🧠 Why Do Banks Obsess Over Interest Rate Risk?
Imagine a bank as a giant sandwich shop. The bread (liabilities) is what customers give you $($like deposits$)$, and the filling $($assets$)$ is what you use it for $($like giving loans$)$. The flavor of your sandwich $($i.e., profitability$)$ depends on the spread between what you pay for the bread and what you earn from the fillings.
This “spread” is formally called Net Interest Income (NII), and when you divide that by your earning assets, you get your Net Interest Margin (NIM): NIM=Interest Income−Interest ExpenseEarning Assets $\text{NIM} = \frac{\text{Interest Income} – \text{Interest Expense}}{\text{Earning Assets}}$
If interest rates go up or down, this whole sandwich could get soggy or stale — which is why banks obsess over Asset-Liability Management $($ALM$)$. But what is ALM, really?
🧮 What Is Asset-Liability Management?
Asset-Liability Management $($ALM$)$ is like managing a seesaw: if the weights (interest rates) on either side shift, you need to rebalance — or the whole thing tips over. This job is handled by the Asset-Liability Committee $($ALCO$)$, a group of senior managers from treasury, lending, and risk.
ALM’s job includes:
- Matching the volume and maturity of loans and deposits.
- Deciding pricing policies $($what to charge for loans and what to pay on deposits$)$.
- Managing interest rate risk, reinvestment risk, and price risk.
But wait… what exactly is interest rate risk, and how does it affect NIM?
⚖️ What Is Interest Rate Risk?
Interest Rate Risk is the potential hit a bank takes when interest rates move.
- If rates rise, and the bank’s assets reprice slowly but liabilities reprice quickly, the cost of funds jumps up, while income lags behind. Ouch!
- If rates fall, the opposite happens — the bank may benefit if its assets are fixed and liabilities get cheaper.
There are two flavors of this risk:
- Reinvestment Risk: You earned interest — now what rate can you reinvest it at?
- Price Risk: Your fixed-income assets lose value if rates rise.
So, how do banks measure and manage this risk?
📏 Measuring Interest Sensitivity with the IS Gap
Enter the superhero of this story: the Interest-Sensitive Gap (IS Gap). $\text{IS Gap} = \text{IS Assets} – \text{IS Liabilities}$
Interest-Sensitive (IS) Assets: Assets that will reprice within a time bucket.
Interest-Sensitive Liabilities: Liabilities that will reprice in the same bucket.
Banks divide their balance sheets into time buckets $($like 0–30 days, 31–90 days, etc.$)$, and for each one, calculate the IS gap.
Let’s look at some examples of IS items:
| IS Assets $($Repriceable$)$ | IS Liabilities $($Repriceable$)$ |
|---|---|
| Short-term securities | Fed funds, repo, CDs |
| Short-term loans | Savings accounts |
| Variable-rate loans | MMDAs |
But how do these gaps influence a bank’s performance?
🔍 Impact of IS Gap on NII and NIM
If the IS gap is:
- Positive: More assets than liabilities reprice → an increase in interest rates boosts NII and NIM.
- Negative: More liabilities than assets reprice → an increase in interest rates hurts NII and NIM.
- Zero: Interest rate changes have little impact on NII.
Let’s use a simplified equation: $\Delta \text{NII} = \Delta \text{Rate} \times \text{IS Gap}$
Banks also use the Interest Sensitivity Ratio (ISR): ${ISR} = \frac{\text{IS Assets}}{\text{IS Liabilities}}$
- ISR \$>\$ 1 → Asset Sensitive
- ISR \$<\$ 1 → Liability Sensitive
So… how do we actually calculate and apply all this stuff?
🧪 Let’s Analyze a Real Example (Figures Explained)
Take this repricing table (see image). The assets and liabilities are grouped by time buckets: 0–30 days, 31–90 days, 91–365 days, and over 1 year.
Let’s dissect the first bucket:
- Repricing Assets $($0–30 Days$)$ = $1,200$
- Repricing Liabilities = $1,900$
- IS Gap = $1,200 – 1,900 = -700$
- ISR = $1,200 / 1,900 = 63
The negative IS gap means the bank is liability sensitive in the short term.
What does this sensitivity do to your bottom line?
💰 Income Impact: Calculating NII and NIM
Using the assumed yields $($e.g., 6% on IS assets, 3% on IS liabilities$)$, the bank calculates interest income and expenses.
One-Month Bucket Example:
- Total Income = $285.50$
- Total Expense = $151$
- NII = $134.50$
- NIM = $134.50 / 4,250 = 3.17\%$
Now imagine interest rates increase by 1%. For a −700 IS gap: $\Delta \text{NII} = 0.01 \times (-700) = -\$7$
New NII = $134.50 – 7 = 127.50$
That’s how sensitive NII can be!
But what if the bank expects rates to rise? Shouldn’t it prepare itself?
🧰 Strategic Takeaway: Hedge or Position?
Banks have two choices:
- Hedge the IS gap: Neutralize exposure using swaps or futures.
- Position for profit: If expecting rates to rise, increase asset sensitivity. If expecting a fall, go liability sensitive.
But here’s the catch: not all rates move in lockstep. The yield curve can twist, steepen, or invert — and each impacts buckets differently.
So banks model scenarios using complex ALM software, but the basic idea remains: manage your gap, or your margin will manage you.
🧩 Summary: What Did We Build?
- ALM integrates assets and liabilities to manage interest rate risk.
- Interest-Sensitive Gap (IS Gap) is the heart of gap management.
- Repricing Buckets and ISR help identify sensitivity.
- NII and NIM are directly impacted by IS gap.
- Banks adjust balance sheet structure or hedge with derivatives to manage this exposure.
Next Question:
If managing gaps helps with income volatility, how do banks address equity volatility due to changes in asset values?
➡️ Time to dive into Duration Gap Analysis and Economic Value of Equity (EVE) sen