This article was updated on January 23, 2024.
Sometimes you have to break from tradition and look to modern solutions to address modern problems. As consumers increasingly expect fast-paced digital experiences, lenders are tapping into advances in computing power to enhance their operations.
According to a 2022 Experian study, 66% of businesses believe advanced analytics, including machine learning and artificial intelligence, are going to rapidly change the way they do business.1
While some may feel wary about trusting automated systems, remember that you’re in control of the strategy. Automation comes in after to help take over monotonous and complex or error-prone tasks. As a result, you can free up resources for work that isn’t as well-suited for automation, such as analyzing results and revising strategies.
The benefits of automation within loan origination
From initial screenings to determining a final decision or credit limit, automation can offer benefits throughout the loan origination process. And lenders of all sizes are exploring opportunities for automation to help them:
- Manage an overwhelming number of applications: Lenders may be struggling to respond to an increased demand for credit, particularly if they’re also dealing with staffing shortages and rely on manual inputs and reviews. Automation can remove some of the burden from employees and lead to faster decisions.
- Increase consistency and accuracy: Transposing information from applications and making calculations by hand can result in errors or inconsistent results. Modern automated systems can help ensure information is accurate, uniform and up to date.
- Create scalable processes: Automated processes are easier to scale than a strategy that relies on consistent manual reviews and frequent back-and-forth with customers.
- Improve customers’ experiences: Fast, accurate and fair decisions make for happy customers. However, 58% don’t feel that businesses completely meet their expectations for their online experience.2 What’s more, 91% of online applications are abandoned before completion.3
More loans, a consistent scalable process and happy customers can all drive revenue growth. When integrated throughout the underwriting journey, automation can also help you increase conversion rates and expand your lending universe without taking on more risk.
What does an optimized and automated loan origination process look like?
Modern loan origination software offers flexibility, security, speed and robust integrations. These can be cloud-based systems that vendors create and manage on your behalf, or lenders that have the resources and capabilities may be able to bring (or build) them in house.
Automating parts of your origination process can save you time and money, but you have to start with a specific strategy. For example, you might consider your model’s outputs and decide on denial and approval cut-off points — you can then automate those approvals and denials. You can also test, revise, and optimize strategies based on your desired results.
Let consumers apply when and how they want, even if it means pausing part-way through and continuing on a different device later. Remove potentially time-consuming steps by letting consumers upload and sign documents digitally, and use AI-driven automated systems to review the documents for accuracy.4
Integration with various data sources
You need good data—and lots of it—to get the most out of an automated system. Some platforms can automatically connect and use internal data alongside third-party data sources, such as alternative data, credit bureau data and credit attributes.
Identity, income and fraud checks
Automated platforms can work with verification tools to quickly confirm the applicant’s employment and income, confirm their identity and perform fraud checks. The process can take minutes rather than days or weeks, letting you quickly move applicants through to the next stage of the process.
Decisions based on optimized models
Automated decision engines use your strategy and the available data to quickly return a decision. Machine learning models can score consumers who aren’t scorable by traditional credit models, expanding your potential customer base while furthering financial inclusion goals. They can also more accurately score applicants and narrow the band (and potentially the number of applications) that requires manual reviews.5
Automation in action: Atlas Credit, a small-dollar lender, wanted to modernize its lending with customized and automated systems. Experian helped them build a custom machine learning credit risk model and optimized their decision strategy and cutoffs. The results exceeded Atlas Credit’s goals, and the company nearly doubled their loan approval rates while decreasing risk losses by 15 to 20 percent.
Automated, fast decisions based on machine learning and AI analytics might raise some compliance flags—but we’ve moved beyond black box models. You need to be aware of and follow all the applicable regulations, and you can use AI and machine learning in precise ways to increase your efficiency while having fully explainable and compliant results.
Experian’s automated offerings build on a history of success
Experian has decades of experience helping lenders make accurate and timely credit decisions, and our flexible loan origination system can help you automate originations while managing risk.
It starts with good data. While we’re known for our consumer credit database that has information on over 245 million consumers, Experian can also give lenders access to alternative data, including alternative financial services, rental payment data and consumer-permission data. And we know how to incorporate your internal data to create strategies that will further your specific goals.
From marketing to collections, our integrated offerings can help you use the data to automate and optimize decisions across the entire customer life cycle. And whether you want to take the reins or tap our data scientists for their expertise, there are options to fit your needs.
1Experian (2022). Explainability: ML and AI in credit decisioning
2Experian (2022). North America findings from the 2022 Decisioning Survey
3Experian (2023). eBook: The Ultimate Guide to Competitive Growth
5Experian (2022). Driving Growth During Economic Uncertainty with AI/ML Strategies