Variables Creation in Fraud Detection-Based on New York Property Data

DOI

10.2991/icesed-19.2020.18How to use a DOI?

Keywords

Fraud detection, Machine learning, Fraud analysis, Variables.

Abstract

With the rapid development of technology, fraud has become an extremely serious problem in the US society, therefore makes fraud detection an urgent need to improve the situation as much as possible. Fraud detection refers to the process of finding anomalies in a huge bunch of data by building fraud algorithms and models that could predict the possible behaviour of the real world situation. This paper will mainly focus on the ‘Variables Creation’ process in fraud detection with the New York property data and discuss how to analyze a fraud problem and build variables based on New York property data. The whole process of fraud detection will render practical help to solve the property fraud problem.

Copyright

© 2020, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Yutong Yao
PY  - 2020/01
DA  - 2020/01
TI  - Variables Creation in Fraud Detection-Based on New York Property Data
BT  - Proceedings of the 2019 International Conference on Education Science and Economic Development (ICESED 2019)
PB  - Atlantis Press
SP  - 299
EP  - 307
SN  - 2352-5428
UR  - https://doi.org/10.2991/icesed-19.2020.18
DO  - 10.2991/icesed-19.2020.18
ID  - Yao2020/01
ER  -