London LendIt: Santander InnoVentures

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Banking partnerships: Mariano Belinky (Santander InnoVentures)

Mariano explains what is the benefit for banks to invest into disruptive ventures such as peer to peer lending market places.

Even though it might sound counter-intuitive and can be perceived conflicting and cannibalizing its own business, investing and supporting disruptive FinTech companies help established banks create a learning curve, better help their current customer and learn how to serve new customers. The usually lower cost that structures like market places or other FinTech companies enjoy make customer who previously were not attractive become interesting for larger banks.

One example is customers who are turned down when applying for a loan at a bank are now redirected to peer-2-peer market places where they have a higher chance to get financing.

Another example mentioned by Mariano is based on the recent deal with Kabbage. According to him, Kabbage managed to crack the “branch challenge” where branch managers are not willing to spend lots of time and energy in underwriting small loans to SMEs and SMEs are not willing to spend more than 8 minutes applying for a loan and getting immediate response.

As a result, and even if there will be some marginal cannibalization in the future, banks will gain from understanding and leveraging partnerships and collaborations with such disruptors. One interesting comment is that a large portion of customers who apply for a loan through peer-2-peer market places have been declined by a bank or “regular” credit organization before and therefore it’s important to offer these customers options. These customers are not necessarily higher risk customers but instead the information used by established credit institutions has not been good enough to rightfully assess the risk level or the customers scored right above the threshold the institutions have set.

This being said, so far not many alternative lending platforms have not experienced downturns and therefore it’s too early to say what data sources, what credit model perform the best during harder financial times.