A new study suggests that lenders may get their strongest overall read on credit default risk by combining several machine learning models rather than relying on a single algorithm. The researchers ...

The regulatory environment continues to increase in complexity as the EBA and the PRA provide new guidelines and updates to ...

These events remain relevant largely because they occurred during an extended period of geopolitical stability that ran from the late 1990s through to the early 2020s. When shocks did occur, they ...

In the past few years, there have been several developments in the field of modeling the credit risk in banks’ commercial loan portfolios. Credit risk is essentially the possibility that a bank’s loan ...

LendScore uses real-time cash flow data and unique account connection insights from the Plaid Network to provide lenders with an updated view of borrower risk To give lenders a more complete financial ...

Pietro Rossi had a problem. An insurance company needed a model that could price bonds based on the likelihood of changes in credit ratings. The standard, off-the-shelf models are based on probability ...

This article was written by Jerome Barkate, Nakul Nair, Zane Van Dusen, and Scott Coulter. We are witnessing a remarkable period in the credit markets. Following years of accommodative monetary ...

Collateral Analytics has launched the CA Credit Risk Model. This new patent pending product is designed to offer quantitative measures of the risk and cost of potential borrower default embedded in a ...

David Croen, Head of Risk Products at Bloomberg L.P., was interviewed by Alison Fletcher, a Corporate Treasury Specialist at Bloomberg, on what customers have faced when evaluating credit rate risk ...