You don’t need a Ph.D to run bank risk models. But it helps. So A Dictionary of Finance got two superterrific scientists to explain

If you’re not already using the Vašíček approach to risk and interest-rate modelling, it’s time you did. At least it’s time someone explained what it is and how this and other very technical information relates to bank risk models.

It’s important because bank risk models are central to the assessment of financial risk by banks.

We admit that it’s complicated stuff. That’s why we asked two of the most expert experts yet to appear on A Dictionary of Finance podcast to explain it. Eva Ribarits, head of the European Investment Bank’s model development, has a doctorate in mathematics. Olivier Wantz, who heads the bank’s model maintenance and monitoring, is a doctor of theoretical physics.

Impressed? You certainly will be once you hear them explain how a bank assesses measures such as distance to default. “It’s also called probability of default,” says Eva. “This is what we want to model and forecast.”

Olivier explains how a bank has to recalibrate its models constantly to make sure that they’re really working. He also talks about ways that machine learning and fintech could affect future modelling in the banking business.

Let us know what you think of the episode on Twitter @EIBMatt or @AllarTankler.

Find our other episodes on iTunes, Acast or Spotify. We have several other episodes on different kinds of risk and risk management, so dive in.