Nos derniers articles

#financialinstitutions are increasingly using #machinelearningalgorithms for credit risk mgmt., #fraudprevention, and #aml. This paper presents robust evidence of using logistic regression, linear discriminant analysis, and neural networks for accurately predicting and classifying financial transactions for Volcker Rule #compliance. It provides a scalable minimum viable product to automate #controls testing.

We provide a #cyberrisk definition and classification scheme for #riskmanagement purposes, to be used as a data collection template for #financialinstitutions.

This paper addresses the challenges associated with the adoption of #machinelearning (#ml) in #financialinstitutions. While ML models offer high predictive accuracy, their lack of explainability, robustness, and fairness raises concerns about their trustworthiness. Furthermore, proposed #regulations require high-risk #ai systems to meet specific #requirements. To address these gaps, the paper introduces the Key AI Risk Indicators (KAIRI) framework, tailored to the #financialservices industry. The framework maps #regulatoryrequirements from the #euaiact to four measurable principles (Sustainability, Accuracy, Fairness, Explainability). For each principle, a set of statistical metrics is proposed to #measure, #manage, and #mitigate #airisks in #finance.

This working paper analyzes whether the #boe has a legal obligation to adjust #capitalrequirements for #financialinstitutions in response to the #climatecrisis. The paper argues that the BoE, as a public authority, must abide by the #humanrights obligations set out in the European Convention on Human Rights, which are deeply intertwined with climate concerns.

It highlights the increasing #regulatory focus on #climaterisk faced by #canada's #banks, both domestically through the #osfi and globally through the adoption of guidelines proposed by the #tcfd. As regulators seek to impose more #monitoring, #disclosure, and mitigation obligations on #financialinstitutions, the article raises whether banks' #capitalrequirements should be increased to reflect the #risks associated with #climatechange.

The current #canadian regime, which draws on the #basel #operationalrisk framework, is not equipped to handle the unique challenges of #cyberrisk. Cyber incidents differ from traditional operational disruptions in terms of their dynamism and impact, and traditional risk-based #supervision is not suitable for the rapidly changing cyber profile of #regulated #financialinstitutions.services for all communities, especially those most impacted by climate change."

"... this paper argues that recent #eu#regulatory reform to #corporategovernance, as a means to improve #financialstability is a large-scale intellectual fallacy. Absent EU-wide structural reform to control #risktaking in large and complex #financialinstitutions, the stability of the EU #bankingsector will remain compromised. Smaller and less interconnected #banks will both improve bank corporate governance and create a safer and more stable #financialsector."

This paper proposes a #credit#portfolio approach for evaluating #systemicrisk and attributing it across #financialinstitutions. The proposed model can be estimated from high-frequency credit default swap (#cds) data and captures risks from publicly traded #banks, privately held institutions, and coöperative banks. The approach overcomes limitations of earlier studies by accounting for correlated losses between institutions and also offers a modeling extension to account for #fattails and #skewness of #assetreturns. The model is applied to a universe of banks in #europe, highlighting discrepancies between the #capitaldequacy of the largest contributors to systemic risk and less systemically important banks.

This #china Wuhan University study proposes a Financial Event Evolution Knowledge Graph (FEEKG) to identify key risk sources by event association and clarify the path of #riskevents. The FEEKG has a multi-layer structure of "entity-event-risk" and includes a subgraph of about 112,000 entities and 78,500 relationships, an event evolution subgraph, and a dynamic evolution probability subgraph of topic risk events and risk types. The study analyzes the characters and rules of entity correlation, event evolution, and #risktransmission based on FEEKG and provides a new perspective for enterprises and #financialinstitutions to find the root of risks and formulate an effective #riskmanagement decision in time.

"The article provides a short overview of methods for constructing mathematical models in the form of Bayesian Networks for modeling operational risks under conditions of uncertainty. Let’s provide the sequence of actions necessary for creating a model in the form of the network, methods for computing a probabilistic output in BN, and give examples of using the tool to solve practical problems of operational financial risk estimation."