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Insights and Expertise

From MCAs to than a traditional monthly billing cycle, is what makes
MCAs fast and elastic. The same tight coupling now un-
AI-powered derpins newer variants offered by embedded platforms.
This processor-adjacent design is where AI can add intel-
ligence. The rhythms of cash collections and outflows are
cash-flow intelligence: observable in real time and ready for modeling.
AI-informed underwriting
Alternative financing AI does not replace the MCA concept so much as expand

it. Machine-learning models can evaluate far more than
is growing up trailing card sales, for example, seasonality, store-level
momentum, SKU mix, invoice timing, deposit volatility,
payroll cadence, marketing lift and local demand signals.
Instead of a single view of sales that occurred over a spe-
cific period, risk teams get a living picture of the busi-
ness’s health and near-term trajectory. In practice, that can
mean smarter offer sizing, holdback percentages calibrat-
ed to actual variability and dynamic repayment plans that
adjust within pre-agreed bounds.

It also means declining more applications that look fine
on paper but spike certain risk indicators in pattern data.
Done well, this improves access for good businesses while
By Chad Otar containing losses.
Lending Valley
A related trend, cash-flow underwriting, is pushing be-
mall and midsize businesses run on cash flow, yond transaction processors to bank-account data. With
not quarterly earnings calls. When revenue borrower permission, lenders pull real-time inflows and
comes in waves access to fast, flexible working outflows from business accounts, categorize them and
S capital can be the difference between capturing evaluate repayment capacity based on actual cash dynam-
an opportunity and missing payroll. For years, merchant ics rather than proxies.
cash advances (MCAs) filled that need-it-now gap by
exchanging a lump sum today for a slice of future card Open-banking rails and account-connection tools have
sales tomorrow. made this far simpler than even a few years ago. For SMBs
with thin or atypical credit files, cash-flow data can be the
What’s changing the game is artificial intelligence. AI is difference between a hard no and a tailored offer.
transforming how financing is underwritten, priced and
monitored, as well as how merchants themselves forecast Speed still matters. Embedded finance programs housed
cash flow, plan spending and grow more resilient. The re- inside commerce platforms can pre-underwrite using plat-
sult is a financing relationship that looks less like a one-off form telemetry and update risk views continually. That’s
advance and more like an ongoing, data-rich partnership. how some programs surface pre-qualified offers inside
a merchant dashboard and allow the business to choose
MCAs in brief an amount, with repayments swept from a percentage of
daily sales. The appeal is obvious: capital aligned to the
The classic MCA exchanges an upfront advance for a fixed rhythm of sales, with fewer forms and faster decisions.
or variable percentage of future card receipts, withdrawn
automatically until the obligation is met. Because remit- Beyond the advance
tances scale up and down with revenue, the structure can
be gentler in slow periods than a fixed amortizing loan. Today’s financing platforms increasingly ship with soft-
ware, not just money. The most valuable additions help
Decisions are fast, and approvals hinge on business per- owners answer three questions:
formance more than the owner’s personal credit profile, 1. What will my cash look like next week, next month,
which is useful for firms that can’t clear bank loan hurdles. next quarter?
But costs can be high, and the factor-rate pricing used by
many providers can obscure the true annualized expense. 2. What could break that forecast, and how would I
In short: quick oxygen, not always cheap oxygen. respond?
3. What investments can I responsibly make, and
The model’s operational backbone is payment data. Pro- when?
viders historically partnered with processors to see daily
card settlements and sweep agreed percentages as sales AI-assisted forecasting models ingest accounting feeds,
occur. That deep integration with POS revenues, rather settlements, invoices and seasonality to produce rolling
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