PRMIA Learning Catalog

Climate Scenario Analysis

New course! This course is designed to give participants the tools to build their own climate scenario analysis framework and provide some practical tools and templates to deliver a climate scenario set and associated board level report.

 

Where: Self-Study

How to Respond to Climate Change: Transition Risk

New course! Climate change not only impacts organizations through extreme wheather events and physical impacts, it bites via so-called transition risks as well. Regulators’, technologists’, and consumers’ response to climate can hit your organization hard. This course provides a basic level understanding of Transition Risk to help you prevent that "bite."

Where: Self-Study

MLARM Certificate Exam Prep

The Market, Liquidity, and Asset Liability Risk Management self-study course is intended to prepare individuals for the MLARM certificate exam.




Where: Self-Study

Fundamentals of Market Risk Management

In this fundamentals course, you will become familiar with market risk and its associated terminology. The lessons explain and give examples of market risk with its measurement and risk mitigation methods. Additionally, you can further explore this type of risk and experience first-hand the practical use of risk measurement and mitigation methods through hands-on exercises.

Where: Self-Study

Fundamentals of Credit Risk Management

In this fundamentals course, you will become familiar with credit risk and its associated terminology. The lessons explain and give examples of credit risk with its measurement and risk mitigation methods. Additionally, you can further explore this type of risk and experience first-hand the practical use of risk measurement and mitigation methods through hands-on exercises.

Where: Self-Study

Fundamentals of Liquidity Risk Management

In this fundamentals course, you will become familiar with liquidity risk and its associated terminology. The lessons explain and give examples of liquidity risk with its measurement and risk mitigation methods. Additionally, you can further explore this type of risk and experience first-hand the practical use of risk measurement and mitigation methods through hands-on exercises.

Where: Self-Study

Fundamentals of Interconnected Risk Management

In this fundamentals course, you will become familiar with interconnected risk and its associated terminology. The lessons explain and give examples of interconnected risk with its measurement and risk mitigation methods. Additionally, you can further explore this type of risk and experience first-hand the practical use of risk measurement and mitigation methods through hands-on exercises.

Where: Self-Study

Introduction to Risk and Regulation for International Banks

Gain a high-level understanding of banking regulation, Basel I, II, and III. This course is an excellent complement to Fundamentals of Financial Risk Management.
Introductory topics.


Where: Self-Study

Capital Requirements Calculations (Credit, Market & Op Risk)

Learn the regulatory landscape of Credit, Market, and Operational Risk, as well as the Supervisory Review. This course is an excellent complement to Fundamentals of Financial Risk Management.
Intermediate topics.

Where: Self-Study

Complex Capital Risk Calculations

Learn about advanced regulatory topics such as Interest Rate Risk in the Banking Book, Total Loss Absorbing Capacity, Counterparty Credit Risk, and Credit Valuation Adjustment.


Where: Self-Study

Market Risk Management under Basel III and FRTB

Basel III framework for market risk, also known as the Fundamental Review of the Trading Book or FRTB, represents a pivotal change in the way banks’ trading businesses will be capitalized, regulated, and managed. As banks intensify their implementation efforts and deepen their knowledge of FRTB, this course provides best practices for tackling the myriad of challenges and implementation deadlines. 


Where: Self-Study

Practice Test Question Banks for the PRM 1 and 2 exam programs

Candidates studying for the Professional Risk Manager (PRM) Designation program can self-assess their readiness for the PRM Exam 1 and 2 using the PRMIA banks of practice test questions. 30 days of access for each bank.

Where: Self-Study

Machine Learning and AI Certificate Program

As the complexity of ML models grow, risks grow & we need learn how to address risks in Machine learning models pragmatically. Join PRMIA's partner, QuantUniversity, for the industry's first Machine Learning and AI Risk Certificate program geared towards the financial services industry.

Where: Self-Study

Just Enough Python For Data Science - Finance Edition

Learn key concepts needed to write and understand Python. Rather than bogging you with all the syntactical details, we focus on the key elements and packages giving you just enough orientation to start your Data Science journey in Python.


Where: Self-Study

Machine Learning and AI for Financial Professionals

The use of data science and machine learning in the investment industry is increasing. Financial firms are using artificial intelligence (AI) and machine learning to augment traditional investment decision making. In this course, we aim to bring clarity on how AI and machine learning are revolutionizing financial services. Rather than just showing how to write code or run experiments in Python, we will provide an intuitive understanding to machine learning with just enough mathematics and basic statistics.

Where: Self-Study

Model Risk Management for Machine Learning Models

The financial industry has been adopting AI and machine learning at a rapid pace. Alternative datasets including text analytics, cloud computing, and algorithmic trading are game changers for many firms exploring novel modeling methods to augment their traditional investment and decision workflows. In this course, we aim to bring clarity to some of the model risk management and validation challenges with data science and machine learning models in the enterprise.


Where: Self-Study

Risk and ML Models: Stress, Scenario Testing and Evaluation

Institutions have ramped up the adoption of ML models and are seeing significant benefits through the growing portfolios of ML based decision making models. While the interest is huge, the challenges of comprehensively testing and evaluating ML models remain. By the end of the course, participants will have a clear idea of the challenges, best practices, and pragmatic tools that can be used to address risks in machine learning models.


Where: Self-Study

Algorithmic Auditing for ML and AI Models

Learn about the emerging and important area of algorithmic auditing. As your organization adopts machine learning and AI products, now is the time to incorporate formal ethics reviews, and model validation exercises within your ML & AI strategy.



Where: Self-Study

Risk Type Compass

The Risk Type Compass personality assessment focuses on differences in the way individuals perceive, react to and manage risk, as well as how they make decisions. Based on extensive global psychological research, it places individuals into one of eight distinctive Risk Types, providing insights that have important implications for individuals, teams and the organization.

Where: Online