NLP-based detection of systematic anomalies among the narratives of consumer complaints

arXiv:2308.11138v3 Announce Type: replace-cross
Abstract: We develop an NLP-based procedure for detecting systematic nonmeritorious consumer complaints, simply called systematic anomalies, among complaint narratives. While classification algorithms are used to detect pronounced anomalies, in the case of smaller and frequent systematic anomalies, the algorithms may falter due to a variety of reasons, including technical ones as well as natural limitations of human analysts. Therefore, as the next step after classification, we convert the complaint narratives into quantitative data, which are then …

abstract algorithms arxiv case classification consumer cs.cl detection nlp q-fin.rm stat.me stat.ml type