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Featured
10 February 2026
Machine learning model stability: Do Gradient Boosting Machines (GBMs) and Deep Neural Networks (DNNs) really degrade faster?

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.

Nick Sime
28 April 2026
15 mins with…Bilal Shaik Mohammad, Director of Sales, GCC
Saghir Khan
28 April 2026
Combined vs bespoke models in credit risk: Does segmentation still add value?
Nick Sime
23 April 2026
Hybrid case-based reasoning for better underwriting decisions
Steve Finlay
20 April 2026
Modernising credit-risk models without drifting outside risk appetite
Carl Ireland
14 April 2026
Identifying hidden fraud networks: Why fraud detection needs a network-based approach
Ben Archer
12 March 2026
Sample size and model choice: When GBMs outperform DNNs in credit risk
Nick Sime
06 March 2026
Smarter fraud and AML convergence: Escaping the silos
Ben Archer
04 March 2026
Geopolitical shocks and credit risk: Are your models ready?
Steve Finlay
10 February 2026
Machine learning model stability: Do Gradient Boosting Machines (GBMs) and Deep Neural Networks (DNNs) really degrade faster?
Nick Sime
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