It used to be that small businesses needing loans could wait weeks or months for a decision from the provider, with pre-qualification steps taking up a huge chunk of the time – and after all that, there was no guarantee that the provider would find them creditworthy.
Today, artificial intelligence can do a lot of the heavy lifting at the front end of the process. Applicants can find out within seconds whether they’ve been approved, and some can receive money as soon as the next day via ACH – all without providers lifting a finger of their own.
Headway Capital, which provides online flexible credit lines of up to $50,000 for U.S. small businesses, has learned through experience what a difference it makes to automate these early decisions.
The Chicago-based provider uses predictive analytics and digital decisioning to understand customers and make optimal decisions, mitigating fraud and risk. Many of its customers have subprime credit, so making the right decision out of the gate is a critical part of protecting its revenue and reputation.
“As we work with business customers with non-prime credit, decisions around credit risk are key to the success of our business,” said Haijian Hu, head of Headway Capital. “Without predictive analytics and digital decisioning capabilities, companies are at risk of rejecting customers worthy of credit and accepting those with a higher default risk, which can negatively impact the customer experience as well as bottom-line results.”
Since launching in 2014, Headway has implemented Colossus, a digital decisioning system by parent company Enova International. Three years later, the company says it would never use anything else. Colossus handles fully half of application pre-qualifications without human help.
“For all our customers, there’s no need to wait more than a few seconds before knowing their pre-qualified loan offer,” Hu said. “Fifty percent of the customers get an instant final loan decision after they submit required documentations. Different algorithms within the decision flow help to reduce time to customer decision like electronic bank statement data parsing models.”
Enova’s Colossus platform uses machine learning and sophisticated decision flows to make basic operational decisions related to fraud, credit risk, operations, payments, collections and marketing, such as determining whether customers are fraudulent, what their risk level is, whether Headway Capital should accept them and what kind of offer Headway Capital should extend based on risk.
After customers fill out the online application, Colossus works with other systems and third-party data to make decisions around identity verification and fraud. It then begins the underwriting process for approved applicants. At that point, live underwriters jump in and run additional reviews or verifications if they think it necessary. Finally, the completed agreement goes to the customer for review and digital signature, and the funds typically appear in their bank account within 24 hours.
Headway Capital has found Colossus not only accurate and efficient but easy to use, requiring just a single API call to implement. Whereas the last generation of solutions burdened providers with integrating multiple data sources, Enova Decisions’ Colossus corrals sources into one place.
As new models are built, they can be implemented quickly by business analysts rather than requiring a full scheduled rollout by the IT department, and machine learning technology guarantees that the technology, like fine wine, will only get better with age.
That ease of use is what Hu loves about Colossus and the reason he would recommend it to any other lender out there – plus folks in adjacent fields, from financial services to telecommunications, from insurance to higher education.
“Competing on analytics is possible for teams without technical or analytical expertise in decisioning,” Hu said; they just need the right tools.