What Is the Fallout Rate in Mortgage Lending and How Is It Tracked?

Mortgage lending involves various risks, and one key metric lenders monitor is the fallout rate—the percentage of loan applications that do not close due to borrower decisions, market conditions, or other factors. A high fallout rate affects pipeline management and financial planning.

Concept in Mortgage Lending

Fallout rate influences how lenders manage loan pipelines and financial expectations. When a borrower applies for a mortgage, the lender allocates resources for processing, underwriting, and funding. If the loan does not close, these efforts become sunk costs, reducing profitability and efficiency.

Lenders use fallout data to forecast loan volume and manage liquidity. Since they often fund loans using warehouse lines of credit before selling them to investors, inaccurate estimates of closed loans can lead to excess borrowing costs or liquidity shortages. A consistently high fallout rate may indicate inefficiencies in borrower qualification, pricing strategies, or market positioning.

Borrower behavior plays a major role. Some applicants withdraw due to job loss or credit score declines, while others switch lenders for better terms. External factors, such as home price fluctuations or economic uncertainty, also contribute.

Calculation Components

Fallout rate is calculated by comparing the number of loan applications that fail to close against total applications received within a given period:

Fallout Rate (%) = (Number of Loans That Did Not Close / Total Loan Applications) × 100

Lenders track fallout monthly, quarterly, or annually. Shorter periods allow quicker adjustments, while longer periods provide trend analysis.

Loan type affects fallout. Refinances typically have higher fallout than purchase loans, as borrowers often apply with multiple lenders to find the best deal. Government-backed loans, such as FHA and VA mortgages, may show different fallout patterns due to stricter eligibility requirements and longer processing times.

Creditworthiness and approval conditions also matter. Applications with conditional approvals—requiring additional documentation or credit improvements—are more likely to fall through than fully approved loans. Borrowers pre-approved but later failing underwriting conditions contribute to fallout, making it essential for lenders to refine pre-qualification processes.

Relationship to Interest Rate Locks

Interest rate locks influence fallout by affecting borrower commitment. A rate lock secures a specific interest rate for a set period—typically 30, 45, or 60 days—shielding borrowers from market fluctuations. If rates drop after the lock, some borrowers abandon their original lender for a lower rate elsewhere, increasing fallout. If rates rise, borrowers are more likely to proceed, reducing fallout risk.

Lenders hedge against fallout risk using secondary market instruments like mortgage-backed securities (MBS) and forward commitments. Fallout disrupts these hedging strategies since locked loans that do not fund leave lenders exposed to market shifts. To counteract this, lenders apply hedge ratios based on historical fallout trends. For example, if a lender expects a 25% fallout rate, they may hedge only 75% of their locked pipeline to avoid unnecessary costs.

Rate renegotiations complicate fallout management. Some lenders allow borrowers to adjust their locked rate if market conditions improve, reducing the incentive to switch lenders. While this helps retain borrowers, it affects profitability, as lenders may have to absorb the cost of the lower rate. Some institutions charge fees for rate renegotiations to discourage excessive re-locking.

How Lenders Track Fallout

Lenders use internal reporting systems and mortgage loan origination software (LOS) to monitor fallout trends across loan types, borrower profiles, and geographic regions. These systems track each stage of the application process, flagging loans that drop off before closing. Categorizing fallout by reason—such as borrower withdrawals, underwriting denials, or documentation issues—helps lenders identify inefficiencies.

Historical fallout data is incorporated into predictive models to estimate future fallout rates, allowing lenders to adjust funding strategies. For example, if data shows that fallout spikes during periods of increased refinancing activity, lenders may modify hedging positions to account for expected volatility. Advanced analytics tools, including machine learning algorithms, improve accuracy by identifying correlations between borrower characteristics and likelihood of closing.

Investor reporting requirements add another layer of tracking. Mortgage lenders selling loans to government-sponsored enterprises (GSEs) like Fannie Mae and Freddie Mac must provide detailed data on loan performance, including fallout rates. Investors use this data to assess a lender’s reliability in delivering expected loan volumes. A consistently high fallout rate can lead to pricing adjustments or stricter purchase conditions from investors, affecting profitability.

Market Factors Linked to Fallout Rate

Economic conditions and industry trends influence fallout rates, as financial market shifts affect borrower behavior and lender operations. Mortgage rates, employment levels, and housing supply all impact whether applicants follow through with their loans.

Mortgage rate volatility is a primary driver. When interest rates fluctuate, borrowers may delay decisions in hopes of securing a better rate or abandon locked loans if better terms become available elsewhere. During periods of declining rates, lenders see increased fallout as borrowers seek to renegotiate or switch lenders. Conversely, when rates rise unexpectedly, some applicants may no longer qualify for their desired loan amount, leading to higher fallout due to affordability constraints.

Housing market conditions also contribute. In competitive markets with low inventory, borrowers may apply for mortgages before securing a property, resulting in fallout if they cannot find a suitable home. In a slowing market, buyers may withdraw applications due to concerns about declining property values. Broader economic factors, such as job stability and inflation, further impact borrower confidence.

Example Scenario

Consider a lender operating in a market where interest rates suddenly drop. A borrower applies for a 30-year fixed mortgage at 6.5% and locks in the rate for 45 days. Two weeks later, market rates decline to 6.0%, prompting the borrower to explore options with other lenders. If they find a competitor offering a lower rate with similar terms, they may abandon their original application, increasing the lender’s fallout rate.

From the lender’s perspective, this disrupts pipeline projections and hedging strategies. If the lender had anticipated a 20% fallout rate but experiences 35% due to the rate decline, they may have over-hedged their locked loans, resulting in financial losses. To mitigate this, the lender could implement a rate renegotiation policy, allowing borrowers to adjust their rate within a certain threshold. While this may reduce fallout, it also affects profitability, requiring careful cost-benefit analysis.