Prediction of Auto Insurance Risk Based on t‑SNE Dimensionality Reduction

"... we develop a framework based on a combination of a neural network together with a dimensionality reduction technique t-SNE (t-distributed stochastic neighbour embedding)... The obtained results, which are based on real insurance data, reveal a clear contrast between the high and low risk policy holders, and indeed improve upon the actual risk estimation performed by the insurer."

A Text Analysis for Operational Risk Loss Descriptions

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"... we have applied text analysis methodologies to extract information from descriptions in the OpRisk database. After delicate tasks like data cleaning, text vectorization, and semantic adjustment, we apply methods of dimensionality reduction and several clustering models and algorithms to develop a comparison of their performances and weaknesses. Our results improve retrospective knowledge of loss events and enable to mitigate future risks."

Strategic Data Access Management

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"An employee may be attacked by a potentially sophisticated adversary whose goal is to steal all their data. Therefore, the firm trades off the efficiency benefit of the more permissive data access architecture with the adversarial risk it incurs. We characterize the firm's optimal data access architecture and investigate how it depends both on the adversarial environment and the firm's technology."

A Time Series Approach to Explainability for Neural Nets with Applications to Risk‑Management

"We here propose a novel XAI [eXplainable AI] technique for deep learning methods (DL) which preserves and exploits the natural time ordering of the data. Simple applications to financial data illustrate the potential of the new approach in the context of risk-management and fraud-detection."

Climate Risk, ESG Performance, and ESG Sentiment for U.S. Commercial Banks

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"Climate risk is positively associated with the environmental, social, and governance (ESG) performance of banks and negatively associated with the stakeholder ESG sentiment towards them. Negative sentiment due to such exposure is associated with worse financial performance and lower stock returns, but stronger ESG performance mitigates these adverse effects."

The ECB Single Supervisory Mechanism: Effects on Bank Performance and Capital Requirements

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"Under the Single Supervisory Mechanism (SSM) introduced in 2014, the European Central Bank directly supervises significant euro area banks, which hold about 82% of total banking assets. We find that this important supervisory change has positive effects on the return on assets and the return on risk-weighted assets of SSM banks without increasing the risk weights used to calculate regulatory capital."