A Dynamical Model for Operational Risk in Banks

TL;DR

This paper introduces a dynamical model for operational risk in banks that accounts for spontaneous and interaction-driven losses, with potential for parameter estimation and effective forecasting.

Contribution

It presents an exactly solvable dynamical model incorporating bank efforts and interactions, advancing risk modeling capabilities.

Findings

Model can be exactly solved under certain conditions

Forecasting power of the model is remarkably effective

Parameters can be estimated from real data

Abstract

Operational risk is the risk relative to monetary losses caused by failures of bank internal processes due to heterogeneous causes. A dynamical model including both spontaneous generation of losses and generation via interactions between different processes is presented; the efforts made by the bank to avoid the occurrence of losses is also taken into account. Under certain hypotheses, the model can be exactly solved and, in principle, the solution can be exploited to estimate most of the model parameters from real data. The forecasting power of the model is also investigated and proved to be surprisingly remarkable.