Credit anti-fraud method, system, apparatus and computer-readable storage medium

Abstract

The invention discloses a credit anti-fraud method, which comprises the following steps: when a credit core body call is detected, obtaining the risk level of the current core body customer, and obtaining the voice data of the customer collected in the process of the credit core body call; Determining a target anti-fraud strategy according to the risk level, wherein the target anti-fraud strategyis one or more of voiceprint anti-fraud strategy, voice anti-fraud strategy, light voice anti-fraud strategy, background voice anti-fraud strategy and voice emotion anti-fraud strategy; According to the customer voice data and the target anti-fraud strategy, performing an anti-fraud identification operation to obtain an anti-fraud identification result of the current core customer. The invention also discloses a credit anti-fraud system, a device and a computer-readable storage medium. The invention can improve the identification rate and coverage rate of fraud and reduce the credit risk.

Description

technical field [0001] The invention relates to the field of anti-fraud, in particular to a credit anti-fraud method, system, equipment and computer-readable storage medium. Background technique [0002] When financial companies carry out credit review work, they need to review whether credit applicants have fraud risks, but the accuracy and efficiency of manual review cannot be guaranteed. For this reason, major financial companies have developed anti-fraud systems, which can help financial companies Institutional targeting identifies fraudulent customers and events. With the rapid development of artificial intelligence, anti-fraud has developed from manual identification to intelligent algorithm identification, which not only reduces labor costs, but more importantly improves the accuracy and recall of anti-fraud, and ensures the stability of anti-fraud Consistent with the standard. [0003] At present, fraudulent customers and events are mainly identified based on face ...

AI Technical Summary

Problems solved by technology

[0003] At present, fraudulent customers and events are mainly identified based on face recognition technology and voiceprint recognition technology, which has improved the fraud recognition rate to a certain extent. There are loopholes in the system, and the loopholes are used to conduct fraud in an attempt to deceive financial institutions. However, the existing anti-fraud methods cannot identify all fraudulent customers and events, and the coverage of fraud identification is low.

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