Alternative lenders use all sorts of complicated models based on sophisticated algorithms and machine learning in extrapolating data that is never certain or reliable. Cosigning is simple. It relies on a real person with a prime credit score. The equation is reduced to a number and a heartbeat.
To deliver above average returns to investors, online lending startups have been grabbing alternative data from a potential borrower’s email, social media, and even mobile accounts. They are determining risk based on a borrower’s likes, shares, and phone usage. There is a better option to capitalize on the $3.5 trillion consumer loan market: Cosigning.
Here are 5 reasons why online lenders like Backed, Inc., which relies on cosigning, yield superior overall returns than those lenders who rely on algorithms that are overloaded with over 10,000 data points:
- Using new methods is UNPROVEN. There is still a lot of trial and error. According to Lending Times, major online lenders employing alternative data suffer from default rates of over 5%. Alternative data may also pose possible regulatory and compliance pitfalls that can create a nightmare for compliance departments to clear these type of investments. Cosigned loans have been around for hundreds of years.
- A cosigned loan relies on relationships, not machines. Its success is underwritten on the trust between people, not computers. With an algorithm, an unsecured loan is backed by nothing more than the willingness of the borrower to pay back the financial institution. His motivation is the ability to take on more debt in the future. Cosigning is secured by human loyalty. The relationship between a borrower and cosigner can be a parent to a child, a boss to her employee, even army buddies who have entrusted each other with their lives.
- Social Media data is not normalized or simple. Many alternative lenders create a credit score based on thousands of different inputs. There is no guarantee enough data will be available to support these fragile risk models. For high yield borrowers, there are less LinkedIn professional accounts used compared to Facebook, making relevant data harder to come by. Social media giants are infamous for changing what they make available to third parties. It is an ongoing uncertainty that vital elements of an algorithm may suddenly disappear, making the model useless, and the investment itself riskier.
- For companies such as Backed, Inc, a cosigner must have at a least prime credit score, adding a significant layer of security for the loan. If the borrower fails to pay the loan, the loan becomes the obligation of someone with a credit score above 720.
- It is easier to dupe an investor using sophisticated terms about the science or technology behind their latest algorithm.
QUOTE: It’s a proprietary strategy. I can’t go into it in great detail. -Bernie Madoff
Any savvy lender, in hot pursuit of new funds, can dazzle an investor about the sophisticated details of their new business model using lots of Greek letters. A lot of money has been lost this way. Lest we forget Long Term Capital Bank and their new algorithms and how they caused stock markets to drop 20% in a mere 11 weeks. Merrill Lynch observed that mathematical risk models “may provide a greater sense of security than warranted; therefore, reliance on these models should be limited.”
Companies like Backed, Inc. which rely on cosigning, make lending simple. Cosigning entitles the lender to reduce the risk with an added layer of human security. It gives the borrower a lower rate, making it easier to pay off the loan. It benefits investors by offering the maximum returns for each risk. Technology is used to keep all parties in the loop at every stage of the loan, leveraging trust as top grade collateral.
Written by Gilad Woltsovitch.
Before Backed, Gilad Woltsovitch co-founded iAlbums, a semantic curation engine for media players in 2010 where he served as the company’s CEO from 2011-2014. In 2013, Gilad also served as the entrepreneur in residence for Cyhawk Ventures and joined the Ethereum project, establishing the Israeli Ethereum meet-up group. Gilad holds a Masters of Art Science and Bachelors in Sonology from the Royal Conservatory of The Netherlands in The Hague, University of Leiden.