With the publication of the draft implementing technical standards on disclosure requirements for Interest Rate Risk in the Banking Book (IRRBB), the European Banking Authority (EBA) has taken another step in completing the regulatory IRRBB framework. The standards include both a qualitative and a quantitative template.
Managing interest rate and liquidity risk on savings and current accounts is a hot topic for banks in 2021. Risk, ALM, and treasury managers have to navigate changing regulatory requirements, changing withdrawal behavior and deposit pricing strategies due to COVID-19, and decreasing market rates.
Currently, for many organizations, operational resilience is at the top of the agenda of the Board and senior management. The COVID-19 pandemic clearly showed how vulnerable societies and organizations can be to unexpected and unforeseen events.
In the past 20 years, all industries have felt the impact of technological innovation. In some cases, this impact has been so great that disruption has occurred. A clear and often used example is the travel industry, where companies that did not exist 20 years ago, like AirBnB and Booking.com, are now major players.
Recent technological advances increase the possibility of using qualitative data in risk models to ensure a timelier recognition of threats. News articles, which can be seen as a type of unstructured data, are flooding the world every day. However, one can imagine the time it would take to manually process all this information. Recent developments in natural language processing (NLP) show some very promising results in automating that task by a computer. We assess the possibilities of these recent advances within credit risk management.