LendingTech and BNPL Software Development

Application intake covers digital borrower onboarding, document upload, identity verification via providers like Onfido or Persona, and pre-population of bureau data from Experian, Equifax, or TransUnion so your underwriters are not re-keying data. A structured application workflow routes each file through the steps your credit policy requires before it reaches decisioning.

The credit decisioning engine applies your specific underwriting rules, not a template. Income verification, affordability calculation using open banking data from Plaid or TrueLayer, debt-to-income thresholds, and custom scoring variables are all configurable by your credit risk team without code changes. Decisions within your automated appetite return in seconds.

Built for consumer lenders replacing manual intake queues, SME lenders building a digital origination channel, and specialist lenders whose product mix requires a decisioning engine that a standard LOS cannot configure.

Embedded checkout integration gives merchants a single SDK or API to add BNPL as a payment option, with a branded experience that keeps the customer on the merchant's checkout. Real-time credit decisioning returns an approval or soft decline in under two seconds, so cart abandonment from underwriting latency is not a factor.

Repayment scheduling handles instalment plans, automated payment collection via Stripe or Dwolla, failed payment retry logic, and customer-facing repayment management. The merchant dashboard surfaces approval rates, average order values, and repayment performance by category so your risk team has the data to tune policy.

Built for BNPL operators building a credit product from scratch, retailers adding BNPL to their checkout, and embedded finance businesses adding short-term credit to an existing payment product.

A configurable rules engine applies your credit policy as a sequence of decision gates: bureau score threshold, income verification, affordability ratio, fraud flags from providers like Socure or Sardine, and any custom variables your model uses. Policy rules are managed through a UI your credit risk team operates directly, with version control and full audit trails on every rule change.

AI-assisted underwriting uses machine learning models trained on your historical loan performance data to surface risk signals that static rule sets miss: thin-file borrowers who perform well, application patterns that correlate with early arrears. The model augments the rules engine rather than replacing it, so your credit team stays in control of policy.

Built for lenders replacing manual underwriting, BNPL operators improving approval rates without increasing default rates, and credit unions building a data-driven decisioning capability.

The loan ledger holds every loan record with disbursement date, principal balance, interest accrual, scheduled repayment dates, and payment history. Repayment collection integrates with ACH, Dwolla, or Stripe, with real-time payment confirmation events updating the loan record so the balance is always current.

Arrears management applies configurable rules to overdue accounts: automated payment retry, SMS and email contact sequences via Twilio, internal escalation to a collections queue at defined days past due, and external collections handoff workflows. Early settlement calculations and loan modification workflows handle the edge cases that generate the most manual work in a growing book.

Built for consumer and SME lenders whose current servicing tools require manual reconciliation, BNPL operators scaling repayment volume beyond what a spreadsheet supports, and mortgage lenders who need a servicing platform that reflects their product structure.

Collections workflow automation segments overdue accounts by days past due, balance, risk tier, and contact preference, then routes each account to the right action: automated payment retry, outbound SMS or email, agent-led contact, or external debt collection agency referral. Each step is logged with timestamp and outcome so your compliance team has a full contact history.

Agent workload management gives your collections team a prioritised daily queue rather than a raw list of delinquent accounts. Predictive prioritisation uses repayment history and behavioural signals to surface accounts most likely to respond to contact on a given day, so agents spend time on accounts where contact makes a difference.

Built for lenders whose collections team works from spreadsheets and manual queues, BNPL operators facing rising arrears as their book scales, and credit unions adding a digital collections workflow to replace their current paper-based process.

ECOA adverse action notice generation creates compliant decline letters with the specific reasons required under US consumer lending law, pulling directly from the decisioning engine's output so the reason codes are accurate and traceable. HMDA data capture records the required fields at application and decision stage so your annual LAR submission is not a manual data assembly exercise.

Audit trails on every credit decision, policy rule change, and customer interaction give your compliance team the documentation for a regulatory examination without a support ticket. For UK lenders, FCA Consumer Credit Act compliance includes responsible lending assessment records and Section 75 liability documentation. Data retention rules under GDPR are enforced at the data layer, not by manual deletion processes.

Built for regulated lenders who need compliance infrastructure that scales with volume, BNPL operators preparing for FCA authorisation under the UK's 2026 BNPL regulatory framework, and credit unions whose current audit trail is a spreadsheet.