Machine learning models often outperform early, but what happens after go-live? We look at long-term performance of GBMs and DNNs using multi-year credit data.
23 April 2026
Hybrid case-based reasoning for better underwriting decisions
20 April 2026
Modernising credit-risk models without drifting outside risk appetite
14 April 2026
Identifying hidden fraud networks: Why fraud detection needs a network-based approach
12 March 2026
Sample size and model choice: When GBMs outperform DNNs in credit risk
06 March 2026
Smarter fraud and AML convergence: Escaping the silos
04 March 2026
Geopolitical shocks and credit risk: Are your models ready?
10 February 2026
Machine learning model stability: Do Gradient Boosting Machines (GBMs) and Deep Neural Networks (DNNs) really degrade faster?
06 February 2026
Tackling telecom-enabled fraud through smarter data collaboration
27 January 2026
Managing model risk using next-gen model-governance infrastructures