Operational Risk Modeling in Financial Services

CHAPTER 1Creation of the Method

This first part of the book presents our experiences in operational risk modelling from a subjective point of view over the past 10 years.

1.1 FROM ARTIFICIAL INTELLIGENCE TO RISK MODELLING

We are engineers specialized in artificial intelligence. We have been working together for about 25 years, and early in our careers we spent a lot of time on applications of neural networks, Bayesian networks, and what was called data mining at this time. It was almost a generation before the current popularity of these techniques.

Back in the 1990s, few industries had the means to invest in artificial intelligence and data mining: mostly banking, finance, and the defense sector, as they had identified applications with important stakes. The defense usually conducts its own research, and so, quite naturally, we spent a lot of time working in research and development with banks and insurance companies, for applications such as credit rating, forecasting financial markets, and portfolio allocation. We were fortunate enough that the French Central Bank was our first client for this service, for several years. Thanks to a visionary managing director, the French Central Bank created in the early 1990s an AI team of more than 20 people working on applications ranging from natural language processing to credit scoring.

Our conclusion was mixed. Machine-learning techniques were generally not better than conventional linear techniques. This mediocre performance ...