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 ...

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 ...

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 ...

The key function of banks in the real world is endogenously creating (inside) money. But they do so facing solvency, liquidity and maturity risks and being subject to regulatory and demand constraints ...

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 ...

Structural models of default are widely used to analyze corporate bond spreads, but have generally been unable to explain why risk premiums are as high as they are. This credit spread puzzle can be ...

This piece is part of a series benchmarking bank climate risk management practices. Risk Management subscribers can view selected cuts of the underlying data here. Sign up for Risk Benchmarking emails ...

Thomson Reuters has introduced a new model that includes forward-looking analyst estimates to assess the credit risk of publicly traded companies. Automated traders can incorporate it via a daily data ...

STOCKHOLM, June 16 (Reuters) - Swedbank said on Monday Sweden's Financial Supervisory Authority had approved its use of a credit risk model for corporate exposures in Sweden and Norway, boosting some ...