Model risk and data -
a symbiosis

Poor data can lead to arbitrary large errors on model output.

Solving this problem requires both a technological solution as well as mathematical techniques.

Addressing data transformation from within the context of model risk allows for the early identification of value. 

"Model risk and data - a symbiosis" by Jos Gheerardyn, 2020

In this essay, we explain how applying model risk management principles on data transformation both lower risk and helps to extract more value.

At, we have created Chiron, an enterprise solution for Model Risk Management

This approach leads to both added value and cost reduction.

Key Points:

About The Author Co-Founder Jos Gheerardyn has built the first FinTech platform that uses AI for real-time model testing and validation on an enterprise-wide scale.

A zealous proponent of model risk governance & strategy, Jos is on a mission to  empower  risk managers and model validators with smarter tools to turn model risk into a business driver.