PRMIA Institute Publications
Written by Sayonton Roy
This paper assesses reputational risk from a financial institution's perspective and lays down a basic framework through which reputational risk can be assessed and managed.
Written by Dr. Gary Nan Tie and Dr. Bob Mark
In this paper Dr. Gary Nan Tie and Dr. Bob Mark introduce kernel surrogates, which are mathematical functions that mimic AI behavior on a sample of its input-output for the purposes of understanding and explaining AI algorithm results.
Written by Nergiz Eryilmaz
This paper provides critical elements of a mature model risk management program and aims to help identify gaps in the existing and developing model risk management programs to bring the programs into mature stage.
Written by John Thackeray
This paper outlines and suggests a path for board engagement and participation in a meaningful and transparent fashion
Written by William W. Hahn, CFA
This paper examines how a financial institution might create a process and procedures that systematically identify climate risks and incorporate them into the existing financial risk management systems.
Written by Gerhard Mulder
This paper
explores how risk managers should be able to adapt in response to changes and new information.
Written by Dr. Gary Nan Tie, Dr. Bob Mark
This paper
explores how fairness is an important consideration in finding a parsimonious model solution.
Written by Dr. Edward Thomas Jones
The paper is aimed at financial professions, regulators, policymakers and researchers in the area of banking who seek to understand where this new field of research currently is and what evolution is to be expected.
Written by Hersh Shefrin
This paper Explainable AI as a Tool for Risk Managers, focuses on subtleties associated with the black box character of machine learning algorithms and techniques to infer the nature of what is going on inside those black boxes.
Written by Thibaud de Barmon and Simon Tweddle
In this paper, we explore the latest developments in operational resilience, from regulatory updates to latest best practices.
Written by Gary Nan Tie and Dr. Bob Mark
In this paper, we systematically explore how to understand and mitigate model risk. Guidance is given on finding parsimonious models within a spectrum that neither under fit nor overfit data in order to rationally and consistently make informed business decisions.
Written by Oscar McCarthy, Ken Radigan, and Alexandru Voicu
In this paper, the PRMIA Institute provides Risk Leaders with an overview of the critical industry changes associated with different climate change scenarios, insight into the key risks, and a discussion of how these risks can be managed.
Written by Kenneth Chen and David M. Rowe
In our "Much Needed Credit Insights" we discuss a multi-component, granular and forward-looking framework that is practically applicable in today's market. In order to achieve this, financial institutions require advanced support from experts in data, technology and analytics, and we lay out the skills required for implementation.