FIRM: An information solution to the challenge of rural financial inclusion

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Presentation at the Fin4Ag conference - Nairobi, July 2014.

Presentation at the Fin4Ag conference - Nairobi, July 2014.

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  • 1. © 2010 Experian MicroAnalytics. All rights reserved. Experian and the marks used herein are service marks or registered trademarks of Experian Limited. Other product and company names mentioned herein may be the trademarks of their respective owners. No part of this copyrighted work may be reproduced, modified, or distributed in any form or manner without the prior written permission of Experian MicroAnalytics. FIRM: An Information Solution to the Challenge of Rural Financial Inclusion Unlocking the power of non-financial data to enable financial inclusion
  • 2. © 2010 Experian MicroAnalytics. All rights reserved. 2 PERC’s Alternative Data Initiative (ADI) PERC galvanizes the inclusion of alternative data for use in credit granting as a means of financial access to mainstream lending markets for the financially excluded alternative = regular payments data from telecoms, energy utilities, mobile (pre)payments, fast moving consumer goods supply chain data, agricultural supply chain data, and other such non-financial services and transactions
  • 3. © 2010 Experian MicroAnalytics. All rights reserved. 33 0% 5% 10% 15% 20% 25% 30% < $20K $20-$29K $30-$49 $50-$99 $100K+ 2009/2010 2005/2006 Access to Credit Resulting from Non-Financial Data by Household Income
  • 4. © 2010 Experian MicroAnalytics. All rights reserved. 4 The Limits of Tradition Financial Data Models to Bring Data Online  Non-financial service firms don’t have clear incentive to report to a bureau in the traditional way. ► Prepayment reduces value of “disciplining” consumer ► Transaction counterparty gains nothing by reporting ► Providing data for free so bureaus can monetize seems unfair  Little uptake of data on most people (pre-paid or transactional) over past decade.  A lot of our focus has been on how to get these data furnishers to share data.
  • 5. © 2010 Experian MicroAnalytics. All rights reserved. 5 ► Non-financial payment information ● Pre-paid utilities ● Telecom prepayments ► FMCG supply chain (P&G, Nestles, Coca Cola) ► Other SME suppliers (e.g., in construction) ► Agricultural supply chain information ● E.g., coffee wet mills collect data on acreage, bushels, coffee berries per bushel, bean quality, price, sale….for season after season after season ● Similar data in tea, dairy, etc. Potential alt data in emerging economies
  • 6. © 2010 Experian MicroAnalytics. All rights reserved. 6 What is FIRM?  FIRM is a new initiative by Experian, the world’s leading consumer information services and risk analytics firm and PERC  FIRM aims to leverage digital technology to gather non-financial information in real time to create a financial identity, credit risk profile and income estimate of a potential borrower, especially those outside the financial mainstream.  FIRM is not a credit bureau. It does not collect or centralise any information. FIRM provides a solution for lenders when a bureau has no report. Conducted a feasibility study sponsored by Bill and Melinda Gates Foundation in Kenya December 2012 – May 2013
  • 7. © 2010 Experian MicroAnalytics. All rights reserved. 7 FIRM seeks to overcomes hurdle: the incentive to share data  Because alt data providers are reluctant to turn over their whole database, FIRM does not store data. Data furnishers only provide data on each individual request they receive, leaving them in control of their database.  Because alt data providers resist giving data for free so that others make money, FIRM shares revenue based on the value of the data.  Because alt data providers are concerns about customer fears of privacy, FIRM requires that consent be obtained each time the applicant’s data is pulled.
  • 8. © 2010 Experian MicroAnalytics. All rights reserved. 8 The FIRM Network Structure
  • 9. © 2010 Experian MicroAnalytics. All rights reserved. 9 FIRM and the Agricultural Supply Chain Large/Medium Buyers Processors Farmer Small Holder SME Large/Medium Suppliers Banks MFIs SACCOS FIRM Information Information (e.g., Coffee wetmills, tea factories, dairy processors) (Agri inputs) FIRM Report VAS such as Score Biometric ID in Economies where needed Sales Purchases Advances AcctRecAcctRec Loan product
  • 10. © 2010 Experian MicroAnalytics. All rights reserved. 10 Advantages for the lenders  Better Data: Lenders get access to new data, available for the majority of the potential borrowers and are able to better predict credit risk and affordability.  Lower Costs: Use of FIRM reduces origination costs as data that was manually collected is now available digitally.  Can ease the entry of larger lenders into lower income segments without altering their lending models very much.
  • 11. © 2010 Experian MicroAnalytics. All rights reserved. 11 Advantages for the borrowers  Fairer, more inclusive credit access: Experience and research demonstrate that by using non-financial data, lenders extend affordable credit to a much greater percentage of low income, female, and minority borrowers.  Access to more affordable mainstream credit: Borrowers get access to competitive financial products since their credit risk is better accessed and start being reported to credit bureaus, becoming credit visible.  Protections: Borrowers have control over this information being accessed, as they need to give their explicit consent, limiting chance of consumer backlash for unauthorized violation of privacy.
  • 12. © 2010 Experian MicroAnalytics. All rights reserved. 12 The need for FIRM Why FIRM, given new digital finance MNO driven options like SMART (Philippines), M-Shwari (Kenya), why share data rather than have holders enter financial markets  FIRM will enable lenders to digitally provide a broader range of financial services ► A lot of new digital finance provides small, short-term loans (often month payback period). ► To identify which BoP, MM borrowers can afford longer term loans for investment, a more 360° financial view is needed—willingness and capacity ► A more comprehensive historic view of income cycles also allows lenders to better structure products, e.g., payment cycles that match up with agricultural income
  • 13. © 2010 Experian MicroAnalytics. All rights reserved. 13 What Our Feasibility Study Found  Data furnishers: ► There are data sources that are being digitized in agriculture (tea, dairy) ► The question of confidentiality, loss of control and fairness is a major hurdle, i.e., incentives design is key to data access. ► Large strategic players are less willing—seek to capture revenue for themselves, other players unwilling to share with strategic players; challenge to developing a comprehensive view  Large lenders: ► Willing to service down market if down market risk assessment segments can be made to conform to their risk assessment processes.
  • 14. © 2010 Experian MicroAnalytics. All rights reserved. 14 14 201 West Main Street Suite 202-D Durham, NC 27701 USA www.perc.net +1 (919) 338-2798 x803 14