0 x14.1x9.4x47%Mean10.0%12.9%43.4%17.0%22.2%30.1%30.7%8.3x7.0 x6.1x27.7x25.6x21.5x44.0 x30.9x34.0 x(22.5%)Median14.6%9

100、.7%20.5%16.0%26.4%27.2%29.0%8.8x7.5x6.4x23.4x23.1x20.0 x34.3x30.5x26.7x(27.0%)20Banking TechnologyJack Henry12,80713,0718%8%30%8%26.8%32.3%32.3%7.0 x6.5x6.0 x26.1x20.2x18.6x39.1x36.2x34.1x5%MarketAxess10,49710,2373%11%2%11%55.1%54.6%54.2%14.7x14.3x12.8x26.6x26.1x23.6x40.0 x41.9x36.7x(32%)Temenos3,93

101、84,786(1%)6%40%8%27.8%39.3%40.0%4.9x5.0 x4.7x17.8x12.7x11.8x14.1x19.3x17.8x(60%)Q21,5451,88314%14%n.a.47%(8.6%)7.1%9.2%3.8x3.3x2.9xn.m.46.8x31.8x101.4x85.0 x46.2x(66%)Blend Labs3422141%(9%)n.a.n.a.42.6%(51.8%)(39.7%)0.9x0.9x1.0 x2.1xn.m.n.m.n.m n.m n.m(80%)Mean5.0%6.0%23.8%18.4%28.8%16.3%19.2%6.3x6.

102、0 x5.5x18.2x26.4x21.5x48.7x45.6x33.7x(46.7%)Median2.8%8.2%29.5%9.4%27.8%32.3%32.3%4.9x5.0 x4.7x22.0 x23.2x21.1x39.5x39.1x35.4x(59.7%)Public comparables Banking TechnologyPublic comparablesPUBLIC COMPARABLES BY CATEGORY Source:Capital IQ(as of 31 December 2022);Note:EV/Revenue multiples in excess of

103、75.0 x,EV/EBITDA multiples in excess of 100.0 x and P/E multiples in excess of 150.0 x are considered not-material(NM)and are not included in average calculationMarket Cap(USDm)EV(USDm)Revenue GrowthEBITDA GrowthEBITDA MarginEV/RevenueEV/EBITDAP/EShare Price PerformanceCompany31/Dec/2231/Dec/2221/22

104、22/2321/2222/23CY2021CY2022CY2023CY2021CY2022CY2023CY2021CY2022CY2023CY2021CY2022CY2023LTM21Public comparables Online LendersPublic comparablesPUBLIC COMPARABLES BY CATEGORY Source:Capital IQ(as of 31 December 2022);Note:EV/Revenue multiples in excess of 75.0 x,EV/EBITDA multiples in excess of 100.0

105、 x and P/E multiples in excess of 150.0 x are considered not-material(NM)and are not included in average calculationMarket Cap(USDm)EV(USDm)Revenue GrowthEBITDA GrowthEBITDA MarginEV/RevenueEV/EBITDAP/EShare Price PerformanceCompany31/Dec/2231/Dec/2221/2222/2321/2222/23CY2021CY2022CY2023CY2021CY2022

106、CY2023CY2021CY2022CY2023CY2021CY2022CY2023LTMOnline LendersSoFI4,2785,57855%33%n.a.134%(4.5%)7.5%13.3%5.7x3.7x2.7xn.m.48.5x20.7x n.m n.m n.m(71%)Upstart1,0829533%(10%)(84%)105%18.7%3.0%6.8%1.2x1.1x1.3x6.3x38.8x18.9x6.8x n.m 107.1x(91%)LendingClub9259481048%6%221%(12%)58.7%16.4%13.6%9.2x0.8x0.8x15.6x

107、4.9x5.5x35.2x5.4x7.1x(64%)LendInvest1431,405(86%)25%n.a.14%n.a.20.5%18.7%1.7x12.2x9.7xn.a.59.2x52.1x n.a 9.2x8.2x(61%)Funding Circle248264(10%)17%(88%)16%42.1%5.8%5.8%1.3x1.5x1.3x3.2x25.8x22.2x5.6x n.m 72.2x(51%)Mean201.9%14.1%16.7%51.4%28.7%10.7%11.6%3.8x3.9x3.2x8.4x35.4x23.9x15.8x7.3x48.7x(67.5%)M

108、edian3.0%16.7%(83.7%)16.1%30.4%7.5%13.3%1.7x1.5x1.3x6.3x38.8x20.7x6.8x7.3x40.2x(63.6%)22MethodologyThis report is based on the expert insights of GP Bullhounds worldwide team alongside detailed analysis of investment trends across the global technology landscape.GP Bullhounds Fintech sector comprise

109、s Payments,Financial Data&Analytics,HR&Payroll,Banking Technology and Online Lenders.TakeawaysGP Bullhounds Fintech teamBased in our London office,Claudio Alvarez heads up our Fintech practice,which has completed over 20 transactions involving both equity and debt.About usCLAUDIOALVAREZPARTNERBENPIT

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