THE THOUGHTFUL ENTREPRENEUR PODCAST
Trust Science aid preexisting data scientists or risk departments in assessing borrowers’ profiles. They can be the entire solution for smaller businesses or those who have never had experience working with a bureau before because of low score levels. They bring automation and automated decision-making in a high degree of predictability on creditworthiness.
Evan gave out some indicators of what to look at when assessing an individual's creditworthiness. He also talked through the challenges in the conventional system and how Trust Science comes into play to close the gap. Working with the Trust Science system helps their customers find a lender customer worldwide.
Key points from the episode:
- What industry does Trust Science work with?
- Why are old formula credits a bit problematic?
- Indicators to look at to assess creditworthiness.
- How did Trust Science come about?
- Business growth opportunities for Trust Science.
About Evan Chrapko:
Evan is a serial entrepreneur and investor having served as CEO or advisor for numerous innovative start-ups including FloNetworks (acquired by DoubleClick for $80 Million) and PlateSpin (acquired by Novell for $205 Million). Prior to Trust Science, Evan and his brother Shane founded and, within 30 months, sold cloud storage pioneer DocSpace for $568 million. Evan is a CPA, CA and holds a Juris Doctor (Law Degree) from Columbia University. He is a Henry Crown Fellow of the Aspen Institute, a member of YPO, and he has been named to the Real Leaders Global 100 (alongside Bill Gates, Richard Branson, Elon Musk, Peter Diamandi,s et. al.) and a Top 50 AI CEO (alongside others like the CEO of Data Robot.)
About Trust Science:
Organizations in many industries rely on credit scores to gauge amounts and types of credit that they will offer to an individual. Those scores purport to provide meaningful information about how much debt a person should be able to take on and what the level of risk (the borrower’s probability of default) will be. However, the information from old credit bureaus isn't always deep enough for a meaningful assessment, in part because it relies on outdated types of data & calculation methods. This is especially punishing for the financially disadvantaged or N2C (New to Country/New to Credit) person. Credit Bureau 2.0, a FinTech SaaS platform, is the solution to this problem, harnessing alternative data and explainable AI for more accurate and precise credit assessments. This is enabling lenders to find more trustworthy borrowers and letting borrowers gain access to credit based on information that traditional credit bureaus aren't taking into account.
02:24 – “You have people down there, approximately 40% of the people below 700
who, if you gave them the money, would behave like prime or super prime borrowers. They would rather lose their left arm than welch on a debt.”
02:47 – “Many agonies and unnecessary exclusion happen because the current multi-decades-old and multi‑billion dollar system doesn't work very well.”
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Links Mentioned in this Episode:
Want to learn more? Check out the Trust Science website at https://www.trustscience.com/
Check out Greener Trust Science on LinkedIn at https://www.linkedin.com/company/trust-science/
Check out Evan Chrapko on LinkedIn at
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