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 https://www.smefinanceforum.org/post/alternative-data-transforming-sme-finance

1. Alternative Data
Transforming SME Finance
John Owens & Lisa Wilhelm
SME Finance Forum Webinar
June 12, 2017
Washington DC

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. 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. 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. 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. 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. 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. 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. 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. 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. $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. 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. 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. 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. How banks are collaborating/competing with fintechs

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. 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. 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. The Rise of the Digital SME Bank/Lender
Banking as a
Platform
Third Party
Fintechs
Online
Accounting
Data
Bank
Transactional
Data
Open APIs

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. Thanks
johnvowens@me.com
lisa@globalpayexperts.com