MonJa: Features to Look for in Lending Software

12 Features to Look For in Lending Software

In Commercial Lending, Featured, Small Business Loan Underwriting, Underwriting Automation by Yulia GnatyukLeave a Comment

5 Minutes Read.

Lending software that automates loan underwriting can greatly reduce friction points in the lending process. The benefits of faster, more efficient processing, however, should not compromise sound lending guidance. Software can reduce underwriting to an automated process according to pre-set guidelines, but there may be areas where automated underwriting is insufficient. Lenders must balance process optimization with the need for manual review in certain situations. Choosing the right lending software is critical for maximizing both automated and manual processes.

Lending software versus true automated underwriting

MonJa: Features to Look for in Lending Software

Lending software has become quite commonplace, particularly with the growth of mobile applications and online financial services. While automated underwriting systems are a form of lending software, not all lending software has underwriting capabilities. Basic lending software can be used to reduce some of the friction points in the lending process and improve the customer experience.

Common lending software features include:
1. Web and mobile app interfaces.

This is where customers can view various loan offers, calculate estimated payments, submit loan applications and view the status of their loan requests.

2. Document and data management features.

It is extremely important for them to integrate with the customer’s other accounts and keep the information in a centralized database.

3. Organized customer loan account data.

Important for easy review and audit.

In the wake of the financial crisis of 2008, many lenders preferred to limit automation of their lending processes. And some still do. In subprime lending, in particular, lending software is often used only for information handling tasks, but underwriting is left to human expertise.

The rationale for this is that some lenders are more comfortable with human judgment of factors contributing to low credit scores. Some customers that are otherwise a low risk might be bypassed if assessed solely on the basis of credit score plus the loan-to-value ratio. Automated underwriting, by contrast, removes human judgment from the equation.

Like other lending software programs, automated underwriting programs also reduce the manual work involved in the lending process, such as document collection and verification.

So what are the most important features of automatic underwriting systems?
1. The ability to analyze hundreds of data points quickly.

Ability to analyze data fast becomes far more important, compared to conventional credit-scoring models.

2.Programmable credit scoring guidelines. 
3. AI-driven machine learning capabilities

AI and ML capabilities are important in order to, for example, refine the credit scoring system according to data patterns the system detects.

Other automated underwriting features

When considering the available options in automated underwriting programs, there are a number of key features to look for. Not all automated underwriting systems are the same, but in general, a particular system will probably be a good fit if it offers the following benefits:

1. Flexibility. 

This says as much about the capabilities and potential support from the vendor as it does about the program itself. The systems offered should be capable of effectively managing any sort of lending, from consumer and business loans to real estate and auto loans.

2. Integration and ease of deployment.  

Because the automated underwriting program is intended to allow more efficient use of in-house expertise rather than replacing it.  The system should integrate easily with existing systems. It should be deployable within a reasonably short period of time for training and familiarization.

3. Scalability.  

The automated underwriting program and accompanying vendor support should be able to expand with increasing business volume seamlessly.

4. AI-driven risk algorithm.  

The use of AI is considered state of the art, because of the number of data points an effective automated underwriting system has to manage. With machine learning, the system can improve its efficiency with increasing use, a critical capability for managing increasing loan volume without increasing individual loan processing time.

5. Customizable credit scoring

Automated underwriting programs are equipped with credit scoring models, and also allow for the lender’s own credit scoring and risk management standards to be included. A flexible solution enables the lender to use the included credit scoring model, the lender’s own credit scoring system, or a combination of both.

6. Measurable productivity gains.  

The automated underwriting program vendor should provide objective measures for gains in loan origination volume, reductions in processing times and reductions in manual document processing.

Incorporating manual review guidelines

Although automated underwriting programs can handle the majority of loan applications, there will inevitably be cases where manual review is prudent. Some lenders and analysts have even suggested that complacency, or over-reliance on automated underwriting, particularly in the subprime mortgage industry, may have contributed to the 2008 financial crisis.

Lenders using automated underwriting programs should carefully evaluate their credit scoring standards before integrating them into the software system. “Red flags” that would cause a loan application to be set aside for additional review according to credit and risk standards under manual underwriting can be incorporated into the system, so that problematic applications can be scrutinized. This prevents unfair rejections or acceptance of applications, and allows skilled underwriters to focus their attention where it is most valuable.

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