4 Ways Decision Rules Drive Loan Origination Automation Guidelines for Auto Lenders

loan origination software comparison

Loan origination automation guidelines help refine processes by ensuring lenders have a support system to make accurate decisions. This starts with a base level of software features to provide an environment for effective decision rules. After all, automation doesn’t exist in a vacuum. It requires guidelines that limit risk while ensuring flexibility and scalability.

Automation depends on the features of the software that help to support effective decisioning. Configurable options that integrate common supportive third-party solutions are ideal. Running an automated process off a single end-to-end platform that offers optional features and functions and third-party integrations is optimal, and the resulting robust data and analytics help drive strategies.


Loan Origination Automation Guidelines for Software


Loan origination automation has a proven effect on enhancing efficiency when the proper software is used. Loan origination automation guidelines should center around the features of the technology and how it supports decision rules. Some specific attributes to seek out include: 

  • Configurability: Some lenders choose to develop their own customized loan origination software as they believe there is no single solution that can possibly satisfy all their needs. Custom software is a costly option that requires infrastructure development, industry and development expertise, and ongoing maintenance to keep up with business and compliance requirements and advances in innovation.
    A configurable, cloud-based SaaS solution can deliver far more innovation and be far more flexible, and offer the overall infrastructure, core systems, and add-on features and integrations that can be adapted to the lender’s needs. This minimizes a lender’s maintenance requirements, offloading most of it to the software providers. A SaaS solution can offer a much greater level of flexibility, with options for changing things like workflows, integrations, verifications, and other needs. 
  • Integration: Loan origination decisions require data. A loan origination system should include pre-built integrations that lenders can select and quickly incorporate to meet their specific needs. Pre-integrations relating to standard credit data, alternative credit data, collateral valuation, and applicant demographic information, as well as integrations for verifications and fraud protections processes are vital. Integrations for eContracts, eSignatures, and digital document storage ensures greater borrower satisfaction and a simplified file management system for easy retrieval. 
  • Analytics: Automation removes humans from the equation at many points, hence the reason it’s so popular. An automated system can decision an application in literal seconds, thus providing a quick response to the lender, the dealer, and the borrower. Lenders can see the performance of loans in their portfolio using analytics and make adjustments for future underwriting as necessary if the loans aren’t performing as expected. Analytics should provide out-of-the box reports and also allow the option to configure self-service reports that will meet the lender’s specific needs and help to further business goals.
  • Centralized processing: Some lenders choose to use multiple platforms in processing information. While this may provide flexibility with certain solutions, it also creates information silos that lead to inconsistency in decisioning. A single central solution to manage all the aspects of loan origination is necessary to ensure effective automation. 

These features provide an infrastructure for automation, though they don’t take care of the entire issue. A big factor in driving loan origination automation is the reliance on decision rules that provide enough flexibility to support business needs.


How Decision Rules Drive Loan Origination Automation


Decision rules are a big reason why modern, cloud-based loan origination solutions are so efficient. Decision rules may be used in nearly every step of the process and are the foundation for loan origination automation. Unlike legacy lending software, decision rules don’t need in-house programming skills or outside consultants to make loan origination process modifications. Instead, loan origination automation guidelines are created and managed by using configuration menus. As a result, lending professionals can easily implement and modify decision rules that reflect their unique business requirements.

Decision rules provide distinct benefits that improve not only lending efficiency but also the consistency of loan origination processes. Specifically they:

  • Eliminate manual, repetitive underwriting decisions allowing underwriters to focus their time and expertise on high-value decisions that cannot be automated.
  • Bring consistency to underwriting decisions that may otherwise vary based on the judgment and experience of the underwriter.
  • Provide a formal record of current and past decision policies in support of compliance regulations.

Decision rules can be as simple as a comparison of credit score to a minimum threshold in credit policies or as powerful as automating a deal structure by iteratively adjusting terms until they match a credit policy. 

Here’s a quick look at four examples to illustrate the versatility of decision rules in driving loan origination automation.

 


Credit Bureau Waterfall Rules 

Post-Bureau Rules for Quick Approvals or Declines

Modern loan origination systems let lenders access credit bureau data from multiple sources (Equifax, Experian, and TransUnion) using rules to create a waterfall approach. Either natively or using a system such as Digital Matrix Systems (DMS), the rules can determine whether cumulative bureau data is needed instead of a single, standard bureau data. 

Decision rules may be set to govern declines of applications after bureau reports have been pulled. Post-bureau decline rules provide decision consistency and ensure that if any rule triggers a decline, it must be waived in order to approve the application. Decision rules also allow lenders to track and analyze automated decisions. A lender can easily determine the percentage and types of loans that were declined or approved by overrides. 

Automate Tradeline Calculations

Auto Structuring 

This defines rules that determine which specific tradeline data is included in the calculation of borrower expenses. A tradeline rule can be written using any tradeline data field. For example,

When no tradeline rules are active, all open tradelines with a balance > $0 and payment > $0 will be included in the calculation.

Lenders have flexibility in determining how they want to evaluate tradeline data. Rules can be created to use actual monthly payment, percent of the balance, compare actual against percentage and use the greater of the two amounts, or to specify a fixed amount in the expense calculation. Lenders who use multiple bureaus can easily create rules to accommodate the individual bureau’s data.

Auto structuring is one of the most powerful applications of decision rules. With auto structuring, the loan origination system automatically restructures deals to match credit policies. Lenders can define the rules that determine when auto structuring will run. Multiple rules can be created to trigger it. However, only one rule needs to be triggered to initiate auto structuring. 

By iteratively applying the rules that control how the system can modify a credit policy field, auto structuring will attempt to determine a resolution. Successful resolutions can trigger an immediate or conditional approval tied to any stipulations established. Conversely, unsuccessful resolutions automatically issue an auto decline. 

Auto structuring lets lenders translate credit policies and underwriting decisions into a predictable, automated process that accelerates decision time, often allowing a lender to respond with a deal in seconds.  


Decision Rules and Compliance


Decision rules also provide an avenue for maintaining compliance by coding regulations into the system. In a configurable system, this is a process accomplished without the need for technical expertise. The program could be told to, for example, look up maximum interest rates on various tables based on the specific applicant. This information would be automatically applied when creating the offer. 

This is especially useful in instances where policies change rapidly. Rather than updating hundreds of procedures, the lender merely needs to add the revised regulation to their system. It is then applied to all applications moving forward. When appropriately used, decision rules don’t just automate decisions. They also automate compliance.


Loan Origination Automation Begins With Decision Rules


Centralized loan origination systems with robust integrations and analytics capabilities are the best support system for automation. They build the framework where the right parameters can be applied to speed decision-making while boosting accuracy. 

Decision rules that are easily created and managed with configuration menus help achieve loan origination automation. From simple binary decisions based on credit scores to complex calculations that mirror the decisions of experienced underwriters’—rules deliver speed, accuracy, and consistency in lending decisions.


Getting Started


defi SOLUTIONS  is a leading provider of loan origination solutions that incorporate the latest fintech capabilities. Take the first step toward improved lending efficiency and better decision quality by contacting our team today or registering for a demo of defi LOS.

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