Streamline your loan approval process: A step-by-step guide to automation

Are you still bogged down by manual processes in your loan approval workflow? You’re not alone. However, it’s time to evolve. Automating this process is crucial not just to meet industry demands but also to enhance accuracy and efficiency in your operations.

This guide will walk you through automating your loan approval process, from understanding your current workflow to formalizing policy changes. By the end, you’ll have a clear roadmap to follow, leading to a more efficient loan approval system. Let’s dive in.

Step 1: Understanding your current process

Before diving into automation, it’s vital to understand what your credit officers do during the loan review process. While you might have a written credit policy, it may not fully capture the actual steps your team takes. Observing the credit officers can uncover informal evaluation steps not documented in the policy.

Identifying these gaps will help avoid performance issues during the automation process, ensuring a smoother transition.

Step 2: Identifying key processes and checks

In the journey to automation, start by pinpointing the critical processes and checks involved in credit underwriting. Focus first on automating the "knock-out" (KO) criteria—these are the checks that, if unmet, immediately disqualify a loan application.

Documenting and automating these KO criteria is a solid foundation for successful automation.

Step 3: Assessing data availability

Next, evaluate the availability of data necessary for implementing the practical rules you’ve identified. This includes credit history, income, employment records, and other financial information used in loan evaluations. If certain data is lacking, take steps to ensure it can be efficiently collected and processed.

Step 4: Implementing the rules

With your rules and data in place, it’s time to automate the credit underwriting process. This can be achieved by either hard-coding the rules into your loan management system or utilizing a rule engine. The implementation should strictly follow the processes and checks identified earlier, ensuring all KO criteria are enforced.

Step 5: Formalizing policy changes and impact assessment

As automation progresses, formalize the policy change approval process to ensure thorough testing before implementation. Monitor the impact of each change by cross-referencing expected outcomes with actual results, particularly concerning approval rates and risk performance.

Why not everything should be automated

It’s important to acknowledge that not all aspects of the loan approval process can be automated immediately. After automating the primary rules, you may find that certain parts of the credit underwriting process still require manual intervention. This is acceptable.

Automation should be approached incrementally, with continuous data collection and analysis guiding further automation steps. This method ensures informed decision-making and helps maintain risk performance over time.

Conclusion

By following this step-by-step approach, you’ll transition from manual processes to a more automated and efficient loan approval system. Each step is designed to provide clarity, ensure practicality, and balance the benefits of automation with the necessity of human oversight. Embrace the change, and your operations will become faster, more accurate, and more cost-effective.