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Reducing Model Risk by Honing Code

Reducing Model Risk by Honing Code

by Jonathan Leonardelli, FRM | Sep 24, 2025 | Model Development

In this blog of FRG’s blog series on coding best practices to reduce model risk during model development, we focus on the Honed element of MATHS. To hone a process, skill, or ability, means to make it “perfect or completely suitable for its purpose.” That is the focus...
Model Risk Management Through Archiving

Model Risk Management Through Archiving

by Jonathan Leonardelli, FRM | Sep 10, 2025 | Model Development

This blog series explores how applying a set of coding best practices can help reduce errors during model development. We’ve captured these practices in the acronym MATHS: Modularized, Archived, Tested, Honed, and Standardized. This post focuses on the Archived...
Reducing Model Risk through Modular Programming

Reducing Model Risk through Modular Programming

by Jonathan Leonardelli, FRM | Sep 3, 2025 | Model Development

This blog series explores how applying a set of coding best practices can help reduce errors during model development. We’ve captured these practices in the acronym MATHS: Modularized, Archived, Tested, Honed, and Standardized. Each post will dive into one element of...
The Model Development Lifecycle (MDLC): Data Assessment

The Model Development Lifecycle (MDLC): Data Assessment

by Jonathan Leonardelli, FRM | Sep 26, 2024 | Model Development

This blog series explores the stages of the Model Development Lifecycle so that you understand the components of model development and maintenance as well as where potential sources of model risk can reside. Read the first post here for an introduction to the series...

CECL Preparation: How Embracing SR 11-7 Guidelines Can Support the CECL Process

by Samantha Zerger | Oct 15, 2019 | CECL

The Board of Governors of the Federal Reserve System’s SR 11-7 supervisory guidance (2011) provides an effective model risk management framework for financial institutions (FI’s). SR 11-7 covers everything from the definition of a model to the robust...
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