Modernizing Utility Collections through Customer Analytics and AI

Gus Wigen-Toccalino, Brian Baids, Abby Hutson-Comeaux
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Abstract

The 2020 COVID-19 pandemic introduced economic calamity and uncertainty in America that had not been seen since the 2007–2008 financial crisis. What began as an uncertain period for individual well-being soon translated into broader economic issues for the American economy. Businesses facing months of lost revenue, deficits, and uncertainty began weakening financially and, as a result, were forced to reduce staff. In the years that have followed, industries which have historically been able to count on stable revenue, such as utilities, particularly suffered. Struggling households and small businesses began missing consecutive monthly payments, and customer debt climbed to unprecedented levels. As of March 2023, “one in six households across the country were behind on their electric bills.”1 Additionally, instances of non-residential customers falling behind on their payments emerged. Historic levels of arrears continue to mount pressure on the industry, and traditional approaches to arrear collection are not working.

通过客户分析和人工智能实现公用事业收款现代化
2020 年 COVID-19 大流行给美国带来了自 2007-2008 年金融危机以来从未有过的经济灾难和不确定性。一开始是个人福祉的不确定时期,很快就转化为美国经济的更广泛的经济问题。面临数月收入损失、赤字和不确定性的企业开始出现财务疲软,并因此被迫裁员。在随后的几年里,公用事业等历来收入稳定的行业尤其受到影响。陷入困境的家庭和小企业开始连续拖欠月供,客户债务攀升至前所未有的水平。截至 2023 年 3 月,"全国每六户家庭中就有一户拖欠电费 "1 。历史最高水平的欠费继续给电力行业带来压力,而传统的欠费催收方法已无法奏效。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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