Improved Underwriting and Leveling Up Lending with DecisionRules
Streamlining Lending Decisions: How First Response Finance leveraged DecisionRules to enhance underwriting agility, empower teams with transparency, and scale operations across auto finance and personal loans while achieving faster rule updates and cost efficiency.
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Read the PDF: How First Response Finance Transformed Underwriting with DecisionRules
About First Response Finance
First Response Finance is a leading UK-based vehicle finance provider specializing in hire purchase agreements for used cars, motorbikes, and vans. In addition to vehicle financing, First Response Finance offers personal loans to existing customers.
Established in 1998, First Response Finance has over two decades of experience, building a strong reputation for responsible lending. Their mission is to provide a seamless and responsive financing experience, blending innovative underwriting practices with a commitment to customer satisfaction.
Operating exclusively in the United Kingdom, First Response Finance caters to consumers seeking tailored solutions for vehicle purchases. With a dedicated team of over 300 employees, the company continually refines its products, processes, and services to meet the evolving needs of its customers.
First Response Finance’s estimated annual revenue is $75 million, reflecting their strong market presence and consistent growth.
The Challenge: Inflexible Legacy Underwriting and Rule Updates
Prior to implementing DecisionRules, First Response Finance’s underwriting rules were hard-coded into their underwriting platform, making any modification lengthy and cumbersome. This code-based approach presented several challenges:
- Lack of Agility: Even small updates required developer involvement in C# code, resulting in lead times of 2+ weeks to implement changes.
- Limited Transparency: Because all decision logic was embedded in code, non-technical stakeholders found it nearly impossible to read or propose rule modifications.
- Scalability Issues: First Response Finance planned to expand its lending products beyond auto finance into personal loans and collections, but the rigid underwriting logic restricted cross-platform reuse.
With markets shifting rapidly and credit risk parameters needing continuous tweaks, First Response Finance recognized that agility in decision-making was a top priority. Their search for a cloud-compatible, user-friendly rules engine led them to DecisionRules.Why First Response Finance Chose DecisionRules
- Cloud and SaaS Flexibility: First Response Finance wanted a solution that would easily integrate with their Azure-based platform and avoid on-premise hosting headaches.
- Cost-Effectiveness: Other rule engines offered advanced features that First Response Finance did not need—and at prohibitively high prices. DecisionRules offered the right balance of robust capabilities and affordability.
- Intuitive UI and Transparency: DecisionRules’ user-friendly interface allowed non-developer teams to read, suggest, and eventually own rule changes without writing code.
- Ease of Implementation: First Response Finance’s team needed a system that integrated quickly with their RESTful Azure APIs, enabling frictionless retrieval and execution of rules.
Implementation and Architecture
First Response Finance’s solution architecture blends multiple credit models with DecisionRules:
- Data Ingestion:
- Borrower information arrives from an underwriting platform or quote engine on First Response Finance’s website.
- Credit bureau data, consumer search history, and other applicant details (e.g., address tenure, employment type) flow into First Response Finance’s Azure API container.
- Data Translation & Scoring:
- The Azure API translates raw variables (e.g., counts of defaults over various time spans, deposit amounts, vehicle details) into 700+ standardized fields.
- Four distinct R-based models (covering creditworthiness, behavior, auto-decline triggers, and missing information checks) run these variables to generate risk or “propensity” scores.
- DecisionRules Integration:
- Once the models return their respective scores, First Response Finance’s Azure API calls DecisionRules.
- DecisionRules combines those model outputs with additional factors (e.g., applicant’s deposit size, vehicle attributes like mileage, brand reliability, or body type) to classify applications into:
- Auto Accept – frictionless approval if the applicant meets top-tier requirements.
- Auto Decline – immediate rejection if critical risk thresholds are met.
- Manual Review/Referral – an underwriter reviews borderline or special cases.
- Tiered Risk Output:
- DecisionRules also returns a tier (1 through 7), reflecting how risky the loan is. The tier dictates the pricing band, which the underwriting system uses to finalize APR.
- Results & Logging:
- First Response Finance logs the JSON response from DecisionRules back into its database, allowing deeper analytics, champion-challenger testing, and performance tracking of the underwriting logic.
