From volatility to visibility – How credit unions can strengthen balance sheet resilience through better data and risk management

Daniel Ahn, CEO and Co-founder, Delfi Labs

Today’s credit unions are navigating a complex financial landscape. After years of relatively low and stable interest rates, volatility has returned and with greater force, reshaping liquidity conditions, heightening asset‑liability mismatches and complicating balance‑sheet decisions. A McKinsey study suggested that institutions are facing a “new era of volatility,” noting that many lack the right tools and modern playbook to manage these conditions effectively in this new environment.

For credit unions, these pressures are magnified even more. While they face the same risks as their larger competitors, they do so with far fewer resources, smaller teams and limited access to the in-depth, quantitative expertise common to Wall Street banks. And yet, the expectations are the same—safeguard member assets, maintain stability and deliver competitive value in the face of an uncertain and evolving market.

To succeed and thrive in this new environment, credit unions must take a modern approach to their balance‑sheet and data management, one that not only equips them with the right tools and insights to respond to volatility but also allows them to benefit strategically.

Historically for many credit union leaders, balance-sheet risk management has ranked lower on their priority lists, often regarded as more of a compliance exercise than a strategic driver. However, recent events like the high‑profile failures of Silicon Valley Bank and First Republic Bank have revealed how quickly balance‑sheet misalignment can become a critical, even existential threat.

Today, vulnerabilities for credit unions lie in four key areas.

Credit unions often rely on a mix of legacy asset-liability management (ALM) systems, spreadsheet modeling and/or outsourced consultants. Unfortunately, these approaches can be slow, static and insufficient for today’s fast-shifting rate movements. When results take days or even weeks, decision-makers are left reacting to yesterday’s conditions rather than the risks emerging right now.

The data needed for strategic decision-making—granular, instrument-level data across the balance sheet—often live across siloed systems. These include detailed loan and deposit data from core systems, security-level investment portfolio attributes, funding and liquidity positions, and capital metrics—which all need to be integrated with market and pricing data, behavioral assumptions (e.g., deposit betas and loan prepayments), and internal policy and regulatory limits to enable forward-looking scenario analysis and strategic optimization.

Traditionally, credit unions store these data in different places, which makes it challenging to quickly generate a cohesive, clear picture and understanding of the balance sheet. In volatile markets especially, incomplete or outdated views of data can lead to decisions that create poor outcomes, or worse, unintended risk.

Many credit unions revert to common risk management scenarios like parallel shocks or simplistic stress tests, even though real‑world rate movements behave nothing like linear models. Without the ability to test realistic scenarios (non‑parallel shifts, curve twists, rapid liquidity drains), it is easy for organizations to underestimate the true sensitivity of their earnings and capital.

Additionally, running multiple what-if strategic decisions against the balance sheet, such as the hypothetical effects of a potential loan participation, a security purchase or a change in funding strategy, can be slow and onerous, especially in situations where real-time insights are required. For example, when a broker approaches a credit union with an investment opportunity, many credit unions struggle to understand how that opportunity reshapes their unique balance sheet today.

While large national banks can employ whole teams of quants, risk modelers and market strategists, most credit unions operate with much leaner lending, finance and ALM teams. Because of this, CU leaders must absorb complexity quickly, often without the analytical power needed for timely and data‑driven decisions, which can cause missed opportunities and poorer outcomes.

As Scott Daukas, Principal of One Washington Financial, has stated, “Credit unions face the same balance sheet challenges as their largest competitors, but they manage them with much smaller teams.”

While volatility creates vulnerabilities, it also offers the chance to capture margin, improve pricing and strengthen long‑term resilience, but only if credit unions can interpret that risk effectively and act quickly and confidently.

Strong balance‑sheet management can help credit unions do this in several ways, starting with identifying mispriced risks and opportunities in their loans or investments and revealing whether they are asset‑sensitive or liability‑sensitive in changing conditions. It can also help to surface earnings opportunities hidden in the shape of the yield curve, in inefficient balance sheet structures, in underperforming investment portfolios or in strategic hedging opportunities. This will ultimately help enhance member value through better pricing, products and returns.

In other words, managing volatility well can become a major competitive advantage, especially for those credit unions positioned closest to the communities they serve.

Better, more modern balance-sheet management requires a shift from backward-looking reporting cycles to real-time visibility and forward-planning. Credit unions should prioritize continuous, on-demand analytics that replace lagging ALM reports and static outputs, giving leadership a true, real-time view of their exposures.

At the same time, credit unions should expand beyond traditional parallel rate shocks to incorporate more realistic and probability-based scenario modeling and what-if analytics. This will help credit unions anticipate how market changes affect overall stability and give them a clearer picture of how today’s decisions could impact future performance. This shift requires stronger data integration, breaking down silos across lending, deposits, treasury and investments, and creating unified data pipelines so that all stakeholders are working from the same trusted foundation.

As both data quality and speed improve, the role of asset-liability committees (ALCOs) will naturally become more strategic. Rather than only reviewing historical results, ALCOs transform into a forward-looking hub where leaders evaluate the future impact of loans, deposit strategies and investment decisions through a risk-return lens, allowing credit unions to stay ahead of change rather than just reacting to it.

Underpinning all of this is a shift from treating risk management not just as a regulatory requirement but as a strategic lever for performance. Credit unions that embrace this mindset can unlock the ability to make faster, more confident decisions, capitalize on timely and relevant opportunities while strengthening member value even in periods of heightened volatility.

As one credit union CEO stated, “We need to lift our organization out of the dark ages, fix our inverted balance sheet structure and improve our investment portfolio risk-adjusted returns.” These balance sheet performance improvements are not just fundamental business goals, but also obligations to credit union members.

Credit unions exist to serve their members, and strong balance‑sheet intelligence and risk management are central to this mission. Every basis point gained through better decisions or smarter risk management flows directly back into member value.

The gap between insight and action is continuing to close across the financial industry. Modern balance‑sheet strategies, powered by real‑time data and deeper analytics, allow credit unions to strengthen resilience, reduce unnecessary risk and capture more opportunities while improving member offerings and competing effectively regardless of size.

In a financial world that is defined by uncertainty, the credit unions that thrive will be those that transform volatility into strategic clarity.

Daniel Ahn is the CEO and Co-founder of Delfi, a fintech company specializing in AI-powered financial risk management and portfolio optimization.