Available at: https://ssrn.com/abstract=4847870 or http://dx.doi.org/10.2139/ssrn.4847870
Abstract:
This paper examines the role of artificial intelligence (AI) in facilitating the non-judicial collection process of delinquent consumer debt. Leveraging a randomized field experiment in the Netherlands, we show that algorithmic calling decisions achieve higher repayment rates with fewer collection calls compared with human collection officers. Uncovering the black box of AI, we find that it extracts predictive signals from unstructured notes compiled by collectors. These signals not only predict whether the delinquent borrowers would repay during the non-judicial collection process, but also shed light on the underlying motivations or impediments of delinquent borrowers' repayment behavior.
Commentary:
While this research looks to increase the efficiency of debt collection through the use of AI, it does also provide valuable insights for human consumer bankruptcy attorneys, because the motivations of consumers in filing bankruptcy is generally just the flip side of the same coin from encouraging repayment by debt collectors. That "discussions on non-repayment consequences'' (an anodyne description to say the least) between debt collectors and consumers has little impact on repayment might indicate that similarly such conversations would not otherwise exacerbate a consumer's fears sufficiently to overcome other impediments to filing bankruptcy.
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