What is the Model Development Lifecycle, or, What’s Baking at FRG?

by | Sep 5, 2024 | Model Development | 0 comments

Few people know that model development has a lifecycle (MDLC) just like software development.

What is the Model Development Lifecycle?

The model development lifecycle is a process that any modeler or risk manager should be aware of when models are being created and used. The fact that it’s a lifecycle underscores the idea that there is a beginning and an ending to a model. The lifecycle is divided into steps that not only provide key components of model development and maintenance but also indicates where potential sources of model risk can reside.

The MDLC consists of these high-level stages:

  1. Define Business Objective
  2. Define Model Objective
  3. Data Assessment
  4. Model Development
  5. Model Validation
  6. Deficiency Assessment
  7. Model Implementation
  8. Model Monitoring
  9. Scheduled Reviews
  10. Model Decommission

And this lifecycle is commonly represented as:

Chart shows the 10 steps that comprise the model development lifecycle

Because models underpin much of what happens in the financial risk management world, it’s important to understand what these stages represent regardless of one’s role in model development. At a minimum, awareness of these stages allows one to be familiar with potential sources of model risk.

We could explain the MDLC in an academic manner but…why? There are enough resources on the web to do that. So, we decided to do something different. We have decided to explain the MDLC through a story. We chose this format because stories are not only a means of communication, but they can also help us learn.

Uh…one other thing. We decided that the story wouldn’t be about financial risk modeling. After all, those who do financial risk modeling probably already know the MDLC. Instead, we wanted to appeal to more people. So, the story is about the creation of a cookie recipe. 

Stay tuned for the next post in this batch of blogs.

 Jonathan Leonardelli, FRM, Director of Business Analytics for the FRG, leads the group responsible for business analytics, statistical modeling and machine learning development, documentation, and training. He has more than 20 years’ experience in the area of financial risk.