Credit Analytics

Credit Analytics is a technology and service provider offering expertise in quantitative modelling and data analysis.

Our offerings

Automated decision models

Artificial intelligence solutions

In the past, quants focussed on decision support models meant to facilitate decisions taken by an enterprise. Today, real-time automated decision models are possible due to improvements in the implementation of Artificial intelligence and Machine Learning techniques.

At Credit Analytics, we build such type of models in an open source environment such as Python, ensuring full transparency of our solutions. Furthermore, we use the latest data visualisation techniques to improve modelling and data insight.

Advisory services

Leading experts

At Credit Analytics, we value the expertise and knowledge of specialists. Furthermore, we encourage our specialists to contribute to the international academic network.

At Credit Analytics, our efforts are intended to have an impact on both the academic and professional community.

Our latest developments

Probability of Default

Model Validation

We are glad to share our latest results on our research in PD model validation, and encourage sharing your thoughts after contemplating on our ideas.

Our goal is to inspire banks to implement more robust methods to evaluate the performance of their internal models.

Probability of Default

Model Development

Credit Analytics supports financial institutions in their pursuit of more accurate and less costly PD models, consistent across various internal applications. In this regard, due to the limitations imposed by the regulation and banks' existing internal frameworks, it can be challenging to address PD calibration issues in a satisfactory manner.

Have a look at our latest Risk.net publication, which offers a fresh perspective on calibrating time-varying TTC and PIT PD estimates on a rating grade level within the framework of the ASRF model.

Data visualisation is key for any organisation applying complex analytics.

Our view on using analytics

"Dans un monde toujours plus complexe, les scientifiques ont besoin des deux outils: des images aussi bien que des nombres, de la vision géométrique aussi bien que de la vision analytique."

Benoît Mandelbrot

In an ever-more complex world, Mandelbrot argues, scientists need both tools: image as well as number, the geometric view as well as the analytic. The two should work together. Visual geometry is like an experienced doctor's savvy in reading a patient's complexion, charts, and X-rays. Precise analysis is like the medical test results-the raw numbers of blood pressure and chemistry. "A good doctor looks at both, the pictures and the numbers. Science needs to work that way too," he says.