Are You for Real? Detecting Identity Fraud via Dialogue Interactions

Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing, pages 1762–1771, Hong Kong, China, November 3–7, 2019. c⃝2019 Association for Computational Linguistics 1762 Are You for Real? Detecting Identity Fraud via Dialogue Interactions Weikang Wang1,2, Jiajun Zhang1,2, Qian Li3, Chengqing Zong1,2,4 and Zhifei Li3 1 National Laboratory of Pattern Recognition, Institute of Automation, CAS, Beijing, China 2 University of Chinese Academy of Sciences, Beijing, China 3 Mobvoi, Beijing, China 4 CAS Center for Excellence in Brain Science and Intelligence Technology, Beijing, China {weikang.wang, jjzhang, cqzong}@nlpr.ia.ac.cn {qli, zfli}@mobvoi.com Abstract Identity fraud detection is of great importance in many real-world scenarios such as the finan- cial industry. However, few studies addressed this problem before. In this paper, we focus on identity fraud detection in loan applications and propose to solve this problem with a novel interactive dialogue system which consists of two modules. One is the knowledge graph (KG) constructor organizing the personal infor- mation for each loan applicant. The other is structured dialogue management that can dy- namically generate a series of questions based on the personal KG to ask the applicants and determine their identity states. We also present a heuristic user simulator based on problem analysis to evaluate our method. Experiments have shown that the trainable dialogue system can effectively detect fraudsters, and achieve higher recognition accuracy compared with rule-based systems. Furthermore, our learned dialogue strategies are interpretable and flexi- ble, which can help promote real-world appli- cations.1 1 Introduction Identity fraud is one person using another person’s personal information or combining a few pieces of real data with bogus information to deceive a third person. Nowadays, identity fraud is becoming an increasingly prevalent issue and has left many financial firms nursing huge losses. Besides, for persons whose identities have been stolen, they may receive unexpected bills and their credit will also be affected. Although identity fraud is a very serious problem in modern society, there are no effective fraud detection methods at present and little attention has been paid to this problem. Intuitively, a simple way to detect identity fraud in loan applications is directly asking applicants 1https://github.com/Leechikara/ Dialogue-Based-Anti-Fraud Nanjing University Baidu No.3 Gulou Street The fake personal information of a loan applicant: System: When was Nanjing University founded? Applicant: I am not sure. System: Which is the nearest subway station to Nanjing University? Applicant: I am not quite clear. Decision: Fraud (Correct) System: Which university did you graduate from? Applicant: Nanjing University. System: Which company do you work for? Applicant: Baidu. System: Where do you live? Applicant: No.3 Gulou Street. Decision: Non-Fraud (Wrong) School Company Residence Figure 1: Dialogue examples of two possible fraud de- tection methods. The first one is directly asking appli- cants about their personal information. The second one is asking applicants about questions that are related to their personal information. about their personal information. However, as shown in Fig. 1, this method is prone to errors because fraudsters may well …

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