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Project for UK based startup

Automating Fintech Lending Operations

TL;DR

A multi-stream transformation to streamline loan origination and underwriting for a fintech startup. We standardized and automated key workflows (income and expense validations, borrower bank account ownership, and debt consolidation), integrated core systems (Morpheus, Trinity, Experian, Neo), strengthened UAT and unhappy-path coverage, and explored targeted GenAI use. Result: faster assessments, fewer manual steps, and a scalable foundation for new products and markets.

The Challenge

  • Multiple, fragmented workflows for loan processing across regions created inefficiencies and quality gaps.
  • Manual, Excel-heavy validation of household income and expenses increased error risk and review cycles.
  • Inconsistent borrower bank account verification and debt consolidation processes across markets.
  • Dispersed governance and UAT practices led to slower feedback loops and unresolved unhappy-path scenarios.

The Solution

  • Target architecture and platforms
    • Core systems: Mambu (case and document flow), Broker Portal, Pricing Engine
    • Integrations: Experian (credit bureau and Delphi scoring), Open Banking for bank data access, Onfido for ID&V documents
  • Data and validation
    • Automated checks for household income and expenses, mandatory data enforcement
    • Borrower bank account ownership validation approach for joint vs single accounts
    • Credit and policy rules including LTV, portfolio limits, CBTL exclusions, valuation policy by AVM or RICS
  • Underwriting and decisioning
    • Unhappy-path handling for failed credit search, max LTV breaches, ineligible categories and guardrails
  • GenAI exploration
    • Implementation of GenAI-assisted Q&A against underwriting guides with scoring on relevance, accuracy, clarity and action tracking for guide updates

The Process

Delivering Complexity Through Structure

Team setup

  • Cross-functional squad including Business Analysts, backend and frontend engineers, QA, UAT coordinators, and product stakeholders;

  • Regional stakeholders engaged from Ireland, London, and CH for requirement alignment

Cadence and ceremonies

  • Sprint-based delivery; regular refinement sessions and end-of-sprint demos

  • Weekly alignment meetings and show-and-tell, with risks and dependencies tracked; governance through analysis reviews and roadmap follow-ups

  • UAT standups and defect triage

Internal processes

  • Backlog management for client changes, policy document updates, and broker feedback incorporation

  • Environment coordination with partner teams, and release management checkpoints

The Results

  • Significant gains in operational efficiency: Automated validations and reengineered workflows dramatically accelerated loan processing times, enabling faster decision-making and reducing processing bottlenecks across departments.

  • Enhanced data integrity and reduced manual workload: By minimizing human input in financial assessments, we achieved higher data accuracy and consistency, while freeing up teams to focus on high-value tasks instead of repetitive checks.

  • Superior user experience and adoption: Streamlined processes and seamless integration of tooling led to greater clarity, fewer user errors, and improved satisfaction among both internal users and external stakeholders.

  • A scalable, future-ready platform: The new architecture lays a robust foundation for continued innovation — supporting expansion into GenAI-driven decision support, deeper automation, and readiness for entry into new markets and product verticals.