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Alternative Data: Transforming SME Finance


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This presentation summarizes the IFC/World Bank/G20 GPFI report on the landscape of alternative data and players that are expanding access to SME finance. This presentation was prepared jointly with the effort of my co-author Lisa Wilhelm. The complete report can be downloaded at

Published in: Data & Analytics
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Alternative Data: Transforming SME Finance

  1. 1. Alternative Data Transforming SME Finance John Owens & Lisa Wilhelm SME Finance Forum Webinar June 12, 2017 Washington DC
  2. 2. SMEs: big market, big gaps, big opportunity High growth, margins  +/- 20%/year market revenue growth  ROEs 20-33%  ROAs 3X bank overall  Lending profits 1.35X overall bank lending  27% of Retail Banking avg. net revenue; up to 50% Global SME banking market sizing (emerging economies only)
  3. 3. The credit gap challenges Credit executives worry about adverse selection; top executives worry they won’t earn sufficient returns above their 10-15% cost of capital 3 1. IFC (October 2013). “Closing the Credit Gap for Formal and Informal Micro, Small, and Medium Enterprises.” SME DEMAND-SIDE ISSUES  High risk BANK SUPPLY-SIDE ISSUES  High cost  Informality  Difficult to reach, dispersed  Difficult requirements  High costs/interest  Cumbersome, slow applications  Low revenue/account  Low business, financial literacy INFORMATION OPACITY DEVELOPING MARKET SME CREDIT GAP 200-245 million MSMEs1$2.1-2.6 trillion1  Fear of decline
  4. 4. Big data + fintech evolution 4 Bank profit/revenue erosion coming Fintech banks  30 percent of U.S. Uber drivers never had a bank account  Uber drivers need a debit card to get paid  Uber solved this problem by allowing drivers to sign up for a bank account as part of the Uber driver application, in real time Uber is now the largest acquirer of small businessbank accounts in the U.S. today The next obvious move: design day-to-day banking (e.g. financing cars, leasing, insurance) into Uber’s app Fintechs: Lower lending costs Fintechs: big data- improved risk models
  5. 5. Global shifts: how much data and where? The digital universe is more than doubling every two years; importantly, digital data will switch from 60% in mature markets to 60% in emerging markets by 2020 Source: “The Digital Universe of Opportunities: Rich Data and the Increasing Value of the Internet of Things” (April 2014). IDC.
  6. 6. Which data sets are predictive for SME Finance? 28 data sets across 6 different alternative data categories that are being analyzed to support SME Finance Online B2B and Commerce Data Banking, Finance, and Industry Data Credit Reference Sharing Data Online Ranking & Social Media Data Mobile Data Individual/Psychometric Data
  7. 7. Fintech transforming the SME lending status quo A rapidly growing crop of technology-focused SME lenders are putting customer needs, big data, and advanced analytics at the center of their business models. P2P SME lenders Supply/trade financing Online balance sheet SME lenders Online invoice financing
  8. 8. Global SME ‘operating systems’ moving online Every time SMEs use cloud-based services, make digital payments, browse the internet, use their mobile phones, engage in social media, buy or sell electronically, ship packages, and manage their receivables, payables, and recordkeeping online, they create and deepen the digital footprints they leave behind. Payment acceptance + much more Making payments Cloud accounting + much more
  9. 9. Emerging digital SME lending ecosystem New analytic firms help lenders analyze big data; telco, bank, and technology firm convergence is fueling new mobile data-lending and financial services; and new marketplace aggregators help SMEs make sense of their growing lending options. Big data analytics Mobile data lending graduating to SMEs SME loan aggregator marketplaces
