Evaluating the ROI of Decision Engines in Financial Companies

Introduction

A Southeast Asia use case for automating loan underwriting

Automating loan underwriting with decision engines like Decisimo gives financial companies a practical way to cut costs, reduce errors, and speed up decision-making. Here is how to evaluate the ROI of that shift, using a real-world Southeast Asia use case.

Cost-Benefit Analysis

Current Manual Underwriting System

• Total monthly cost: 32 underwriters + 3 team leaders = $14,600

Proposed Automated System: Decisimo

• Total monthly cost: Decisimo + 3 retained underwriters + 1 team leader = $3,367
• Monthly savings: $14,600 - $3,367 = $11,233
• Annual savings: $11,233 x 12 = $134,796

Cost Breakdown for Decisimo

• Decision engine cost per month: $1,500
• Retained human underwriters: $1,200
• Team leader: $600
• Amortized one-time integration cost: $67

Key Factors for ROI Calculation

Direct Cost Savings

1. Personnel costs: The transition reduces personnel costs by $11,200 per month.
2. Decisimo costs: $1,500 per month to automate 500 loans per day.

Error Reduction

Human errors can lead to incorrect underwriting decisions and weaken loan portfolio quality. A decision engine like Decisimo applies the same decision logic every time, which lowers the error rate.

Speed and Opportunity Cost

1. Faster approval: Automated systems speed up loan approval. For a broader view of the loan approval process, it helps to map each decision step first.
2. Customer experience: Faster approvals improve the customer experience.
3. Operational capacity: Teams can handle more applications without adding headcount.
4. Revenue timing: Faster decisions can bring forward disbursement and booking.

Calculating ROI

ROI can be calculated with this formula:

    ROI = (Net Profit / Total Investment) x 100
  

Accounting for Internal Integration Costs

While Decisimo does not charge integration fees, financial institutions still need to account for their own internal integration costs. In this example, we estimate two man-days of IT development at $400 per day, for a one-time integration cost of $800. Amortized over 12 months, that adds $67 to monthly operating costs. If you are planning the technical side, this guide on API endpoints is a useful reference.

Risks and Mitigations

1. Implementation time: Delays in implementation push back realized savings.
2. Mitigation: Define scope early, assign owners, and test critical decision flows before rollout.
3. Employee retraining: Retraining costs may appear during the transition.
4. Mitigation: Keep a smaller underwriting team in place and retrain them for exception handling and oversight.
5. Compliance and regulation: The new process must meet regulatory and internal control requirements.
6. Mitigation: Document rules, approvals, and changes so teams can review decision traces during audits. This article on tracing models and decisions covers the basics.
7. Policy design risk: Poorly defined underwriting rules can limit the expected ROI.
8. Mitigation: Review your underwriting policy before automating it.
9. Operational dependency: Teams may rely too much on automation without setting escalation paths.
10. Mitigation: Keep manual review paths for edge cases, policy exceptions, and quality checks.

Conclusion

Switching to a decision engine like Decisimo can produce clear direct savings and reduce the opportunity cost of slow underwriting. In this Southeast Asia use case, the potential cost reduction is about 77%, which makes the ROI case strong. Because Decisimo does not charge integration fees, the investment is driven mainly by internal implementation effort. Financial companies should review these numbers, the operating impact, and the transition risks when assessing a move to automated decision logic.