Fintech: Data Standardization is Your Next Competitive Advantage
Summary
Most of us didn’t think too much of it given our projects, reports and desertion all had nicely formatted and packaged information as their input and, often the data is biased to help us understand the algorithm of theory at hand. I would like to follow up Orchard Platforms white paper on data standardization with a few more practical issues I’ve encountered in the field of credit risk statistical modeling. Sophisticated firms with access to vast amount of data can have a real advantage over their competitors, anywhere from fraud detection to pricing guidelines, However, let’s recall what my Computer Sciences professor once said, “Garbage in, garbage out.” If an originator uses their own loan performance to build a strategy or a model to reduce fraud issues as simple as first payment default, one may argue that it is fairly easy exercise. To start, properly disclose your lending portfolio doesn’t stop at a report that shows your investors average FICO, DTI (Debt to Income) ratio, utilization rate and or percentage of charge offs. However, tracking defaults in a meaningful way such as the rate of which your portfolio transitions from 60 to 90 to 120 days past due is critical in understanding when you will be breaking your covenant or concentration limits with our investors.