Why We Invested: Lenddo

October 10, 2016

I had spent 15 years working on microfinance when one day, back in early 2011, Jeff Stewart, the cofounder and chairman of Lenddo, walked into my office. By then, I was already sold on the concept of using an individual’s community as collateral for a small loan—we had been doing that already with low default rates, but granted at a very high cost: We would send credit officers to the field, sometimes on a bicycle, to interview people’s neighbors, for example. After that first conversation with Jeff, my head was spinning. His arguments were pretty solid. If you believe that your online social network reflects your real life friends, could you use the same principle to actually score somebody based on their social network? Even better, with the push of a button and in a second?

I was intrigued. By the time Jeff presented his idea to Wall Street in a TEDTalk event held at the New York Exchange in 2012, Omidyar Network was already an investor in the company.

Lenddo’s concept was rooted in the past notion that when lending, a person’s character is as important as cash flow, income, or assets. Leveraging the convergence of current trends, such as the pervasiveness of social media, the expansion of smartphones, and the rise of an aspiring middle-class, Jeff believed we could use advanced algorithms on non-traditional data sources to update this concept to current times.

Lenddo was the first company to pioneer this approach. In order to prove the concept and train its complex algorithms, Lenddo started lending on its own. Once the technology was calibrated by the lending experiments, the company evolved its business model to offer its risk assessment platform to lenders in the form of an easy to integrate API.

Today, Lenddo’s alternative credit scores and online verification services are used in more than 15 countries and the company processes tens of thousands of loan applications every month. More importantly, it helps lenders tap into a pool of qualified customers that were invisible to them before, approving 50 percent more loan applicants while at the same time reducing default levels.

Lenddo is a great example of a technology-enabled solution to a complex problem. Combining in-depth behavioral research with intelligent algorithms, the company’s platform can analyze more than 12,000 variables from nontraditional data—such as social media activity and smartphone data—for each loan application, generating a comprehensive credit score in minutes.

To ensure privacy, applicants need to opt-in to share their data and the information is collected only once, at the time of the loan application, and never shared with any parties, including lenders.

An important part of Omidyar Network’s global financial inclusion strategy is grounded in the belief that reducing the high cost of credit assessment and verification for lenders can help millions of consumers gain access to credit they need to invest in their future. Lenddo is doing just that.

Through this new partnership with FICO, the world’s leading analytics software company, which was announced last week, Lenddo’s platform will add a new layer of information to FICO’s traditional credit scoring, helping lenders to include millions of consumers into the formal credit market. In India alone, where the partnership will take effect, this new approach to credit assessment can help 250 million consumers[1] gain access to better, formal loans for the first time.


Omidyar Network. Big Data, Small Credit: The Digital Revolution and Its Impact on Emerging Market Consumers. 2015.

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