This study analyses the evolving landscape of digital risk management within the banking sector. Based on responses from a diverse group of Italian banks, the research sheds light on key trends and strategic priorities in risk management. By soliciting insights from professionals and...

Bank internal ratings of corporate clients are intended to quantify the expected likelihood of future borrower defaults. This paper develops a comprehensive framework for evaluating the quality of standard rating systems. We suggest a number of principles that ought to be met by 'good rating...

Credit risk measurement remains a critical field of top priority in banking finance, directly implicated in the recent global financial crisis. This paper examines the dynamic linkages between credit risk migration due to rating shifts and prevailing macroeconomic conditions, reflected in...

This paper empirically investigates the impact of internal ratings-based (IRB) approach on the risk weight under Basel II. Assuming increasing cost of raising new capital when the requirement constraint is violated, this paper estimates the difference of unknown risk weight parameters between...

Credit scoring models play a fundamental role in the risk management practice at most banks. They are used to quantify credit risk at counterparty or transaction level in the different phases of the credit cycle (e.g. application, behavioural, collection models). The credit score empowers users...

This paper proposes a set of indicators relevant for the risk characteristics of covered bonds, as based on granular publicly available transparency data. The indicators capture various aspects of cash flow risks related to the issuer, the cover pool and the payment structure. They offer unified...

The traditional loans pricing methods are usually based on risk measures of individual loan's characteristics without considering the correlation between the defaults of different loans and the contribution of individual loans to the entire loan portfolio. In this study, using account-level...

Artificial intelligence and machine learning have increasing influence on the financial sector, but also on economy as a whole. The impact of artificial intelligence and machine learning on banking risk management has become particularly interesting after the global financial crisis. The...

Credit risk is the most significant risk by impact for any bank and financial institution. Accurate credit risk assessment affects an organisation's balance sheet and income statement, since credit risk strategy determines pricing, and might even influence seemingly unrelated domains, e.g....

Данная часть завершает серию консультационных публикаций Деана Фантаццини на тему «Эконометрический анализ финансовых данных в задачах управления риском». В...