Accounts Receivable Management (ARM) is a fast-moving, ever-evolving industry. Decisionmakers must possess a comprehensive understanding of creditor client markets, workforce trends, and the latest operational & technological systems to stay competitive.
- Debt Levels
- The amount of debt available for collection has fluctuated throughout the years. Total household debt has grown precipitously since 2000, with the total volume outstanding nearly tripling from $5.2 trillion in Q1 2000 to $15.2 trillion in Q3 of 2021.
- To gain a better understanding of potential business opportunities – placements – available to ARM firms, Kaulkin Ginsberg estimated the level of bad debt (i.e., debt that creditors deem “uncollectible”) in various relevant market sectors from 2000 to 2020.
- After bottoming out in 2014, total bad debt gradually ascended to $480 billion in 2019, indicating that ARM-related opportunities increased as well. In 2020, bad debt drastically declined to $400 billion – a decrease of 16.7% from the previous year – thereby indicating a resultant drop in placement levels.
- This was mostly driven by a 39.9% drop in student loan bad debt – to $100.3 billion – which was brought about by CARES Act forbearance measures that allowed a significant portion of federal student loan borrowers to avoid delinquency.
- At the onset of the COVID-19 pandemic, ARM companies were forced to move some or all of their workforce to a work-from-home (WFH) model within a very short period of time. Impressively, many agencies managed to implement WFH effectively despite having little previous experience with it. While WFH poses certain operational obstacles, the increased flexibility and productivity it gives employees may induce some agencies to incorporate it for at least a portion of their employees on a permanent basis.
- Many ARM executives Kaulkin Ginsberg spoke to while compiling this report mentioned hybrid schedules – in which an employee works half of the week at home and the other half in the office – as a viable WFH solution going forward.
- Artificial Intelligence and Machine Learning
- Artificial Intelligence (AI) – i.e., software that has the ability to “think” – and Machine Learning (ML) – an application of AI that can learn autonomously – are becoming the next big technological revolution.
- Gartner, Inc., a global research and advisory firm that specializes in information technology, projects that AI systems and augmentation will generate roughly $4.4 trillion in global business value by 2025. By 2022, “one in five workers engaged in mostly non-routine tasks will rely on AI to do [their] job”, according to Gartner. For an industry as labor-intensive as ARM, this presents significant implications.
Estimates of Bad Debt, by Market Segment
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 “Difference between Machine learning and Artificial Intelligence.” GeeksforGeeks, 27 Jan. 2022, https://www.geeksforgeeks.org/difference-between-machine-learning-and-artificial-intelligence/.
 “Gartner Says AI Augmentation Will Create $2.9 Trillion of Business Value in 2021.” Gartner, Aug. 2019, https://www.gartner.com/en/newsroom/press-releases/2019-08-05-gartner-says-ai-augmentation-will-create-2point9-trillion-of-business-value-in-2021.