Why your cost of funds rose faster than peers — and how to close the gap

Most CFO conversations about rising funding costs eventually reach the same place: the Fed moved, the market repriced, and every institution is dealing with the same pressure. That explanation is partly accurate. Rates did move.

What it leaves out is why two institutions with comparable balance sheets, operating in the same geography, can show a 60- to 80-basis-point variance in cost of funds through the same rate cycle. In fact, latest data from the FDIC Quarterly Banking Profile highlights just how sharply industry net interest margins fluctuate based on asset-size cohorts and lagging deposit pricing adjustments.

The broader market data does not explain that individual gap. Internal decisions do.

What peer data shows when you control for rate environment

Rate increases move the cost of funds upward across the industry. They do not move it evenly.

Strip out size and geography. Compare institutions with genuinely similar deposit compositions, loan-to-deposit ratios, and market footprints. The performance dispersion in funding efficiency that surfaces is difficult to attribute to market conditions. We have heard every version of that rationalization: larger institutions carry stronger brand recognition, smaller ones serve less competitive markets. None of it holds when two institutions operate on the same street corner and one carries a funding cost 40 basis points below the other. Geography has nothing left to explain.

What peer data surfaces in those comparisons is a discipline and data intelligence gap, not a market gap. The outperformers had isolated their true funding cost drivers long before rates moved: they knew which depositors were rate-sensitive, and they managed pricing by behavioral cohort rather than by product category.

Operating accounts received different treatment than surging corporate balances. Rate-sensitive wealth deposits received different treatment than long-standing core retail relationships. None of that requires sophisticated modeling. It requires a prior decision to look at the deposit base at the account and Household levels rather than the macro product line level.

By the time a CoF spike registers on the income statement, the deposit migration that caused it has already occurred. The P&L shows the consequence. The decision was made months earlier.

The credit signals that never reach the cost of funds conversation

There is a credit problem sitting inside most CoF conversations that does not get named until the damage is already visible.

In third-party loan reviews conducted to assess credit portfolio quality, a consistent share of Pass-rated credits carry early-stage deterioration signals the rating has not captured.

In our experience reviewing credit portfolios across institutions of all sizes, three patterns appear frequently enough to name.

• A DSCR that clears the policy floor on trailing twelve-month financials while the borrower's current run-rate, that is, the annualized pace of revenue and cash flow based on the most recent operating period, is materially lower. Rising input costs, floating-rate debt repricing, softening revenue mid-year. The file shows 1.25x. The actual coverage, calculated from current conditions, shows something different. The rating reflects the past. The cash flow reflects the present.
• Working capital stress that never surfaces in the credit file. Repayment is current. Accounts receivable aging is expanding and inventory is building. The borrower is paying the bank before paying vendors to protect the relationship. That means the bank is the last to know there is a problem.
• Guarantor burnout. The business has deteriorated, but the Pass rating holds because the guarantor is covering debt service with personal liquidity. That is a finite runway. When it runs out, the loan does not migrate from Pass to Special Mention. It goes directly to Substandard. The rating system never registered the deterioration in between.

Clean ratings are not the same as clean risk. The distance between those two statements is where the funding cost problem starts.

How stale risk ratings become a funding problem

The connection between stale credit ratings and rising funding cost runs through loan pricing.

When a loan is rated accurately, its yield includes a credit risk premium sufficient to absorb expected losses and cover the cost of the liabilities funding it. When the rating is stale, that premium is absent while the liability cost is not.

As market rates rise, the cost to fund a misrated asset increases while the asset's yield stays flat. The loan becomes a subsidized position, quietly dragging down overall balance sheet performance and absorbing margin that should be available to attract and retain low-cost core deposits.

Strategic damage compounds from there. When CoF spikes because the institution is funding deteriorating credits with expensive liabilities, NIM collapses. The response, almost universally, is pressure on the lending team to originate higher-yielding assets to restore the spread. In banking, higher yield means higher risk. And if the credit process that produced the mispriced portfolio is still intact and unchanged, the new vintage carries the same latent problems inside better-looking current financials. That cycle repeats.

Most institutions do not connect the two problems until they have run it at least twice. At that point the funding cost problem is visible in the income statement, but its root cause, stale ratings and subsidized assets accumulating on the balance sheet, is already a year or more old.

The two questions that narrow the gap

When a peer is outperforming on the cost of funds, the first diagnostic question is whether the gap is a mix problem or a pricing problem. These require different responses, and treating them as the same wastes capital.

Look at their call reports. Is the outperformance driven by a higher ratio of non-interest-bearing demand deposits to total deposits? That is a mix problem. The peer has more operating account relationships, which are structurally less rate-sensitive and less costly to hold. The response belongs in product strategy and treasury management, not rate adjustments.

If the peer is paying lower rates across the same product lines, that is a pricing discipline problem: fewer relationship managers offering above-sheet rates to retain accounts that would have stayed at the standard rate regardless. The response belongs in RM incentive structure and exception approval policy.

The same logic extends to loan pricing. Peer data showing that comparable institutions are extracting higher yields on equivalent risk profiles is the most effective tool we have found for moving those internal conversations. The market is already pricing that risk. The data makes that argument concrete.

Know where you stand before your regulator does

Peer benchmarking used only to confirm proximity to the industry average is a reporting exercise. The institutions that close the funding gap use peer data to identify exactly where they are underperforming and then hold the right internal conversations with it.

Closing the gap requires naming things that are uncomfortable: Relationship Manager incentives that reward volume over margin, exception cultures that have normalized above-sheet pricing, and pass-rated credits carrying deterioration that has not been acknowledged. Peer data does not fix any of those. What it does is remove the ability to claim the problem is not there.

The gap between an institution's cost of funds and its best peers is not a market condition. It is a record of decisions made internally, on pricing discipline, on credit accuracy, on how carefully anyone looked before the situation became unavoidable. Every basis point traces to a specific decision someone made. Those decisions can be found. They can be changed. The institutions that do that work before the exam cycle or the next rate move forces the conversation are the ones that come through without lasting franchise damage.