Asset Liability
Management (ALM)
ALM Model Validation
Why Choose Us
We simply want what is best for our client. We offer independent fee-based advice, so we do not have financial bias as to the solution(s) an organization opts to implement. We recognize that financial institutions can meet their liquidity needs in different ways and we provide customized solutions to meet their objectives.
We believe effective liquidity stress testing requires a thorough understanding of our client’s balance sheet, business philosophies, operating procedures, and tolerance for balance sheet risk. We also believe that a thorough understanding of our client’s non-maturity deposits is a critical part of liquidity stress testing because they comprise 85% of the financial institution industry’s total deposits.
We believe that a review of ALM modeling should be comprehensive and performed in the context of our client’s policies and procedures and recent financial performance. Our model validation begins with a thorough review of our client’s ALM policies and procedures to better understand our client’s goals, objectives, and risk tolerances. Next, we review our client’s financial statements for at least the past 10 years to understand the institution’s recent financial performance.
After gaining the appropriate context for our review and recommendations, we begin our thorough review of our client’s existing ALM model and Asset Liability Committee (ALCO) reports.
Our Approach
As part of our work, we obtain the data and assumption set inputs (prepayments, pricing lags, pricing betas, etc.) used to produce our client’s most recent ALM reporting package. We input the data and assumptions into the ZM Desk Model to ensure our client’s model is producing expected category-level outputs consistent with the category-level inputs. Next, we analyze our client’s data aggregations and make recommendations for improvement. We then benchmark our client’s input assumptions to industry standards as well as our client’s experience, including the results from back-testing. As a final step, we make overall recommendations regarding our client’s interest rate risk profile, ALM modeling, and strategies designed to mitigate risk, all in the context of our client’s policies and procedures and actual financial results.
FEATURED
Best Practices in ALM [WW University PowerPoint]
This September 2016 PowerPoint shows how measuring interest rate and credit risks on an integrated basis can lead to more informed loan pricing and better decisions regarding asset mix and the resulting capital at risk.
WHAT OUR CLIENTS SAY
“I feel like I know something about ALM. I started my career analyzing bonds. I had the benefit of making some investment mistakes early. I worked for an ALM software […]”
– Matt Wohlers, CFA, Executive Vice President & Chief Financial Officer, Blackhawk Community Credit Union – Janesville, WI