Corporate Credit Analysis and AI

Nyhet

Advancing the Rating System at a Central Bank

Inbunden, Engelska, 2026

2 029 kr

Kommande

This book presents cutting-edge methodologies, including AI techniques, for corporate credit analysis as developed for the in-house credit assessment system (ICAS) of Banca d’Italia. The first part illustrates the methods, applications and use cases of the existing system, that is employed to evaluate a large sample of Italian non-financial companies. The second part presents the rating systems in use at commercial banks and provides a benchmarking exercise of the latter systems against the ratings produced by ICAS. The third part presents new developments of the system, including the evaluation of climate transition risk, climate physical risk, social and governance factors, cyber risk, sentiment analysis. The book illustrates all state-of-the-art AI applications developed for ICAS, providing practical examples and empirical results.

Produktinformation

Utgivningsdatum2026-02-28
Mått155 x 235 x undefined mm
FormatInbunden
SpråkEngelska
SerieFinance for Professionals
FörlagSpringer Nature Switzerland AG
ISBN9783032134219

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Antonio Scalia is the Head of the Financial Risk Management Directorate at the Bank of Italy and a member of the ECB’s Risk Management Committee. He earned the Laurea in Economics with honours from LUISS University in Rome, the M.Sc. in Economics from the LSE and the Ph.D. in Finance from the London Business School. He has published many articles on leading international economic and finance journals on issues including monetary policy implementation and bank regulation, the sovereign bond market, and the effectiveness of foreign exchange intervention.

Corporate Credit Analysis and AI Applications. An Overview.- A SAFE Model for AI Risk Management.- The Statistical Model.- Macroeconomic Variables and Panel Estimation.- The Expert Assessment.- The Climate Risk Survey.- The Credit Risk of Italian Firms and Collateral.- IRB Systems.- The Credit Assessment of Large Firms.- IRB and ICAS: a Comparative Analysis.- Credit Risk Assessment with Stacked Machine Learning.- Physical-Risk Adjusted Credit Analysis.- Transition-Risk Adjusted Credit Analysis.- S and G Pillars in Credit Analysis with AI.- Sentiment Analysis with AI.- The Cyber Risk of Non-Financial Firms.