GF Securities

Investment banking is the primary business of securities companies, and risk management is the core competency of financial institutions. The failure to promptly identify corporate financial anomalies can bring significant business risks to securities firms. Therefore, finding suitable methods for early warning of financial anomalies has always been one of the main tasks of securities companies. Previously, related methods were based on manual identification, decision models, or machine learning models, but the main issue was the difficulty in improving accuracy.

The application of the Pangu Large model in the field of financial anomaly warning has significantly improved the accuracy of financial anomaly detection, raising it from the previous range of 50% to 79% up to 90%. This greatly enhances the usability of AI in the field of financial anomalies and substantially strengthens the risk management capabilities of financial institutions.