Find the lending opportunities hidden in your SMB deposit data.
SMB360 scores your depositors to identify borrowers matching your existing credit profile — growing lending without increasing risk — and puts actionable opportunities directly into your bankers' workflow.
- Uses data you already have
- Fits systems you already use
- Measures the results
Charm's credit and cash-flow intelligence is proven across 98 banks and more than $100B in SMB loans. SMB360 applies it to your deposit base.
49 SMB depositors. The bank lends to two. The rest are never assessed, never offered anything, and borrow somewhere more expensive.
Score more businesses. Find more opportunities. Know what to do next. 12% borrow instead of 5%, 22% are eligible, and risk is flagged early. The rest get the tools to qualify.
SMB360 answers three questions every day
- Who should we lend to?
- Who is at risk?
- Who should we call?
Banks have the data, but aren't turning it into action
Three problems we see at almost every bank.
Too few depositors become borrowers
Most banks lend to about 5% of their SMB depositors, even though many more already fit their credit profile.
Risk is identified too late
Banks wait for statements or a late payment. By then much of the recoverable value is gone. Real-time monitoring closes that gap.
Insights don't become action
Banks can spot opportunities, but turning them into prioritized banker actions and loan applications is still manual.
Charm can tell you which of your SMBs borrow, from which lenders, and at what rates. The data is already in your systems. Charm turns it into actionable insights to win more of your existing customers.
Five steps: turn your data into action
One platform. No migration. SMB360 connects to your core, loan system and CRM by file transfer or API, and is set up in days.
Connect your data
Deposit and loan files already exist. No migration. Setup in days.
Score every depositor
Transaction, cash-flow and relationship signals identify the strongest lending prospects.
Prioritize opportunities
See who to lend to, who may leave, and where risk is emerging across the SMB portfolio.
Take action
Bankers get ranked, actionable opportunities and pre-qualified businesses to contact.
Measure outcomes
Every action tracked through to loans funded, deposits retained and losses avoided.
Built from your loan and deposit data, enriched with credit bureau, socio-economic and industry signals. Insight depth varies with account activity; primary operating accounts provide the richest cash-flow signals.
In practice: Find, Understand, Act
From opportunity to loan application in three steps, inside the core, LOS or CRM your bankers already use. No new workflow.
What your bankers do in the tool
Bankers know why to call and what to discuss. One click sends a pre-qualified business to the loan system with its scores and cash flow attached.
1. Filter the portfolio
Build a call list by lending opportunity, credit risk, deposit risk or relationship value.
2. Review each business
Score, cash-flow trend, key drivers and existing loans, so the banker knows why to call and what to discuss.
3. Send to your loan system
One click sends a pre-qualified business to the LOS with scores and cash flow attached. Nothing is re-typed, every outcome is counted.
What you'll see on your own book
Before you commit, we run your deposit and loan extracts through SMB360 and come back with a readout: a real analysis, on your data, with a value case built on explicit, agreed assumptions.
Illustrative value for a $2.6B SMB deposit base: about $12.5M in year one, about $10M annually
We calculate the opportunity using your portfolio, your economics and your assumptions, then measure it: loans funded, deposits kept, losses avoided. Not just reports delivered.
Lending
interest income, fees and losses avoidedDeposits
a separate pool: the funding value of balances won or keptIllustrative, from a real readout with client data anonymized. Every bank's model runs on its own portfolio, economics and agreed assumptions. Starts in weeks; file extracts are enough. See your own numbers.
Inside the readout: example analysis from a real bank, client data anonymized
Grow the base: where lending penetration rises
Deposits concentrate in the top bands. Borrowing doesn't: even there, only 13–15% have a loan. Tripling penetration band by band, starting where the deposits are, is how the lending base grows.
Businesses ready to borrow
Every business without a loan, plotted by its opportunity and risk scores. The highlighted zone is who is ready for a bank loan today, before anyone has asked.
Where your deposits are going
Where balances came from and where they went. A visible slice leaves as repayments to external lenders: credit the bank could have written itself, funded by its own deposits.
Churn, before it happens
Customers with a loan leave far less often, and scores drop months before an account closes. The same signal that finds a borrower keeps a depositor.
Your whole deposit base, before and after
The same journey for every depositor: more eligible, more borrowing, deeper wallets.
Today
$2.0B base. 5% borrow. Risk hidden in the grey.
With SMB360
$2.4B base. Every depositor scored. 12% borrow. 22% eligible. Risk flagged early.
The funding gap doesn't close by inventing a new lender. It closes when the cheapest one starts using what it knows.
Every dollar an SMB borrows at 40% instead of 8% is growth that didn't happen. Banks hold the deposits, the data and the trust. Charm exists to make that the deciding advantage.
The people behind the engine
Charm was founded on a simple observation: SMB lending runs on out-of-date technology and ignores the data telemetry banks already hold. The team has spent years building the databases, models and platform to change that.
Advisors
Scott Carter
Fintech executive and credit risk innovator, best known for leading ID Analytics and advancing identity-based analytics used by major financial institutions.
Scott Carter on LinkedIn
Ash Gupta
Senior financial services leader with deep experience in global payments, credit risk and regulatory strategy at American Express.
Ash Gupta on LinkedIn
Rahul Gupta
Banking and payments technology executive who led global platform and go-to-market strategy at Fiserv for banks and credit unions.
Rahul Gupta on LinkedIn
Roy Guthrie
Fintech CEO and operator who scaled Renovate America, expanding access to consumer and small-business financing nationwide.
Roy Guthrie on LinkedIn
Eric Haller
Data science and AI leader who built and led Experian DataLabs, focusing on advanced analytics for credit, fraud and decisioning.
Eric Haller on LinkedIn
Bob Hedges
Senior data and technology executive who served as Chief Data Officer at Visa, overseeing large-scale analytics and payments infrastructure.
Bob Hedges on LinkedInA BootstrapLabs portfolio company since 2022. Partnered with Abrigo to bring Charm's scoring into the loan origination systems banks already use.
See SMB360 on your own portfolio
We'll show what the engine surfaces from a sample of your deposit and loan data: how many customers are fundable now, where the early risk is, and what it's worth.