[vc_row][vc_column][vc_column_text]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 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
[/vc_column_text][vc_single_image image=”8653″ img_size=”large” alignment=”center”][vc_column_text]Lending software has become quite commonplace, particularly with the growth of mobile applications and online financial services. Yet 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 lending software to integrate with customers’ other accounts in order to keep their 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. Some still do. Lending software, particularly in subprime lending, is often only used for handling information, while underwriting is left to human expertise.
In truth, some lenders are more comfortable with manual investigation of factors contributing to low credit scores. Assessing customers solely on the basis of credit score and loan-to-value ratio might disregard customers that are classified as low risk by the numbers.
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.
The ability to analyze data quickly is becoming far more important, in contrast to conventional credit-scoring models.
2. Programmable credit scoring guidelines.
3. AI-driven machine learning capabilities
AI and ML capabilities are important for tasks such as refining the credit scoring system according to detected data patterns.
Other automated underwriting features
[/vc_column_text][vc_single_image image=”8663″ img_size=”large” alignment=”center”][vc_column_text]When considering use of 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 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.
The automated underwriting program is intended to utilize in-house expertise more efficiently rather than completely replacing it. The system should easily integrate with existing systems. Furthermore, 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 enormous number of data points an automated underwriting system is able to manage. With machine learning, the system improves its efficiency over time, 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 measurements of loan origination volume, processing times and 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 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. Systems can “red flag” problematic applications for additional review according to credit and risk underwriting standards. This prevents unfair rejections or acceptances of applications, and allows skilled underwriters to focus their attention where most needed.
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