How the Digital Age Could Shape Collection Strategy in the Coming Years

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We live in the Age of Information.

Humans produced 2.5 quintillion bytes of data per day in 2017, according to IBM, and it is often said that humans have generated 90% of the data in the world in the last three years alone. This data is generated through people’s purchasing behaviors, web searches, social media posts and digital messaging, among other digital things.

In 2015, more than 3.5 million text messages were sent every minute, according to a July report from Domo, but in 2016, it grew to around 15.2 million texts, a 334% increase. More vehicles will join this digital ecosystem, which means that the auto finance industry needs continue march in step with the advancing digital age, as well.

So which part of a vehicle’s lifecycle are still lacking advancement in digital technology? On the front-end, customers can already use e-signatures for e-contracts, purchase and finance vehicles (almost) entirely online, and in some cases, dealerships have become sleek digital hubs instead of cumbersome things. But collections practices are still lacking where manual activities, judgment-driven decisions, disconnected actions, and siloed processes can make collections seem antiquated.

Building a nimble yet robust collection strategy doesn’t have to be like climbing Mount Everest. Understanding how collection practices stack up is as simple as asking questions about the customer and employee experience according to a 2016 report from Deloitte. Questions such as, “does your call center staff have access to intuitive dashboards with a single customer view with all the relevant information?” “Does your collections platform allow customers to go from your email reminder to a direct debit instruction on your website within a couple of clicks?” “Is your collections platform flexible enough to enable your analytics team to test and adapt strategies within a few hours?”

The Center for Auto Finance Excellence has harped about artificial intelligence and machine learning before, but it’s true that this kind of software can almost entirely replace the manual processes. Telrock, a global technology provider of SaaS-based collections platforms, in a new whitepaper said AI and automation creates a “frictionless intra-operative ability,” which is to say that the same technology can be applied across a series of collections functions. For example,  filling in missing information by downloading data from several source systems, creating charts in Excel and formatting PowerPoint slides or modeling customer behavior that can be automated and performed overnight.

Short message service (SMS) software which includes web chats and text messages, is another piece of the digital world that can make significant changes for collections.

“The goals of collections platforms ten years ago were to empower the collector and automate processes. The goal of some current systems is to automate negotiations and embed self-service at the heart of the process,” the Deloitte report says.

Payix, which participated in the Auto Finance Innovation 2018 DEMOvation, is one such collection service that provides a mobile app and other collections tools – including a borrower web portal, interactive voice response, text-pay solutions, as well as a client administration portal to provide lenders and auto dealers with control of their payment channels.

Predictive behavioral models, including knowing when the best time to contact someone and using what messaging system, can also help with modernizing your collection strategies. Ask yourself questions like, what’s the propensity of a customer being contactable, and of their responding? Which customers are likely to respond to collections activity? In response to
what? And over what time period?

“The future of the collections industry lies within a mathematical science that leverages alternative, personal data to determine the probability of debt repayment,” said Mark Luber, leader of data analytics teams for receivables management strategy for LexisNexis. “The efficiency of predictive analytics comes through the application of the non-traditional data.”

Overall, the collection environment has become extremely dynamic and highly demanding and over time the companies that have more advanced systems will do better than those without. And with more subprime delinquencies on the rise, it’s a moment for lenders to show they have what it takes to stay strong.

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