  10. 10. Big tech: picking up SME lending steam 10 2 million third party sellers globally. Makes short term working capital loans to sellers on invite only basis (US, Japan, India, China, Canada, France, Germany, UK, Italy, Spain; consumer installment loans at checkout in the UK 8 million Chinese sellers, aims to connect with more than 10 million sellers abroad. $62 billion in loans to 1.6 million SMEs since 2010. Partnered with Lending Club in US, Capify in Australia, iwoca and EZBOB in the UK, and ICICI Bank, Kotak Mahindra Bank, and Capital Float in India to finance domestic SME buyers (and in India, sellers) on its platform. Launched MYBank in 2015. 10 million merchants. As of November 2015, it had provided more than $1 billion in funding to more than 60,000 SMEs in the US, UK, and Australia. PayPal Credit, a reusable credit line available on purchases at thousands of stores (online and offline) that accept Paypal and on eBay surpassed $2 billion in volume in 4QTR 2015.
  11. 11. $1.440 $8.040 $39.630 $0.000 $0.137 $0.565 $0.026 $0.261 $1.460 $0 $20 $40 $60 2013 2014 2015 P2P SME Lending SME Balance Sheet Lending Invoice Trading Expon. (P2P SME Lending) $Billions Source: “Harnessing Potential: The Asia-Pacific Alternative Finance Benchmarking Report” (March 2016). Cambridge Center for Alternative The rapid rise of P2P SME lending in China 11
  12. 12. India case: e-commerce data fuels SME lending 12 Online SBI e-Smart SME e-Commerce Online vehicle loans for Uber drivers 25 other bank and more traditional non-bank lending partners
  13. 13. 09.09.15 Digital data & supply chain financing New digital data platforms allow for expanded supply/trade finance to smaller firms on a more cost-effective basis. This is happening more and more in countries and markets where SMEs are able to move their accounting and B2B relationships online and to digital platforms.
  14. 14. 09.09.15 Mobile data-based lending models KCB M-PESA LOAN Mobile data-based lending models: • instant small mobile loans • credit scores based on mobile transactions, mobile e-money usage, mobile e-money linked savings history • third-party mobile-based lenders are using data from apps running on smartphones
  15. 15. How banks are collaborating/competing with fintechs
  16. 16. Fintech and banks 2017: more friend than foe Advantage: banks • Captive, large customer base/ positive selection in applicant mix • Brand • Distribution coverage • Valuable, “free” internal data (but underutilized) • Low cost, stable source of funds • Regulatory certainty (mostly) 16 Advantage: fintechs • Customer service oriented • Simple and often friction-free applications • More credit data sources • Enhanced risk models • Underwriting costs • Pricing for risk • Less regulation in many markets (but the future is uncertain)
  17. 17. Scaling up: partnership business models 17 Banks SME Solutions Online Lending Government/ Associations Investing FCIF FUNDING CIRCLE SME INCOME FUND Banks SME Solutions Online Lending Payment/ Processors Lending as a service (LaaS) • Focus on technology/embedded analytics a game changer • Can scale very, very quickly • Enables partners to expand core solutions /value added services • U.S., Australia, Canada Acquisitions + referral partners • Acquired Lending Endurance Network to expand to U.S. • Acquired rival Zencap to expand into Europe (Germany, Netherlands, Spain) • Multiple referral partnerships
  18. 18. Licensing the platform to scale globally 18 Licensing technology to lenders globally • Turnkey platform, fully configurable • Rapid global deployment • Rapid processing and decision making can be fully automated • Works across all channels Banks SME Solutions Platform Lending Partners Network Acquirers Institutional Partners • Short online applications; automatically, painlessly link data sources • Uses power of SME’s own real-time, verified business data to get working capital
  19. 19. The Rise of the Digital SME Bank/Lender Banking as a Platform Third Party Fintechs Online Accounting Data Bank Transactional Data Open APIs
  20. 20. Alternative Data: Policy Issues and Challenges • Data privacy and consumer protection issues • Opt-in vs opt-out models • Credit reporting sharing and access • Cyber security • Transparency & disclosure • Balancing integrity, innovation and marketplace competition
  21. 21. Thanks