This paper surveys the impressively broad range of machine learning methods and application areas for credit risk.
Differential PCA is introduced to reduce the dimensionality in derivative pricing problems
As organisations increasingly rely on models that cover a wide range of business functions, there is an increasing need to create and maintain a comprehensive model inventory for enhanced collaboration and regulatory compliance across multiple regions…
Covid-19 has caused widespread disruption to banks’ risk models. Some failed in the crisis while others have required significant overlays or frequent recalibration as extreme volatility has given way to ongoing uncertainty. As banks seek more agile…
PanAgora develops two-stage process that aims to weed out the greenwashers
Novel interpretability method could spur greater use of ReLU neural networks for credit scoring
Machine learning could help with loan decisions – but only if banks can explain how it works. And that’s not easy
In a Risk.net webinar convened in collaboration with Fusion Risk Management, an expert panel delved into best practices for businesses to elevate systems to the next level of prediction, preparation and protection
Data gaps and potential biases must be accounted for in approaches to tackling money laundering
Addressing privacy concerns is not a new topic for data and analytics, but with the explosion of regulations and growing consumer concern around how data can and cannot be used, addressing compliance requirements is more important than ever
A combination of machine learning techniques provides multi-period portfolio optimisation
Buy-siders look to machine learning for clues on the effect of rising prices on portfolios
Imposing set-asides based on stress tests “does not make any sense”, sustainability chief warns watchdogs
Dealers say agencies’ request for info could prompt new rules that stifle model innovation
In today’s fast-changing business environment, an effective governance, risk and compliance (GRC) programme is increasingly seen as a foundation of agile decision-making. Michael Gibbs, chief executive officer of SureStep Systems Integration, discusses…
$110 billion quant investor creates automated system to spot greenwashers
AI may help fund manager count emissions that companies fail to report
In this paper, we propose a conceptual framework that links the technical and business benchmarks in the domain of clearing houses and securities exchanges.
Christoph Kurth, partner and member of the global financial institutions leadership team at Baker McKenzie, covers some of the rapid technological changes under way brought about by, and in the wake of, the Covid-19 pandemic
Despite AI’s growth, investing still needs human adaptability and judgement, writes Schroders’ Lim
This paper examines which hybridization strategy is more suitable for credit risk assessment in the dynamic financial world.
Technologist talks artificial intelligence, angel investing and accidentally contributing to the Basel framework
Risk Awards 2021: new risk engine can run nearly a billion XVA calculations per second