Fraud analytics: a research

IF 2.4 Q2 ECONOMICS
B. Baesens
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引用次数: 1

Abstract

ABSTRACT Fraud is as old as humankind and appears in many types and forms. Popular examples are credit card fraud, tax evasion, identity theft, insurance fraud, counterfeit, click fraud, anti-money laundering, and payment transaction fraud. In earlier research we defined fraud as an uncommon, well-considered, imperceptibly concealed, time-evolving, and carefully organized crime. Nowadays, fraud is typically tackled using state-of-the-art analytical techniques with many accompanying challenges. It is the purpose of this article to highlight twelve research topics (RTs) that we believe prioritize high on the agenda of contemporary fraud analytics models. We do this by reviewing fraud analytics from a data, model, performance, and deployment perspective.
欺诈分析:一项研究
欺诈与人类一样古老,有多种类型和形式。常见的例子有信用卡欺诈、逃税、身份盗窃、保险欺诈、假冒、点击欺诈、反洗钱和支付交易欺诈。在早期的研究中,我们将欺诈定义为一种罕见的、经过深思熟虑的、难以察觉的、随时间演变的、精心组织的犯罪。如今,欺诈通常是使用最先进的分析技术来解决的,伴随着许多挑战。本文的目的是强调十二个研究主题(RT),我们认为这些主题在当代欺诈分析模型的议程上占有重要地位。我们通过从数据、模型、性能和部署的角度审查欺诈分析来做到这一点。
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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来源期刊
CiteScore
4.50
自引率
5.00%
发文量
22
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