Sramana Mitra: Is this a Software-as-a-Service that you sell to banks, or is it a two-sided marketplace that you plug banks into?
Jared Kaplan: We would describe it as a service provided to banks. A bank hires us and asks us to do all the acquisitions.
Sramana Mitra: So you acquire loan customers on behalf of banks?
Jared Kaplan: Yes, we acquire the customers. We provide all of the alternative data algorithms because these customers cannot be underwritten based upon traditional credit scores. Banks use that to adapt and approve customers for credit.
We provide them the technology platforms so that they can make decisions in real-time. We also provide them the customer service behind that. The bank is essentially outsourcing that whole process to us.
Sramana Mitra: To provide small business lending solutions?
Jared Kaplan: It’s not the small business; it’s the consumers. These are small unsecured personal loans to consumers.
Sramana Mitra: Consumer is a big word. What segment of consumers do you cater to?
Jared Kaplan: Based on the US census data, we cater to the median US consumer. These are the people that are making $50,000. They have a job and a bank account, but they have done something terrible to damage their credit.
If you were to judge them based on the traditional credit metrics, they would be deemed as having near-prime for non-prime credit. Therefore, they can’t get access through traditional means.
Sramana Mitra: What is the size of the population that fits this bill?
Jared Kaplan: Out of the 60 million Americans that don’t have access to traditional financial products, 30% are a good fit for this product. That would be around 20 million people.
Sramana Mitra: What are some examples of reasons why they have a bad credit history?
Jared Kaplan: Some of the reasons can be that they went through a divorce, lost a job, and got behind a mortgage payment. Maybe they were undisciplined when they were younger and didn’t pay bills. It’s a good person that has made a mistake.
By traditional measurement, you would say that this person would not be creditworthy. With all the interesting alternative data, we can see through the traditional metrics and figure out who is creditworthy, even though their traditional credit score would tell you otherwise.
Sramana Mitra: Very interesting. What are the signals that show that this person had changed their course and is now creditworthy? What are examples of data signals that you are picking up?
Jared Kaplan: It starts with how you fill up the application. Based upon how you fill up the application, we can determine the riskiness of the customer. You cannot make a decision on that though because that wouldn’t be appropriate from a fair credit decision perspective.
We look at everything from how often you are shopping for various products. We find out what you spend your money on. We look at your banking behavior and how often you go negative in your bank account and what your average balance looks like. We then confirm your income and consistency of income to determine whether you can afford the product.