MCA underwriting is fundamentally <strong>cash flow underwriting</strong>. Unlike traditional lenders who rely on credit scores, collateral values, and financial statement ratios, MCA funders live and die by what the bank statement reveals about a merchant's daily cash position. After analyzing tens of thousands of funded deals and their outcomes, the industry has converged on six metrics that are the strongest predictors of repayment success.
This guide explains each metric in depth: what it is, how to calculate it, what good and bad values look like, and how it correlates with actual repayment outcomes.
1. Average Daily Balance (ADB)
Average Daily Balance is the <strong>mean of the end-of-day balance</strong> across all calendar days in the statement period. It is the single most informative snapshot of a business's cash cushion — the amount of money available to absorb expenses, cover timing gaps, and service debt obligations.
How to Calculate
Sum the ending balance for every day in the period (including weekends and holidays when the balance remains unchanged) and divide by the total number of days. For a 90-day statement: ADB = Sum of 90 daily ending balances / 90.
ADB Context Matters
ADB must be interpreted relative to the business's monthly revenue. A $3,000 ADB on a business doing $50,000/month in deposits represents only 2 days of operating expenses — that is thin. The same $3,000 ADB on a $10,000/month business represents 9 days of coverage, which is much healthier. Use ADB-to-revenue ratio for more meaningful comparison.
2. Monthly Revenue Trend
Monthly revenue trend measures the <strong>direction and magnitude of change</strong> in total monthly deposits over the statement period. A business with growing revenue is fundamentally different from one with declining revenue, even if their average monthly deposits are identical.
How to Calculate
Compare total deposits in each month of the statement period. Calculate the month-over-month percentage change. A simple approach: ((Month 3 deposits - Month 1 deposits) / Month 1 deposits) * 100. More sophisticated methods use linear regression across all three months.
- <strong>Growing (10%+ increase):</strong> Positive signal. Business is expanding, and future cash flow will likely support the MCA payment. Correlates with 85%+ repayment
- <strong>Stable (within +/- 10%):</strong> Neutral signal. Business is consistent, which is predictable and manageable. Correlates with 80%+ repayment
- <strong>Declining (10%+ decrease):</strong> Negative signal. Revenue is falling, and the MCA payment will consume a larger share of shrinking income. Correlates with below 75% repayment
- <strong>Volatile (swings of 30%+):</strong> Caution signal. Unpredictable cash flow makes consistent daily remittance difficult. Seasonality should be confirmed
3. Deposit Consistency
Deposit consistency measures <strong>how regularly deposits arrive</strong> in the business account. A restaurant receiving credit card batch deposits 6 days per week has very different cash flow dynamics than a contractor who receives 2-3 large checks per month. Consistency matters because MCA payments are debited daily — if deposits are lumpy, there will be days when the account cannot support the withdrawal.
How to Calculate
Count the number of days with at least one deposit, then divide by the number of business days in the period. Also measure the coefficient of variation (standard deviation / mean) of daily deposit amounts. Lower CV means more consistent deposits.
4. NSF/Overdraft Frequency
NSF frequency is the <strong>count of returned items and overdraft events per month</strong>. As discussed in detail in our <a href="/blog/nsf-analysis-bank-statements">NSF Analysis Guide</a>, this metric is one of the top three predictors of MCA default. High NSF frequency means the account is already struggling to meet existing obligations — adding another daily debit increases the likelihood of payment failure.
How to Calculate
Scan all transactions for NSF fee charges, returned item notifications, and overdraft fee charges. Count unique events (not double-counting the fee line and the returned item line). Divide by the number of months in the statement period for a monthly average.
Repayment correlation: merchants with 0-1 NSFs per month show <strong>88% or higher repayment rates</strong>, while those with 8+ NSFs per month drop below 65%. The relationship is approximately linear between these endpoints.
5. Existing Debt Service Ratio
Existing debt service ratio is the <strong>percentage of monthly revenue consumed by existing MCA and loan payments</strong>. This is the stacking metric — it quantifies how much of the merchant's income is already committed to debt before your position is added.
How to Calculate
Identify all recurring ACH debits to known MCA funders and lenders. Sum their monthly total. Divide by average monthly deposits. DSR = (Total monthly MCA/loan debits / Average monthly deposits) * 100.
Include Your Proposed Position
When evaluating DSR, don't forget to add your proposed daily remittance to the total. If the merchant is at 20% DSR and your position would add another 12%, the combined 32% puts them in the "High" risk category. Always calculate pro-forma DSR including the new position.
6. Negative Day Count
Negative day count is the <strong>number of calendar days</strong> in the statement period where the account ended with a negative balance. This is a direct measure of insolvency frequency — how often the business literally has less than zero dollars. Negative days are highly correlated with both NSF activity and MCA payment returns.
How to Calculate
Review the daily ending balance (or compute it from the running balance on transaction lines) and count every day where the balance was below $0. This requires tracking the balance on non-transaction days (weekends, holidays) as well, since the balance remains negative until a deposit posts.
Metrics Summary Table
Banklyze calculates all six metrics automatically from uploaded bank statements and combines them into a single composite health score with a letter grade.
See Banklyze in ActionUsing Metrics Together
No single metric tells the full story. The power of these six metrics comes from <strong>analyzing them in combination</strong>. A high ADB with high NSFs suggests the merchant has cash but manages it poorly. Low revenue trend with zero NSFs may indicate a business that is shrinking but still solvent. High deposit consistency with a high DSR means the merchant has revenue coming in regularly but it is all going to existing debt.
The best underwriting systems assign weights to each metric and compute a <strong>composite score</strong> that accounts for both individual metric values and their interactions. This is exactly what Banklyze's health score algorithm does — it combines all six metrics with appropriate weighting to produce a single score from 0 to 100 that reliably predicts repayment probability.
Individual metrics are useful. Combined metrics are predictive. Weighted composite scores are transformative. The progression from looking at one number to understanding how six metrics interact is the difference between guessing and underwriting.
— MCA Underwriting Principles
Stop calculating metrics in spreadsheets. Banklyze extracts, computes, and scores all six metrics in under a minute.
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