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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.

Modernising regulated analytics (without rebuilding legacy controls)

15 mins with…Bilal Shaik Mohammad, Director of Sales, GCC

Combined vs bespoke models in credit risk: Does segmentation still add value?

Hybrid case-based reasoning for better underwriting decisions

Modernising credit-risk models without drifting outside risk appetite

Identifying hidden fraud networks: Why fraud detection needs a network-based approach

Sample size and model choice: When GBMs outperform DNNs in credit risk

Smarter fraud and AML convergence: Escaping the silos

Geopolitical shocks and credit risk: Are your models ready?

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