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3 Advantages of Automating Loan Processing and Decisioning

3 Advantages of Automating Loan Processing and Decisioning

by Origence

Changing member expectations call for new conveniences, and new technological solutions will help credit unions further their future success.

 

In today’s digital-first world, lenders are striving to create a better, faster, more frictionless experience for their members. Changing customer expectations calls for new customer conveniences, such as the ability to complete membership or lending applications online and receive a decision in minutes.

 

Providing an outstanding digital member experience — from origination to onboarding — is at the heart of how credit unions will further their success in the immediate future. Pressure from fintechs, a fickle economy, and the rapidly changing technology landscape are driving credit unions to adopt new technological solutions. Automating loan processing and decisioning is one of those solutions that can help credit unions benefit the most.

 

How Automation Helps

For credit unions, there are three advantages to implementing automated loan processing and decisioning.

 

1.      Improved Efficiency. Credit unions are always searching for ways to fund more loans and make faster decisions. What if there were a way to provide faster decisions along with higher approval rates without increasing your appetite for risk? That’s what automation helps achieve while simultaneously improving processes and reducing underwriting costs.

2.      Accuracy. Credit unions have historically been reluctant to embrace high levels of automated decisioning, but it can actually improve decision-making. In fact, we have seen AI machine learning increase approvals by up to 25% without a corresponding increase in risk.

As part of automation in processing and decisioning, AI engines can achieve 99% accuracy rates while guarding against fraud and ensuring compliance. Automated document processing has been shown to reduce human error and fraud risk while helping credit unions provide their members with a more frictionless loan origination experience.

Automation means speed and the ability to process more loans with fewer points of friction. Even better, for credit unions that need to expand their network of dealer relationships, automation helps deliver faster funding.

3.      Improved Digital Experience. How many opportunities are lost simply because an applicant is asked for redundant information or details the lender should already know? Alternatively, how quickly are disruptors like Carvana moving to fill the gaps that tradition-bound credit unions sometimes struggle to match? Meeting and beating competitors with new digital conveniences is one of the key challenges credit unions face.

 

Putting A Program In Place

Credit unions have often been late adopters when it comes to automation and auto decisioning. Whereas finance apps and global banks offer cutting-edge technology, credit unions take pride in offering member service with a personal touch. But those two forces no longer need to be at odds. The next generation of automation and decision solutions includes configuration capabilities designed to meet specifications and needs.

 

Credit unions can use automated loan processing and decisioning to accelerate approvals in specific scenarios while creating automatic rejections for others. These configurations create flexibility to adjust programs to specific risk factors and changing economic situations. Scoring models and risk factors can always be altered, so credit unions gain better control of their output.

 

Simply put, automated loan processing and decisioning create a system that assesses relevant information and data related to the applicant, allowing a quick credit decision. The credit union controls the setup of the decision engine and uses the champion challenger to apply decision variables to a set of loans to determine how decisions would be rendered. This enables the team to quickly review and deploy automation, then reap the benefits of increased efficiency and accuracy.

 

In the future, the models will continue to improve as the technology is refined and more data is gathered. Already, risk-based pricing models can account for how various borrowers with the same credit score can have dramatically varied default frequencies. AI models are able to parse through remarkably vast amounts of data in seconds. They can find variances that humans cannot — at least not without several months of painstaking research.

 

For more information about how to implement automated loan processing and decisioning, contact Origence.