Page 33 - GS250802

Insights and Expertise

projections with confidence bands. Scenario planning The need for guardrails
moves from guesswork in a spreadsheet to a few clicks.
The tools don’t replace basic financial discipline; they sur- As AI moves deeper into underwriting and portfolio man-
face the right decisions sooner, when costs are lower and agement, governance grows more important. Banking
options are wider. supervisors have long required robust model-risk man-
agement, including clear development and validation pro-
For underwriting teams, the benefit is two-fold: precision cesses, performance monitoring, and effective oversight.
(more accurate estimates of loss and prepayment) and Even nonbanks that rely on bank partners or sell to bank
timeliness (faster detection of deteriorating conditions). investors are feeling these expectations. Across jurisdic-
Models can spot subtle shifts in deposits, ticket sizes or tions, the regulatory arc points in the same direction:
refund rates that often precede distress. They can also transparency, testing and controls commensurate with
flag positive momentum such as a marketing campaign risk.
pulling through to revenue, or a new location ramping on
schedule, which supports responsible upsizing of offers. In the EU, for example, the new AI Act sets a risk-based
For merchants, the benefit is transparency and agency. framework that treats the assessment of creditworthiness
With AI tools, they gain clearly defined ranges for remit- as high-risk, triggering stricter obligations. Firms that
tances, earlier alerts when a plan veers off track, and dash- build explainable models, document decisions and track
boards that explain why the system is recommending a outcomes will be better positioned as rules converge.
change, not just what it recommends. Practical AI playbook

Case in point: JPMorgan’s tools combine machine-learn- Lenders need to standardize POS, bank and accounting
ing forecasts with real-time visibility and workflow au- inputs so models learn on consistent features rather than
tomation, cutting manual effort and improving decision brittle one-offs. Instrument for feedback. They need to
speed for clients. The important part for SMB finance is close the loop between predicted and actual cash perfor-
not copying the exact stack but adopting the principles mance to recalibrate quickly, and give risk analysts tools
of integrated data, rolling forecasts, and model-driven to interrogate drivers and override when the model’s con-
alerts. Those concepts are now reachable for smaller firms fidence is low. Also, clear communication is a must. Mer-
through embedded platforms and next-gen SMB software. chants should see repayment logic, not just repayment
results. Bundle tools, not just term sheets. The value prop-
The cutting edge osition grows when forecasting and scenario modeling
Cash-flow underwriting depends on consented access to ride along with funding. These aren’t theoretical; they’re
bank data. The industry has been moving away from frag- already embedded in programs merchants use daily.
ile screen scraping toward secure APIs that give custom-
ers granular control over which accounts and fields can Merchants need to treat forecasting as a weekly habit.
be shared and for how long. This shift reduces error rates, Rolling views beat annual budgets. They should: use sce-
bolsters security and helps lenders meet compliance obli- narios; model upside (a marketing win), downside (a sup-
gations. As open-banking practices spread, expect under- plier delay), and neutral paths; watch early-warning sig-
writing to feel more like linking a payroll app: authenti- nals such as slipping deposit cadence, rising refunds and
cate, choose accounts, share selectively revoke easily. creeping expenses. With AI, merchants can make capital a
tool, not a crutch. Advances and loans are accelerants that
Another fast-moving frontier is AI agents that behave like work best with a plan that turns dollars into durable earn-
a virtual finance team that pulls bank feeds, reconciles ing power. And merchants should seek explainability. If a
transactions, projects cash flow and drafts recommen- platform proposes a repayment adjustment, they deserve
dations. Early movers are positioning these agents as AI to know why. The same AI that evaluates risk should help
CFOs for SMBs that can’t afford a full finance department. business owners understand it.

The promise is compelling: always-on financial monitor- Alternative financing is becoming an operating system
ing plus human review for high-judgment calls. For lend- comprising capital on demand, underwriting tied to real
ers, that same agentic capability can standardize document cash flows and AI that illuminates what’s ahead. As SMB
collection, surface exceptions, and keep risk views current tools mature and standards for data sharing and model
without drowning analysts in manual checks. SMB adop- governance crystallize, all parties involved can expect a fi-
tion of AI tools is accelerating, particularly in finance and nancing experience that feels less transactional and more
operations. Survey data from the small-business ecosys- advisory, which is measurably better for merchants and
tem points to a majority of owners now using at least one safer for funders. The original promise of MCAs—speed
AI-enabled product, with daily usage climbing. The early and flexibility—remains. AI adds foresight.
wins are pragmatic and include automation of repetitive
workflows, faster reporting and better visibility. Hands- Chad Otar is CEO of Lending Valley Inc. For information about the
on programs and how-to resources are helping owners company, please visit www.lendingvalley.com. To reach Chad, send an
separate durable tools from hype and integrate them into email to chad@lendingvalley.com.
everyday routines.

33