Generative AI in Operational Risk Management: Harnessing the Future of Finance

#generativeai AI offers opportunities to enhance #operationalriskmanagement #orm through its ability to analyze #unstructureddata, #simulate #risk #scenarios, and #automate tasks. However, integrating this technology into ORM presents challenges, including #dataquality, #interpretability, #performance validation, #ethicalconsiderations, and organizational readiness.

Learning Inter‑Annual Flood Loss Risk Models from Historical Flood Insurance Claims

This research evaluates different regression models to predict #flood-induced #insuranceclaims, using the #us #national #floodinsurance Program (#nfip) dataset from 2000 to 2020. The models studied include #neuralnetworks (Conditional Generative Adversarial Networks), #decisiontrees (Extreme Gradient Boosting), and #kernel-based regressors (#gaussian Process). The study identifies key predictors for regression, highlighting factors that influence flood-related financial damages.

The Credit Suisse CoCo Wipeout: Facts, Misperceptions, and Lessons for Financial Regulation

The #creditsuisse #coco wipeout occurred when the #finma announced that the contingent convertible bonds that were part of the Credit Suisse Additional #tier1 (AT1) #regulatory capital had been written off.FINMA’s decision creates a healthy precedent: restoring #financialdiscipline in AT1 #bondmarkets by reminding investors that their investment is exposed to #creditrisk and that #duediligence is advised before investing in these products.

Correlation Pitfalls With ChatGPT: Would You Fall for Them?

Date : Tags : , ,
"This paper presents an intellectual exchange with #chatgpt, … , about correlation pitfalls in #riskmanagement. … Our findings indicate that ChatGPT possesses solid knowledge of basic and mostly non-technical aspects of the topic, but falls short in terms of the mathematical goring needed to avoid certain pitfalls or completely comprehend the underlying concepts."