Machine learning
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
The fate of zombie firms: prediction, determinants and exit paths
This paper examines how machine learning and statistical methods may be used to predict whether or not zombie firms will escape their fate as zombies.
Enhancing default prediction in alternative lending: leveraging credit bureau data and machine learning
The authors apply machine learning techniques to credit bureau data and loan-specific variables to improve default prediction in the alternative lending sector.
Supervised similarity for high-yield bonds
Quantum cognition ML is used to identify tradable alternatives for high-yield corporate bonds
How magic a bullet is machine learning for credit analysis? An exploration with fintech lending data
The authors apply machine learning techniques to consumer fintech loan data to assess how such techniques can improve out-of-sample default prediction.
Investment decisions driven by fine-tuned large language models and uniform manifold approximation and projection-supported clustering and hierarchical density-based spatial clustering
The author proposes an investment strategy using LLMs and text from social media posts and business and economic news and demonstrate that the strategy outperforms the chosen benchmark.
Why AI will never predict financial markets
Laws that govern swings in asset prices are beyond statistical grasp of machine learning technology, argues academic Daniel Bloch
DeepSeek success spurs banks to consider do-it-yourself AI
Chinese LLM resets price tag for in-house systems – and could also nudge banks towards open-source models
Tech firm OneChronos to offer ‘bundled’ equity-FX trading
New auction algorithms will optimise multi-leg trades; FX roll-out due in second quarter
AI ‘lab’ or no, banks triangulate towards a common approach
Survey shows split between firms with and without centralised R&D. In practice, many pursue hybrid path
Everything, everywhere: 15 AI use cases in play, all at once
Research is top AI use case, best execution bottom; no use is universal, and none shunned, says survey
Researchers, quants, strats – AI is coming for you
Survey IDs roles to be most impacted by front-office AI, but experts say many will change, not disappear
Front office open to AI promise
AI offers real potential for capital markets firms. But how disruptive, and how immediate, will the impact be?
For AI’s magic hammer, every problem becomes a nail
Risk.net survey finds banks embracing a twin-track approach to AI in the front office: productivity tools today; transformation tomorrow
Degree of influence 2024: volatility and credit risk keep quants alert
Quantum-based models and machine learning also contributed to Cutting Edge’s output
Quants try investing like Socrates, with help from AI
Researchers are testing whether LLMs can use methods borrowed from ancient philosophy to answer complex questions
How a serverless risk engine transformed a digital bank
Migrating to the cloud permitted scalability, faster model updates and a better team structure
Mitigating model risk in AI
Advancing a model risk management framework for AI/machine learning models at financial institutions
The prediction of mortgage prepayment risks in the early stages of loan origination: a machine learning approach
The authors put forward a machine learning model for the prediction of mortgage prepayment risks at the loan origination phase.
Advanced visualization for the quant strategy universe: clustering and dimensionality reduction
The authors present a novel visualisation model, based on 5000 quantitative investment strategies, which can identify nonlinear relationships and clustering strategies with similar risk factor exposures.
Best use of machine learning/AI: CompatibL
CompatibL won Best use of machine learning/AI at the 2025 Risk Markets Technology Awards for its use of LLMs for automated trade entry, redefining speed and reliability in what-if analytics
Rising star in quant finance: Milena Vuletić
Risk Awards 2025: Machine learning-based volatility model confounds sceptics