In traditional banks, underwriting loans are typically based on two main factors: FICO score and human discretion, with FICO playing a key role. Innovators in the financial technology (FinTech) space such as P2P lending platforms go beyond FICO and rely on public sources of data, past loan data, and even heuristic factors such as the type of activity the visitor performs on the website, all to determine the potential risk of a loan and then assign a credit rating and interest rate.
The FICO Standard
FICO is a measure of consumer credit risk as determined by a private company originally named Fair, Isaac and Company but now known as FICO. The FICO score debuted in 1989, and consists of a combination of: payment history, debt burden, length of credit history, types of credit used, and number of inquiries. FICO score is the standard used by the vast majority of banks and loan issuers and is based on credit information from the three major credit bureaus Experian, Equifax and TransUnion.
Take FICO, Add Big Data
Today, the availability of data from any number of public websites, agencies, and public records, when used properly, can provide a more complete picture of a borrower. In fact, the leading platforms use a wide range of data some of which may include:
- Length of time the borrower has used the same email address
- Number of connections on Twitter, Facebook or other social media sites
- Reviews and ratings from business directories such as Yelp
- Sales volume from credit cards
- Accounting records from small businesses
- Local and government public records
“We are literally a big data company with marketing and risk people, but this is data,” said Ron Suber, president of Prosper at the AltFi Global Summit 2014. “We’re constantly looking for new sources of data to validate identity, income, employment. (Data is a very) big deal.”
Banks may not have the technical ability, the analytical skills, policies, or internal desire or ability to utilize these new forms of data and consider them as part of their lending review process. Marketplace participants have no legacy ideas or ties and can and must use the latest technology to create a better more innovative platform in order to lend, or provide the opportunity for others to lend, to a wider pool of quality candidates efficiently.
By combining both FICO and additional data, a more complete composite of a borrower can be analyzed and presented to potential lenders. Charles Morrow, a partner in Foundation Capital, a venture capital firm specializing in marketplace lending and FinTech (also a lead investor in Lending Club) says, “Smart data can suss out false positives (when FICO data incorrectly suggest capacity and willingness) and false negatives (when FICO data incorrectly suggest an inability or unwillingness).”*
Creating the Unique P2P Lending Credit Score
The two leading P2P lending platforms in the US, Prosper has created the Prosper Score, and Lending Club has a rating called Model Rank. Prosper and Lending Club state that these scores are derived from a combination of the answers from a borrower’s application, credit reporting agency or FICO score, and “other” factors.
The Prosper Score and Model Rank are then used to determine a Prosper Rating on Prosper and Loan Grade on Lending Club. These ratings indicate the risk level of the loan and determine the interest rate of the loan accordingly.
Making Data Transparent
While all of the underlying data used to determine the score is not completely available, Lending Club and Prosper both make a variety of risk data available on their platforms accessible through the APIs utilized by P2P lending funds like the Prime Meridian Income Fund and institutional investors that have created their own access to such data.
Professional traders can create pre-determined algorithms for analyzing these scores and the various characteristics of each loan, and automatically allocate (or not) based on these rules. Algorithms are modified over time based on the results, changes in trends, and other conditions.
Conclusion
Marketplace lending is a segment that counts on innovation to create new ways of providing financial services and analyzing the risk in providing services on a per client basis. In technology, attention frequently centers on new service concepts and how they are provided, but the concepts are empty without the innovation in how these services are processed, reviewed and executed. In the era of Big Data it’s these unique processes and analysis that are a catalyst for creating truly disruptive financial services.
Don Davis is a Managing Partner and Portfolio Manager of Prime Meridian Capital Management, an early adopter P2P/online lending investment management firm which manages the Prime Meridian Income Fund and Prime Meridian Small Business Lending Fund, and has an established track record of outperforming P2P lending platforms.
*From Foundation Capital Whitepaper “A Trillion Dollar Market By the People, For the People: How Marketplace Lending Will Remake Banking As We Know It”, by Charles Moldow, Foundation Capital