SMB Lending Platform

Part of the worlds-biggest-software-project initiative.

An AI-native, open-source platform for small business loan application, credit decisioning, and servicing.

The SMB Lending Platform is an end-to-end loan lifecycle system covering origination, underwriting, servicing, and collections for small and medium-sized businesses. It targets community banks, credit unions, fintech lenders, SBA-approved lenders, and B2B platforms embedding credit offerings — providing a modern, standards-aligned alternative to expensive, proprietary incumbents.

Why SMB Lending Platform?

Incumbent platforms such as nCino, Mambu, and TurnKey Lender are priced for enterprise budgets — typically $100,000–$500,000/year in licensing — putting them out of reach for smaller lenders and embedded-finance startups.
nCino's dominant position in community banks comes with a hard Salesforce dependency, increasing total cost of ownership and limiting flexibility for non-standard lending products.
Decisioning specialists like JUDI.AI and origination-only tools like Lendflow force lenders to stitch together multiple proprietary stacks rather than offering a coherent end-to-end platform.
Dodd-Frank Section 1071 demographic and pricing data collection is now a major operational burden for any lender originating 100+ SMB loans annually, and tooling is uneven across vendors.
No serious open-source alternative exists in a $2.5T (2023) market projected to reach $7.2T by 2032, leaving lenders without an auditable, self-hostable foundation for credit decisioning models.

Key Features

Loan Origination & Application

Digital loan application submission with e-signature
Borrower portal with loan status and payment history
White-label borrower experience for embedded finance partners
Loan officer mobile application
REST APIs for third-party and embedded integrations

Underwriting & Decisioning

Underwriting workflow with approval routing and history
Credit decisioning engine (rules-based or ML-powered)
Cash-flow-based underwriting using bank transaction data
Automated document spreading from tax returns, bank statements, and P&Ls
Credit bureau integration for credit scores and fraud flags

Servicing & Collections

Payment collection, statement generation, and escrow management
Payment processing with multiple funding sources
Collections workflow with delinquency escalation rules
Portfolio risk analytics dashboard
Early warning system for delinquency

Compliance, Risk & Fraud

KYC/AML screening and compliance checks
Regulatory compliance reporting (SBA SOP 50 10, Dodd-Frank Section 1071, HMDA where applicable)
Fraud detection at origination (synthetic identity, altered documents)
Audit trails for all transactions
Auditable, model-level transparency for non-discriminatory lending

Extensibility (Backlog)

Composable/modular architecture for custom lending products
No-code workflow builder for non-technical lenders
Conversational AI for application assistance
Post-disbursement borrower monitoring and covenant alerts
Accounting software integrations (QuickBooks, Xero, Freshbooks)

AI-Native Advantage

AI is applied where it directly reduces decision time, fraud loss, and manual analyst work: cash-flow-based credit models trained on bank transaction data underwrite SMBs that lack traditional credit history; document-spreading models extract structured financials from tax returns and bank statements in seconds rather than hours; anomaly-detection models flag synthetic identities and altered documents at origination; and post-disbursement agents monitor borrower transaction patterns to surface early warnings before covenants are breached. A natural-language application assistant guides SMB owners through eligibility, document collection, and form pre-population from connected accounting and POS data.

Tech Stack & Deployment

The platform is designed API-first, mirroring modern incumbents like Mambu, LendFoundry, and Lendflow, with optional white-label borrower and loan-officer UIs. Expected deployment modes include self-hosted and cloud, with embedded-finance use cases supported through REST APIs and webhook events. Standards alignment includes SBA SOP 50 10, URLA / SBA Form 1919, Dodd-Frank Section 1071, HMDA, MISMO (for real-estate-secured SMB loans), ISO 20022 for payment messaging, and GDPR / CCPA for applicant data privacy. Integrations target credit bureaus, payment processors, KYC/AML providers, and core banking systems.

Market Context

The global small business loans market was valued at $2.5 trillion in 2023 and is projected to reach $7.2 trillion by 2032 at a 13.0% CAGR (Allied Market Research, 2024). Embedded B2B lending is forecast to reach $50–75 billion in volume by 2026, roughly 15% of total SMB lending (Bain & Company, 2025). Software platform pricing ranges from $100,000–$500,000/year in enterprise licensing to $50–$200 per originated loan, with API-embedded models using revenue share or per-call pricing. Primary buyers are community banks and credit unions modernising SMB workflows, fintech lenders building automated underwriting, SBA-approved lenders, and B2B platforms embedding credit for their SMB customers.

Project Status

This project is in the research and specification phase.
Contributions, feedback, and domain expertise are welcome.

Contributing

We welcome contributions from developers, domain experts, and potential users. See CONTRIBUTING.md for guidelines.

Important: All contributions must be your own original work or clearly attributed open-source material with a compatible licence. Copyright infringement and licence violations will not be tolerated and will result in immediate removal of the offending contribution. If you are unsure whether a piece of code, text, or other material is safe to contribute, open an issue and ask before submitting.

Licence

Licence to be determined. See discussion for context.