Machine learning
Model risk managers see growing regulatory divergence
Risk Benchmarking study finds most banks expect easing of model risk supervisory scrutiny in the US, but tightening in Europe
MRM: how banks are scaling models in the age of AI
MRM capabilities are evolving to ensure compliance while helping organisations retain a competitive edge
Responsible use of artificial intelligence in financial market infrastructures
The author investigates current and prospective role of AI in FMIs and develops a principled framework for the responsible use of AI based on the principles of explainability, data stewardship, governance and ethics.
The do-it-all machine: model risk in the age of generative AI
Banks race to understand risks posed by new breed of multi-purpose bots
The MIT professor giving LLMs a ‘brain scan’
Hui Chen’s research is yielding new ways to interpret – and steer – AI models
New LLMs are proving to be surprisingly good quants
Strides in AI’s ability to do maths mean models can plausibly help with research
Can AI be the great equaliser in e-FX?
FX market-makers see real benefits for agentic AI in code generation and data analysis
CanDeal looks to simplify third-party risk management
Six-bank vendor due diligence utility seeks international reach
JP Morgan AI research founder and head departs
Manuela Veloso leaves as bank announces greater spend on tech and AI
Demand deposit balance prediction models under the interest rate risk in the banking book guidelines: an empirical analysis integrating time-series models and machine learning predictions in Mexican banks
The authors analyze the interest rate risk in the banking book regulations, arguing that financial institutions must develop robust models for forecasting demand deposit balances while adhering to regulatory guidelines.
Ram AI’s quest to build an agentic multi-strategy hedge fund
The Swiss fund already runs an artificial intelligence model factory and a team of agentic credit analysts
Degree of Influence 2025: Derivatives pricing dominates; quants don’t follow the AI herd
Rates and volatility modelling, as well as trade execution, top quants’ priorities
Artificial intelligence in password-less authentication: bridging the gap between security and transparency
This paper investigates the role played by artificial intelligence in the adoption of password-less authentication in India, providing insights for policy makers, information technology developers and digital service providers.
How investment firms are innovating with quantum technology
Banks and asset managers should be proactive in adopting quantum-safe strategies
Baruch, Princeton cement duopoly in 2026 Quant Master’s Guide
Columbia jumps to third place, ETH-UZH tops European rivals
Best use of machine learning/AI: ActiveViam
Bringing machine intelligence to real-time risk analytics
The role of personal credit in small business risk assessment: a machine learning approach
The authors investigate how personal credit data can be combined with business-level and tradeline variables in a machine learning framework to enhance default prediction.
Quantcast Master’s Series: Jack Jacquier, Imperial College London
A shift towards market micro-structure and ML has reshaped the programme
Interpretable machine learning for default risk prediction in stress testing
This paper proposes a benchmark model which can be used to predict the forward-looking probability of default of a real-world credit card portfolio.
XVA desks prioritise core tech upgrades over AI
Vendor upgrades, cloud-native rebuilds and sensitivities tooling dominate 2026 budget road maps
Machine learning in oil market volatility forecasting: the role of feature selection and forecast horizon
This paper investigates oil market volatility prediction, showing financial variables to dominate short-horizon forecasting, while macroeconomic and sentiment factors increase in importance at longer horizons