Identification on Financial Fraud by Companies Using the Logistic Regression Model - Tumbel, Noldin Jerry (Pascasarjana STIE Amkop Makassar, 2024)
Financial fraud by companies has a negative effect on the trust and loyalty of all stakeholders as well as market efficiency in allocating assets. This study aims to identify financial fraud in a rapidly developed manner, using the Logistic Regression Model to build an index system. Chinese companies listed in the China Stock Market & Accounting Research database were the focus of the investigation; the following industries were excluded: J67 (capital market services), J68 (insurance industry), J69 (other financial industries), J66 (other financial industries except monetary and financial services). The investigation will take place between 2017 and 2020. A total of 53 fake businesses and 53 legitimate Chinese businesses are included in the data sample. Based on the research results, the total prediction accuracy value of the model is 83%. To improve the effectiveness of financial fraud identification from technology boothsKeywords: cryptocurrency fraud, financial statement, investment activities, logistic regression model