Zorro MCP is live — plug private markets into Claude. Try it
SME Lenders

Smarter SME Lending
Origination, Powered by AI

Identify high-intent SME borrowers, enrich credit-relevant context, and help lending teams move from prospecting to pipeline faster.

Origination Agent Running
Scoring 1,247 companies 84% fit rate

ML-powered scoring against your lending criteria — revenue, sector, charge history, growth signals.

47 qualified this week
£12.4M aggregate opportunity
Finding decision makers 18 contacts found

Identifies FDs, CFOs, and owners with borrowing authority at every qualified company.

94% email verified
LinkedIn profiles matched
Drafting outreach 5 warm replies

Signal-specific messages — charge renewals, growth events, refinance windows — personalized per contact.

32% open rate
8% reply rate
The broker problem

You're paying brokers to own relationships that should be yours.

Broker fees compound forever

1–2% arrangement fees, year after year, on borrowers your team never spoke to directly. Every deal renews the dependency — and the cost.

You don't own the relationship

Brokers decide when to submit, who to submit to, and how your product is positioned. You get applications, not relationships. They can switch you off tomorrow.

No channel you own

If the broker panel changes, your deal flow stops. You've built no direct origination muscle, no data, no repeat borrower base. Nothing compounds.

"Broker fees were becoming a structural cost. The opportunity was there — we just didn't have the infrastructure to originate directly. Zorro gives us that infrastructure."

— Regional SME lender, illustrative scenario
How your agents work

Deploy managed origination agents. They run. You lend.

1

We encode your lending criteria

Sector preferences, deal size, geography, risk appetite, excluded industries. Zorro maps your underwriting model into agent scoring — lending-specific propensity models.

2

Custom ML models score the UK market

Three proprietary ML models: Market Need, Apply Propensity, and Lender Fit. Updated daily across 5M+ companies. Who will seek finance, who will apply, who fits your book.

3

Agents reach borrowers directly

Contact Selector identifies the decision-maker. Writer agent drafts a personalised message referencing the specific signal — charge renewal, revenue growth, fleet expansion.

4

Responses route to your team

Warm replies land in your inbox — from borrowers who've already shown interest, already been qualified, already received context about why you're reaching out.

5

Models retrain on your applications

Connect your CRM. Every application, approval, and decline updates your custom ML models. Month 6: no broker knows your market better.

Proprietary ML models

Not a database. A scoring engine that learns your book.

Most data providers sell static lists. Zorro deploys three ML propensity models — and as you connect your CRM, they become custom models trained on your actual deal history.

M1 — Market Need

Will they seek finance?

Logistic Regression + XGBoost ensemble. Trained on charge history, revenue trajectory, sector seasonality, company lifecycle signals. Predicts finance-seeking intent 3–6 months ahead.

M2 — Apply Propensity

Will they apply to you?

Scores likelihood of application, not just need. Factors in creditworthiness, prior lender relationships, CCJ history, director profile. Filters out companies that will apply but not qualify.

M3 — Lender Fit

Are they right for you?

Custom per lender. Connects to your CRM to retrain on your approved and declined applications. Month 3: your model knows your book. Month 6: it outperforms any generic credit score.

Your agents learn your book

Month 1 is good. Month 6 is a moat.

MONTH 1

Baseline deployed

Pretrained models deployed against your criteria. First companies found. First outreach sent via agents. You see what the market looks like at your lending criteria.

MONTH 3

Pattern emerges

CRM connected. Models retrain on your first applications. The system learns which signal combinations predict applications for your specific product.

MONTH 6+

Proprietary channel

A direct origination channel trained on your deal history. Custom ML model no competitor can replicate. Full relationship ownership. Data that compounds forever.

Stop paying for roles agents replace

Deploy agents. Cancel the contracts.

Broker network fees
£40k–£800k/yr

Arrangement fees, panel management, relationship maintenance. All for introductions to borrowers who should be yours.

Business development team
£60k–£90k/head

Headcount for outreach, follow-up, relationship management. Work that doesn't scale. AI agents do this at any volume, 24/7.

Data providers
£8k–£40k/yr

Creditsafe, Dun & Bradstreet, Experian. Static databases that tell you who exists, not who needs your product right now. Included in Zorro.

Lead generation agencies
£150–£500/lead

Paid leads that expire, convert poorly, and reach your competitors at the same time. Agents generate unlimited qualified targets.

Typical annual saving — managed lender account
£120k – £900k
in broker fees, BD headcount, and data subscriptions replaced by Zorro agents

See how Zorro fits your lending criteria

Get a walkthrough tailored to your market, borrower profile, and origination process.

Deploy origination agents.
Own your borrower relationships.

Book a demo Available this week