Banks face a seemingly never-ending array of financial risks, as the pandemic showed. From health-related surprises to natural disasters to terrorist attacks, the unexpected circumstances that can affect the balance sheets of financial institutions highlight the importance of capital planning and asset/liability management (ALM). Indeed, having sufficient capital to handle the unexpected economic impacts allowed financial institutions to play a key role in the U.S. recovery to date.
“We’re not going to get rid of risk,” notes Dave Koch, Director of Advisory Services at Abrigo. “And we don’t want to get rid of risk. In fact, we make money by taking risk.” Good asset/liability management, he says, “is knowing how much risk do we take.”
Banks that continue to use their ALM models to manage risk and plan strategically during the projected recovery will generate sustainable earnings that allow them to maintain capital to grow, add shareholder return, or continue bringing value to their communities in other ways.
Which risks does ALM address?
An asset/liability management model captures three key types of risks facing financial institutions. These risks are measured by ALM solutions and managed by chief financial officers and other financial professionals as well as the institution’s asset/liability committee (ALCO). The three main risks in ALM are:
- Credit risk
- Liquidity risk
- Interest rate risk
To put it simply, Koch says, bankers can think of each of the above risks in these terms, respectively:
- What will happen if we don’t get paid like we expected?
- What will happen if we don’t have enough money to meet demands for loans or deposit withdrawals?
- What will happen to core earnings or value if rates change and stay there?
A closer look at each type of risk and the interplay among them reveals why ALM is more than a report required by regulators.
“Asset/liability management is a process – it’s how do I put loans and investments and borrowings together,” Koch says. “It’s about how to make decisions inside the bank to manage risk. And it takes everybody in the organization to bring together the ideas and execute on them to do it well.”
Credit risk and ALM
Loans are the largest source of credit risk for most banks. In addition to loans, other sources of credit risk on and off the balance sheet include:
- cash management services
- foreign exchange
- credit derivatives
- unfunded loan commitments
- letters of credit
- lines of credit
At its core, credit risk plays a critical role in balance sheet management because of the impact that the extension of credit and losses from poor credit have on a financial institution’s capital. Regulators expect banks to be able to forecast credit losses in order to evaluate both liquidity and interest rate risk. Financial institutions are already calculating the allowance for loan and lease losses (ALLL) or the allowance for credit losses (ACL) under the current expected credit loss model, or CECL. Using the same assumptions for prepayment schedules, loan loss forecasts, and loss severity forecasts in both the allowance calculation and the ALM model ensures a consistent approach for accurately projecting cash flow and the impact on capital under various scenarios.
Liquidity risk management and ALM
Liquidity risk management has taken on a completely different perspective over the last 18 months. Financial institutions with high loan-to-deposit ratios in 2019 saw tremendous asset growth in 2020 due to the influx of relief dollars, Paycheck Protection Program loan funds, and customers’ flight to safety early in the pandemic. Much of that money is sitting in lower-yielding cash and investments, and with weaker loan demand, corresponding levels of income have been insufficient to maintain spreads. As a result, institutional net interest margins have dropped to record lows.
From regulators’ standpoint, liquidity is defined as the capacity to readily meet cash and collateral obligations at a reasonable cost. Management and directors are expected to understand their institution's liquidity risk profiles relative to established limits, and to understand the potential impact of strategic and tactical decisions on liquidity.
ALM helps a financial institution estimate and plan for and meet liquidity demands over various periods without adversely affecting daily operations or financial performance. It projects how funding requirements change during routine times, as well as during times of stress.
Many community financial institutions identify, measure, and monitor liquidity risk through spreadsheets that compute existing balance-sheet liquidity positions, forward-looking source and use projections, and adverse scenario effects.
A key benefit of dynamic asset/liability management is that it allows banks to pivot when unexpected conditions arise and warrant a shift.
Dynamic ALM can help a financial institution decide where to put excess liquidity to work in a low-rate environment while still managing risk. It can help the bank make decisions about what rates are most advantageous for in its specific situation to offer on non-maturity deposit account products, rather than relying solely on what rates competitors are offering. This style of dynamic asset/liability management allows financial institutions to elude the risk of underperformance while avoiding the hazards of extreme increases in interest rates.
Interest rate risk and ALM
Interest rate risk, the risk most strongly associated with an ALM model, is generally associated with risk resulting from changes in interest rates.
Four common interest rate risks among community financial institutions:
- Repricing risk: Also known as mismatch risk, it’s the risk tied to assets and liabilities maturing at different times, which can crimp margins between interest income and interest expense.
- Basis risk: The risk that underlying rates used to price assets and liabilities change in a non-correlated manner, putting margins at risk of narrowing.
- Prepayment/extensions risks (also called option risk): Prepayment risk is the risk that asset repayments accelerate amid low interest rates, diminishing net interest income and creating the need to reinvest the repaid funds into lower-yielding assets. Extension risk, on the contrary, occurs in a rising rate environment when payoff rates lengthen, reducing the availability of funds to invest at higher yields.
- Yield curve risk: The risk that asset values or cash flows will be disproportionately affected by nonparallel changes in short- and long-term rates used to price assets.
Regulators expect a financial institution's interest rate risk measurement tools and techniques to be sufficient to quantify its risk exposure. Due to varying levels of risk and risk profile complexity, these tools and techniques can differ widely from institution to institution. As a result, some banks run ALM models themselves, others outsource the process entirely, and some use a hybrid approach of using outside ALM experts to help run a model in-house.
Many financial institutions assess the three major types of risk in siloes because of the way their data systems and models are constructed. But this approach ignores the benefits of an integrated model. By utilizing the same assumptions across the financial institution, executives harness consistent data that pleases examiners and auditors and generates meaningful reports for managing capital and growth.
Banks that actively manage their balance sheets using dynamic ALM will be able to achieve their desired growth and profitability while mitigating risks – even in the face of the unexpected.
By Mary Ellen Biery, Abrigo