1. Access to Finance, Psychometric Screening & Female Entrepreneurship The Entrepreneurial Finance Lab

2. © 2011 – EFL Global Ltd. All Rights Reserved. Some stylized facts Microcredit -> increased access to finance for female microenterprise owners But females still lag greatly in SME ownership In general, microcredit hasn’t lead to many transitions into larger formal growth-generating SMEs MFIs seeking to give larger loans for SMEs are facing many barriers, similar to those faced by downscaling banks Business Size (revenues) % Female owned

3. © 2011 – EFL Global Ltd. All Rights Reserved. Some stylized facts Why do these gender and business size differences exist? Possibility 1: entrepreneurial traits in men v. women? Possibility 2: current approaches biased against women? Microfinance screening – use social capital, group liability instead of collateral But MFI approach has limits for moving upscale to SME financing – amounts, risk, and relevance of data So SME lenders fall back on collateral & history New approaches to screening on future potential rather than current wealth could increase access to finance SMEs And in particular for female-owned SMEs

4. © 2011 – EFL Global Ltd. All Rights Reserved. What is our new approach? Risk Psychological Profile Ethics & Honesty Intelligence Business Skills – 30-40 minute automated proprietary psychometric test – Structured objective assessment of character & ability – Forward-looking rather than backward looking credit history and collateral EFL Tests can meet and exceed the predictive power of credit scoring models in developed countries and can be applied to MSMEs that lack financial statements or collateral

5. © 2011 – EFL Global Ltd. All Rights Reserved. EFL Research Pilots – Started as research center at Harvard CID in 2006 – Initial funding from Tested 2500 entrepreneurs across Africa & Latin America Loan size $1000$10,000$100,000$1m

6. © 2011 – EFL Global Ltd. All Rights Reserved. EFL Research Pilot Results 2007-2010 Pilot testing procedure: Randomly selected samples of clients were given our test We then measured the statistical power of the test to separate the good performers (successful businesses, repaid financing) from the bad performers (failed businesses, default) The results are very strong: our test is able to meet and exceed the predictive power of credit scoring models in developed countries, which use audited financial statements and history But our test can be used on microenterprises and SMEs who don’t have financial statements and histories The predictive power of our test is summarized using the AUC: area under the ROC curve This is a common measure of how well a test or scoring model does. It is a number from 0 to 1. The higher, the better A ‘good’ corporate credit scoring model in developed countries has an AUC of 0.65 to 0.75 EFL Global Results: AUC of 0.75 Relationships with each individual dimension are statistically significant at the 95% level

7. © 2011 – EFL Global Ltd. All Rights Reserved. From research to implementation EFL partnered with Africa’s largest bank in 2010 ( assets of over US $200 billion) Wanted to increase participation in the profitable and rapidly growing SME segment But collateral & histories not working- needed new tools with low transaction costs & controlled risk Began pilot lending against the EFL test 6-12 month unsecured working capital loans 4 countries Average loan size $8,000 USD

8. © 2011 – EFL Global Ltd. All Rights Reserved. EFL in Africa Yes No YesNo X Pilot Design Want to know exactly how much value EFL adds After a simple pre-filter, every applicant gets EFL evaluation and bank evaluation EFL If one OR the other says ‘yes’, the loan is given So we know exactly how much EFL helps in reducing risk for current market, and how much it opens up the new market Set EFL ‘Yes’ decision very aggressive (accept everyone with 10% or lower probability of arrears) to maximize learning

9. © 2011 – EFL Global Ltd. All Rights Reserved. Results YesNo Yes 20% of loans 75% of loans No5% of loans EFL -Reduces risk on existing clients: test separates approved clients into top 3rd with 1% arrears, bottom 3rd with 15% arrears -Opens up new markets in a big way: 3/4 of loans are EFL “Yes” Bank “No”, meaning inaccessible without EFL -These loans are performing at exactly the target cutoff selected by the bank

10. © 2011 – EFL Global Ltd. All Rights Reserved. Results Currently lending $1 Million USD per week using EFL tools Allowing the bank to penetrate completely new markets in a highly profitable, scalable way Because of these powerful results, the bank is signing a major agreement with EFL across Africa Aggressive roll-out to 9 countries within the year 100,000 tests, anticipated lending over $250,000,000

11. © 2011 – EFL Global Ltd. All Rights Reserved. Results: Female Access

12. © 2011 – EFL Global Ltd. All Rights Reserved. Results: Entrepreneurial Traits Slightly more external locus of control NO differences in any other key personality traits associated with entrepreneurial success Less likely to run their parents’ business Therefore, on average have a better EFL score – Male average: 268 – Female average: 273 – P-value:.028**

13. © 2011 – EFL Global Ltd. All Rights Reserved. Results: Predictive power Even after removing collateral requirements, screening on credit history works poorly for women Credit history-based screening: – Model degradation of 36% from males to females Psychometric screening works better: – Still model degradation, but only 15% Model degradation calculated as reduction of Gini coefficient from male vs. female predictions

14. © 2011 – EFL Global Ltd. All Rights Reserved. Other differences For males: – intelligence and social sensitivity are stronger differentiators of risk For females: – honesty, calmness/steadiness, and dependability/dutifulness are stronger differentiators But differences are very slight. Main results: – Levels of key psychometric variables are similar between males and females – same frequency of entrepreneurial traits – Same psychometric variables predict risk for males and females – Psychometric screening does better job of predicting risk for female entrepreneurs than traditional criteria – increases female access – And increases access to finance for SMEs in general

15. © 2011 – EFL Global Ltd. All Rights Reserved. EFL Next Steps – Latin America Winner of G-20 SME finance challenge With G-20 & FOMIN support, major Latin America expansion starting in November 2011 First major regional partner: