Machine learning
XVA desks prioritise core tech upgrades over AI
Vendor upgrades, cloud-native rebuilds and sensitivities tooling dominate 2026 budget road maps
Supervised similarity for firm linkages
Quantum fidelity is used to capture dependency structures in equity
AI as pricing law
A neural network tailored to financial asset pricing principles is introduced
Deep self-consistent learning of local volatility
This paper offers an algorithm for calibrating local volatility from market option prices using deep self-consistent learning, by approximating both market option prices and local volatility using deep neural networks.
The AI explainability barrier is lowering
Improved and accessible tools can quickly make sense of complex models
BlackRock, BGI and the big quant pivot
How the world’s largest asset manager revived the fortunes of its struggling west coast unit
Rates investors unmoved by stories of AI bliss, or doom
Research shows downward moves in US Treasury yields around generative AI model releases
Why know-it-all LLMs make second-rate forecasters
A bevy of experiments suggests LLMs are ill-suited for time-series forecasting
Addressing climate-related risks in banking: a framework for sustainable risk management and regulatory alignment
This paper puts forward a dual-layer approach to climate risk management with utilises root cause-based analysis and severity assessments to prioritize and address climate-related risks.
A comprehensive explainable approach for imbalanced financial distress prediction
The authors suggest an explainable machine learning method for imbalanced financial distress prediction which uses extreme gradient boosting.
Trump’s FX impact: a tale of two terms
Traders say Trump version 2.0 is already proving a much trickier task to manage than the original, and have had to adapt
Removing the barriers to AI success
Addressing challenges of data quality and governance to scale AI for competitive advantage
The AI bot that left the garage
Senior operational risk exec explains how hidden third-party feature could lead to systemic risk
Quants use AI to shush noisy order-book data
Signals from clusters of seemingly informed trading perform better, researchers say
Building reliable and successful LLM-based workflows
How AI is reshaping analytics, compliance and modelling in finance
Machine learning and a Hamilton–Jacobi–Bellman equation for optimal decumulation: a comparison study
This paper ascertains a decumulation strategy for the holder of a defined contribution pension plan with an approach based on neural network optimization.
Stock-picking bots and models that don’t trade: AI at Vontobel
Early experiments are already bearing fruit, in sometimes surprising ways
Podcast: Villani and Musaelian on a quantum boost for machine learning
Classical methods struggle with highly dimensional problems. Quantum cognition takes a different approach, as hedge fund duo explain
Model risk quantification for machine learning models in credit risk
This paper analyses bank-specific model risk measurement methods with a focus on implemented model risk rating solutions for MLMs and discusses challenges faced by the validation function.
Why AI-enhanced risk management is vital for open finance
In bank-fintech partnerships, AI can be both a source of operational risk and a solution to it
Bank FX market-makers ramp up AI usage
Barclays applies tech to predictions, while HSBC and ING look at pricing accuracy