There is an increasing influence of machine learning in business applications, with many solutions already implemented and many more being explored. Since the global financial crisis, risk management in banks has gained more prominence, and there has been a constant focus around how risks are...

Risk diversification is the basis of insurance and investment. It is thus crucial to study the effects that could limit it. One of them is the existence of systemic risk that affects all of the policies at the same time. We introduce here a probabilistic approach to examine the consequences of...

The application of industry 4.0 in banking presents many challenges, with several operational risks related to downtime and timeout services due to system failures. One of the operational risk management steps is to estimate the value of the maximum potential losses. The purpose of this study is...

Risk taking is an inherent element of the banking business. Banks make conscious decisions regarding risk taking as they expect to make more return if they take more risk. The primary objective of this study is to empirically investigate the efficiency of Indian banks in generating return...

The aim of the research presented in the article was to analyse the legitimacy of the use of scoring models in banking activities, together with the assessment of the effectiveness of this tool in reducing the high value of the NPL ratio in Polish cooperative banks on the example of banks...

We develop an operational model of information contagion and show how it may be integrated into a mainstream, top-down, stress-testing framework to quantify systemic risk. The key transmission mechanism is a two-way interaction between the beliefs of secondary market investors and the...

This paper deals with stress tests for credit risk and shows how exploiting the discretion when setting up and implementing a model can drive the results of a quantitative stress test for default probabilities. For this purpose, we employ several variations of a CreditPortfolioView-style model...

We explore the Monte Carlo steps required to reduce the sampling error of the estimated 99.9% quantile within an acceptable threshold. Our research is of primary interest to practitioners working in the area of operational risk measurement, where the annual loss distribution cannot be...

This paper provides a critical analysis of the subadditivity axiom, which is the key condition for coherent risk measures. Contrary to the subadditivity assumption, bank mergers can create extra risk. We begin with an analysis how a merger affects depositors, junior or senior bank creditors, and...

This paper examines the bank liquidity risk while using a maturity mismatch indicator of loans and deposits (LTDm) during a specific period. Core banking activities that are based on the process of maturity transformation are the most exposed to liquidity risk. The financial crisis in...