MANAGING RISK IS A CONTINUOUS JOURNEY
Whether due to your own risk appetite, or in response to the increasing pace of regulatory change, managing risk is a continuous journey. We deliver best-in-class analytics and consulting to ensure organisations of all industries, sizes and complexities optimise profits and achieve regulatory compliance.
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Exploring Nationwide's ‘explainable’ AI-driven application scoring
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Transforming onboarding processes for Together
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Implementing Data Governance and Data Management for England’s Largest Specialist Housing and Care Provider
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Starling Bank appoints Jaywing to build a robust IFRS 9 model framework for its CBILS
Discover Archetype
Use explainable and controllable AI to generate models with greater accuracy, speed and precision than ever before.
Find out moreJaywing and Virgin Money shortlisted for Collections & Vulnerability Award
Jaywing has been shortlisted alongside Virgin Money for Best Outsourcing & Partnership Initiative of the Year at the Collections & Vulnerability (C&V) Awards 2026. The nomination recognises a joint project to develop a predictive machine learning model that not only identifies customers who may be at risk of attrition, but also estimates when that risk is most likely to occur.
The Mills Review: a smart long-term plan with a near-term problem
The FCA's Mills Review plans for 2030. For model risk and credit risk teams, here's what it leaves open and what to start now.
Are fraud controls becoming unsustainable?
Fraud volumes are rising. Investigative capacity isn't. Here's why rules engines drift toward unsustainability, and what the data says about where to focus.
How to choose a risk modelling partner
Choosing a credit risk modelling partner? Learn what to look for, the questions to ask, common pitfalls to avoid and how to assess modelling consultancies with confidence.
Credit risk modelling statistics 2026: What risk managers need to know
Here is what the data shows and what it means for credit risk modelling decisions in 2026.
Fraud contamination in credit risk models: why portfolios stop behaving as expected
Fraud losses hiding inside credit risk models corrupt training data for years. Here's what a retrospective audit catches that backtesting can't.
