Organizations in the ARM industry have embraced the use of digital channels to not only communicate with customers, but to also improve the collections process. But that is just the first step. Organizations must also leverage artificial intelligence to identify and contact the highest-potential accounts at the most opportune time by leveraging machine learning algorithms.
Knowledge is power
The better you know your customers, the better you can serve them. That’s not an earth-shattering revelation. Organizations spend a significant amount of time and budget to do just that. What they’ve discovered is that consumers prefer to be treated as individuals and in a way that is relevant and tailored to their preferences.
To provide this kind of personalization, organizations need to dig a little deeper to understand consumers’ preferences. With a better understanding of how consumers prefer to communicate and pay, you can improve consumer engagement and operational efficiencies to drive revenue growth.
This data is also critical to drive your digital strategies. For example, organizations often focus on digital natives – those who grew up online, using computers, tablets and smartphones practically since they were born. However, that’s a little short-sighted.
According to a recent survey, consumers 55 years and older are more comfortable paying bills online than their younger counterparts. These consumers, sometimes referred to as baby boomers, have adapted to the digital era and continue to take advantage of the convenience of conducting business and paying bills online.
The same study also confirms that education level impacts communication and payment preferences. The higher the level of education in U.S. adults, the more comfortable they are with communicating through digital channels. For example, a large gap exists in the percentage of those who prefer to receive payment reminders and billing statements via email for those who have a high school diploma or less versus those who have a bachelor’s degree.
Survey data, such as this, is helpful in getting to know your customers. But this type of static data only paints part of the picture. To get a complete look at your customers, you need more. And you can use technology to get it.
Better to know you with
ARM organizations focus the most time and effort on the accounts that are most likely to pay. Traditionally, they determine this using the scores from credit reports. Yet, this type of static data can’t be updated in real-time and only gives organizations a limited view of the customer.
Organizations need to leverage dynamic scoring models that can be updated in real-time to get a more accurate look at their customers.
Machine learning (ML), one kind of artificial intelligence (AI), can help with this when combined with historical data along with alternative data sources, such as spending behavior, social media activity, online presence, and more.
This ongoing process of gathering and evaluating data provides a more holistic view of consumer behavior. And that can provide huge benefits.
The proof is in the pudding
An advanced segmentation solution that uses ML can breathe new life into your portfolios and increase the value of accounts you might not be working today. The algorithms that drive decision-making and guide account work are easily understandable and “explainable,” alleviating collectors’ and regulators’ concerns around disparate impact.
But don’t take my word for it. Organizations that have incorporated a solution that uses advanced segmentation have reported:
- More than a 50% increase in revenue per call
- More than a 20% increase in right party contact rate
- More than a 40% increase in average yield per account
- A 50% increase in overall collections.
Agencies that embrace the digital technology that allows them to better understand and connect with their consumers will quickly set themselves apart from the competition.