Noticias de la Cámara
Quantitative Risk – Decision-Making Models & The Use of Advanced Estimation Techniques | Grant Thornton
02/10/2023
Modelling techniques for bank risk management have always been an important element, with greater emphasis during the last two decades. Well established risk quantification methods are used by banking institutions within their capital calculation, provisioning, forecasting and stress testing, pricing and decision making.
The significant improvement in data processing and computational capabilities has resulted in an increasing industry trend to use more advanced techniques in risk identification and quantification. The trend has been strongest in the area of decision making (non-regulatory) models.
However, recent publications on regulatory models from the EBA (European Banking Authority) and PRA (Prudential Regulation Authority) are developing advanced method use cases. An increased focus on Artificial Intelligence (AI) and machine learning (ML) methods highlights the need for bank risk management to understand the capabilities of advanced modelling techniques.
Within Credit Risk, a role for ML models is becoming more and more relevant across several areas.
Read more here.
