Design and Development of Financial Fraud Audit System Based on Big Data Technology

Binglan Meng

2022

Abstract

Based on the combination of big data technology and financial fraud audit, Hadoop framework, Relief algo-rithm under data mining technology, Logistic, SVM and Random Forest classifier are combined to complete the sample data feature acquisition and financial fraud identification model construction, and the financial fraud audit system is packaged and published in Python language environment. The system is presented in the form of Web, which is convenient for auditors to query all kinds of financial data or non-financial data, identify fi-nancial fraud and assess the risk of financial fraud through simple and convenient operation. It provides com-prehensive application solutions for the problems of complexity, concealment, difficulty and risk in the audit of financial fraud in the data age.

Paper Citation

in Harvard Style

Meng B. (2022). Design and Development of Financial Fraud Audit System Based on Big Data Technology. In Proceedings of the 1st International Conference on Public Management, Digital Economy and Internet Technology - Volume 1: ICPDI; ISBN 978-989-758-620-0, SciTePress, pages 378-381. DOI: 10.5220/0011737600003607

in Bibtex Style

@conference{icpdi22,
author={Binglan Meng},
title={Design and Development of Financial Fraud Audit System Based on Big Data Technology},
booktitle={Proceedings of the 1st International Conference on Public Management, Digital Economy and Internet Technology - Volume 1: ICPDI},
year={2022},
pages={378-381},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011737600003607},
isbn={978-989-758-620-0},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 1st International Conference on Public Management, Digital Economy and Internet Technology - Volume 1: ICPDI
TI - Design and Development of Financial Fraud Audit System Based on Big Data Technology
SN - 978-989-758-620-0
AU - Meng B.
PY - 2022
SP - 378
EP - 381
DO - 10.5220/0011737600003607
PB - SciTePress