# Spin Mobile: Revolutionizing Credit Scoring

An episode of [The Mwango Capital Podcast](https://invisiblenetwork.ai/podcast/1583367792), 17 Dec 2024, 57 min.

Audio: https://api.substack.com/feed/podcast/153253271/2b6b10eb95f2e6cea7f9b7e70b3a9f6a.mp3

In this episode recorded on 21.11.2024 and hosted by Tim Kipchumba - Co-founder at Questworks, we are joined by Spin Mobile Limited’s CEO, Dr. Victor Kiplagat, and CTO, Eng. Sammy Kariuki, to discuss how alternative data is revolutionizing credit scoring. We cover the use of alternative data in credit scoring, security and privacy of user data, the application of AI in credit scoring, and adapting alternative data for SMEs. Subscribe to get notified when we make a new post. Key Quotes “ One of the biggest benefits of this alternative data is triangulation. Data should be able to verify itself. I'll give you an example. If this customer at the point of loan application or providing their KYC indicated that they operate in Thika Road, maybe Kahawa Sukari or Kahawa Wendani. Maybe wrote they run a small shop around that. Now, when you get data, let's say from mobile money statements, which actually provided by the customer, and you notice that this customer is literally doing their shopping every day in the evening in Langata, they take their lunch along Langata Road, probably shop at Naivas Supermarket next to Langata Road, literally itself correct. So it's actually able to tell you there is something here that is not adding up. So that's really the beauty of having many sources of data. Remember, in conventional lending what we call traditional data, it was mainly referencing. It is historical and submitted by financial institutions. But now if you have this many sources of data and confirmations coming in from these verification APIs, you can be able to verify most of these aspects.” Dr. Victor Kiplagat “Another challenge is ensuring that the lender has the credit scores within three minutes or five minutes, and whether it's a tiny statement, 20 pages, or something with 2000 pages, they're able to make a decision within five minutes. This overall ensures that at some point, we will not even need to have human beings looking at this data. We can be able to automate this data because you can guarantee that the system would have already generated the expected output within one minute and can move on to the next decision.” Eng. Sammy Kariuki “ Anybody who is venturing into technology space, be ready to change. Remember our story of how we started by being a lending company, and it's a customer who requested us to do this credit scoring. We were not to get into it. So it was client-led. So I think be more agile. Be willing to try new technologies.” Dr. Victor Kiplagat “Listen to who you're targeting, your customers, what they need. And I think that's one of the things that have helped us to innovate and to keep improving on the product. It's not an easy thing to do perfectly, but it really ensures that you are solving real problems and that people find your product to be very useful and adaptable. That's something I would tell any startup or any company that's trying to find its footing and make a difference.” Eng. Sammy Kariuki Show Notes 00:00:00 Introduction 00:06:44 Alternative Data in Credit Scoring 00:15:20 Misconceptions About Alternative Data 00:22:24 Financial Inclusion and Success in Credit Decisions 00:25:51 Challenges in Collecting, Processing, and Analyzing Alternative Data 00:28:10 Classification, Security, and Privacy of User Data 00:33:20 AI in Credit Scoring 00:37:00 Open Banking and Data Integration 00:39:36 Adapting Alternative Data for SMEs 00:45:53 The Future of Credit Scoring in Emerging Markets 00:49:11 Expanding Reach and Advice for Fintech Startups Get full access to The Mwango Weekly at mwangocapital.substack.com/subscribe

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