Individuals or businesses are denied credit due to lack of data. Given how suffused the world is by data, this is ironic. Hence, Alexander Graubner-Müller’s message, at the 2016 NOAH London conference in November, highlights how traditional financial systems fail the underbanked. Everyone produces increasing amounts of information daily by the use of the internet, smartphones etc. Thereby laying out (often) personalized footprints via the deployment of a broad range of online services available across the globe.
“That information provides a pretty good indication on some of the qualities which are important in determining who makes a good borrower.”
The biggest advantage here is that most of these data is today quite transferable.
“I can grant API access to my bank account and share my financial history. Basically with a click of the button. And financial institutions can use that to very easily understand my ability to repay. Likewise I can basically authorize API access to my LinkedIn or my Facebook profile. And provide additional proof about my identity and therefore give trust into my willingness to repay.”
Data science and analytics enable financial technology companies to gain a better understanding of who the customer is. By so doing they are hence able to better serve them. Traditionally, the process entails the customer going to a bank with a bunch of documents. This would most likely include income statements and tax returns to prove his ability to repay. Then the bank will go to the credit bureau. The individual’s credit report is then pulled out and their credit history reviewed. If they repaid a loan in the past, it is likely that they would repay a loan in the future. This therefore suggests a high willingness to repay. However, an underbanked person often finds it difficult and inconvenient to put together these document particularly in the digital world.
“[The underbanked] are people that are not employed in a regular fixed term job where they work 9 to 5 and have a stable income. Most of the underbanked are people that are self-employed, work as seasonal workers, and they may have multiple jobs. So admittedly it is hard for banks to understand the income pattern of these customers. And then there is usually little or no credit history given these people have usually never used credit before.”
The bigger problem here is that the credit bureau system is rather unreliable. Its architecture is not setup to work optimally for this customer group. With the reporting process the information sometimes does not come through properly. This may have to do with outdated or missing information. Meanwhile, some countries are still just in the process of establishing credit bureaus. And even where they exist, often they cover only a small fraction of the population. Also worth noting are developed countries with established credit bureaus, where laws could constrain which information may be shared.
“What we have done at Kreditech is basically build a scoring technology that takes advantage of this alternative data to replace the credit bureaus and compliment the credit bureaus in the rating process. And we do that by using modern age technology from the field of machine learning and artificial intelligence that helps us to process that information. It’s not only the credit rating that we derive. In fact we derive a fully personal loan offer. Which means understanding what is actually the rate most suitable for the customer to pay based on his affordability, what his monthly installment would be and certain issues relating to repayment flexibility such as offering him options of allowing him to skip a payment. All of which adds up to making the credit offer as good as possible for this customer.”
So the business we have built around machine learning and artificial intelligence, is an end to end consumer lending company. It acquires customers, underwrites the credit risk, finances the loans and then manages the servicing and collection process. Kreditech is thus succeeding to change the system, partly because of our willingness to make user experience convenient and accessible. Most of our originations:
“are today driven over web and mobile clients. And we just recently started to set up a lending-as-a-service business where we can integrate our products with partners to offer, for instance, a point-of-sale finance or a complimentary credit product for financial institutions that don’t serve our customers.”
To show you how well our technology is working, the CEO, who took helm of the company in 2015, gives a snapshot of a typical week. This involves 12,000 loans originated to people spread across the globe, spanning a very broad geographical distance.
“The cool thing is that those are really people either because of their credit history had no way of obtaining loans before. Or they are simply not near any bank branch” like somewhere in Siberia. “Or were in a need to obtain capital at a point when for instance banks were closed. Our goal as a company, is to really make sure that consumer credit around the world is no longer a two class system. And we see ourselves as putting people into control of their lives by making sure they have fair and easy access to capital when needed. Or as we can summarize, it improves financial freedom through technology.”