We were inspired by the high rate of financial inequality in Africa, especially in the area of credit accessibility. The structure of credit scoring itself constitutes systematic bias by excluding a significant portion of the population from accessing credit. This inspired us, and we have decided to tackle this, one product at a time.
What it does
It obtains customer spending data alongside other alternative data and uses it to predict the likelihood of default. This is then supplied to the loan providers to use to supplement traditional credit scoring criteria, and thereby provides a more objective evaluation of creditworthiness
How I built it
We will build the product using a suite of technologies including Firebase, node.js, and FusionFabric.cloud. Through FusionFabric.cloud we will be able to integrate Finastra’s API into our product, and thus obtain the latest and specific fintech data that isn’t available to the public.
Challenges I ran into
We needed to increase our value proposition significantly so as to increase the chances that Loan Providers will subscribe to our product. We also had to find a value proposition that fit the target customer. Over several nights of brainstorming, we reached the consensus that if we also provided the loan customers access to income-generating opportunities, it would reduce the chances of default, and would attract more adopters. Thus, this provides a more exhaustive value proposition and delivers more value to the customer than the sum of their individual values alone.
Accomplishments that I'm proud of
A Diverse team. Driving a product that holds Diversity and Inclusion as a core tenet.
What I learned
I learned about the various types of biases that exist in Fintech including Data, Algorithmic bias, and Systemic bias.
What's next for UpScore