Timeline:
- While the internal processes extended the overall deployment, integrating the DecisionRules SaaS was swift. First Response Finance’s main complexity lay in finalizing contractual details and building alignment between internal APIs and the DecisionRules contract.
Key Use Cases
- Holistic Auto Finance Underwriting
- Score Consolidation: DecisionRules ingests four model outputs (credit, behavior, auto-decline, missing information) and merges them with additional applicant data (e.g., deposit, vehicle type).
- Automated Decisioning: Based on if-then conditions (e.g., “if deposit < 20% and age < 21, route to referral”), it swiftly sorts applications into accept, refer, or decline.
- Risk Mitigation by Vehicle Factors
- Vehicle Reliabilities: Luxury or older vehicles with high maintenance costs are flagged. DecisionRules may override an “auto accept” if the risk profile is elevated by certain makes and models.
- Champion-Challenger Analysis
- First Response Finance compares new underwriting logic (the “challenger”) with the legacy approach (the “champion”) to measure acceptance rates, default patterns, and profits.
- By collecting results from the DecisionRules JSON responses, First Response Finance can refine or revert rules in near real time.
- Transparency and Collaboration
- Business Teams in Control: Non-technical users now view, comment, and propose changes within the DecisionRules UI.
- Audit & Troubleshooting: Audit logs identify repeated calls (e.g., test heartbeats) or anomalies in usage, helping First Response Finance optimize system calls.
Measurable Outcomes & Benefits
- Drastic Reduction in Rule Update Times
- Before: 2+ weeks to cycle a minor rule tweak through developer sprints, QA, and deployment.
- After: Some changes move to production in 2 days or even less, drastically improving First Response Finance’s responsiveness to market shifts.
- Empowering Non-Technical Teams
- The underwriting and analytics teams can directly read and propose updates in the rules—no coding required. This fosters greater collaboration and ensures underwriters aren’t bottlenecked by IT.
- Enhanced Decision Transparency
- Decision logic is no longer buried in C# code. By centralizing logic in DecisionRules, First Response Finance can easily debug or investigate borderline cases.
- Teams track exactly which rule conditions triggered an accept, decline, or referral—building trust and clarity across the organization.
- Cost Efficiency and Future Scalability
- Freed from maintaining an in-house rules engine, First Response Finance’s developers focus on strategic projects (e.g., new loan products, advanced analytics).
- The subscription model and flexible usage plan from DecisionRules avoids the steep licensing fees of competing solutions.
- Real-Time Monitoring & Analytics
- First Response Finance logs every DecisionRules outcome, enabling champion-challenger comparisons of approval rates.
- This continuous feedback loop fuels data-driven refinements to underwriting strategies.
What’s Next for First Response Finance and DecisionRules
- Personal Loans
- First Response Finance plans to integrate DecisionRules into a new personal loan product, ensuring consistent, automated, and transparent credit risk decisions across its entire lending suite.
- Collections & Recoveries
- First Response Finance aims to extend DecisionRules into collections, using rule flows to tailor repayment plans or special strategies for delinquent accounts—closing the loop from loan origination to resolution.
- Advanced Rule Flow and Split Testing
- Next steps include A/B testing (split testing) and “multi-hit” rule flows in DecisionRules. This functionality will let First Response Finance surface every rule triggered, not just the first.
- Enhanced rule flows will support even more granular credit strategies, such as partial auto-accept with conditions or different deposit thresholds.
- Continuous Improvement
- With iteration cycles now measured in days, First Response Finance plans to further streamline internal processes and harness deeper data analytics to keep pace with changing credit landscapes.
Conclusion
By implementing DecisionRules, First Response Finance significantly improved its underwriting workflow, dramatically reducing turnaround times for rule changes, improving transparency, and laying the groundwork for expanded product offerings. The move away from code-heavy logic into a dynamic, easily adjustable rules engine has not only cut costs and increased agility but also enhanced collaboration across development, analytics, and underwriting teams.For First Response Finance, DecisionRules isn’t just another tool—it’s a critical part of their evolving strategy to lead in auto finance and beyond, ensuring that every decision, from loan origination to collections, is made swiftly, fairly, and with the highest degree of accuracy.