AI Modeling

Most lenders we work with already have a sizable pile of data—application fields, bank data, bureaus, device signals, platform behavior. When building a credit model, not all data is good data. Some data actually carries long-term risk not just to your model, but to your entire business. Here’s a quick guide to evaluating your data. Here’s a snapshot of what we often see on our first call with a lender: Application data : Self-reported income, employer name, product type, pur

If you already have smart people on your team—and you’re not looking to fully outsource your modeling work—why bring in an outside partner? We’ve partnered with all sorts of modeling teams, from small startups creating their first model to established lenders and banks with mature modeling talent and fully built-out systems. Across all of them, we’ve learned how to make our presence a multiplier, not a crutch. Here’s how. 1. We meet you where you are We don’t sell prebuilt mo

One of the most common questions we hear about credit model modernization is this: “We use a lot of underwriting rules—how can we safely...

In short: Yes, we can. But not without you. Potential clients, especially in emerging markets, often ask us how well we understand the...

Do you want to accurately and consistently segment risk, therefore enabling your entire credit strategy? Then yes, you need to monitor...

"If it ain't broke, don't fix it." Lenders often push back when we suggest exploring a new model build. It's fair—model builds require...

What Exactly Is a Leaky Variable? A leaky variable is any feature in your training data that contains information you won't have at...

Gradient Boost Models (GBMs) have become the go-to tool for many credit modelers for good reason. GBMs can unlock meaningful lift in...

FICO and Vantage scores are well-known, widely used, and easily accessible. Meanwhile, building a custom credit model can take...

One of the most common questions we get about building a credit model is " How much data do I need to make it work? " And like many...