Integrating ALM into Enterprise Risk Management: Insights from Brian Hague

Asset/Liability Management (ALM) is, fundamentally, balance sheet risk management. It incorporates managing liquidity to ensure the ability to meet members’ borrowing and deposit withdrawal needs, as well as managing potential declines in the net worth ratio due to excessive deposit growth. It also incorporates managing interest rate risk, which includes changes in the market values of assets and liabilities that result from changing interest rates.

This discipline informs pricing, duration targets, the structuring of deposit maturities, loan retention vs. selling strategies, and other key decisions. However, while some ALM advisors have argued that ALM is “an optimal decision-making framework” for credit unions, ALM only provides a portion of the overall risk puzzle.

Consider these risk categories:

? Compliance risk

? Credit risk

? Information security risk

? Interest rate risk

? Liquidity risk

? Reputation risk

? Strategic risk

? Transaction (or operational) risk

Only two of these risk categories – interest rate risk and liquidity risk – are addressed by ALM. In a broader enterprise risk management (ERM) context, ALM is thus just a part of the overall picture.

The reality for credit unions in 2021 and beyond is that if we are going to remain relevant to our current and prospective members, we will likely have to assume more risk in the strategic, credit, and information security categories. In terms of strategic risk, we will have to continue to innovate, pursue scale, focus on talent acquisition and retention, reduce friction, and otherwise enhance the member experience. With respect to credit risk, we have to seek opportunities to make the loans that banks (and fintechs) may not wish to make and pursue new lending niches to benefit our members.

Finally, with respect to information security risk, we must strike a balance between member convenience and fraud risk. Money is a tool, and the easier we make it for members to access the toolbox, the easier it becomes for others to access it as well – especially since our members do not always keep the door locked.

If we assume relatively more strategic, credit, and information security risk, we will have to assume less risk in other areas to balance risk-taking across the enterprise. This is where ALM is lacking as a comprehensive decision-making framework, and where ERM is superior. However, ALM can be used in this balancing exercise, and ERM can in turn inform the ALM process.

How is ALM useful in balancing risk across the organization? By default, to a degree. The more credit risk we assume (in terms of increasing loans-to-shares), the more liquidity risk we may have to accept. Reputation risk may be difficult to reduce significantly, in the age of social media. And while transaction risk can be mitigated to a degree through scale, there are limits as to how much transaction risk can be eliminated.

That leaves interest rate risk as the primary lever we can use to balance overall risk-taking. Interest rate risk is relatively easy to manipulate through adjustments in pricing, duration, and other factors. Additionally, liquidity risk can be managed through borrowing, pricing, selling loans, etc. Thus, if our strategy is to aggressively grow loans, we can seek to minimize interest rate risk to offset the increased credit risk.

Conversely, if circumstances – field of membership, risk appetite, or economic conditions – dictate that we take less credit risk (i.e., accept lower loans-to-shares), we may need to assume more interest rate risk to maintain sufficient earnings to retain deposits and attract new members.

Assessing risk appetite by category can also help establish ALM risk tolerances. The appetite for interest rate and liquidity risk should be sufficient to allow manipulation to balance risk appetite across the organization. Furthermore, measuring risk-adjusted capital adequacy can also inform the capacity to assume additional risk, or the need to reduce risk. Again, interest rate risk can be used as a lever to strike the optimal balance.

A robust, quantitative ERM program can incorporate ALM data, and can also inform the ALM process to optimize balance sheet risk to fit within the overall risk-taking framework of the credit union, thus ERM intelligence and risk-taking strategies in other categories should drive the ALM strategy.

For more information about developing an ERM program, reviewing your existing ERM framework, assessing risk appetite, or developing a risk-adjusted capital adequacy to incorporate ERM intelligence, contact Stuart Girk, Chief Sales Officer at Rochdale Paragon at stuartgirk@rochdaleparagon.com or visit our website at www.RochdaleParagon.com .

Brian Hague, Senior Consultant, Rochdale Paragon Group