Transformation of the Accounting Function in Supply Chain Finance Innovation in the Perspective of Intelligent Algorithms

Abstract

In the era of artificial intelligence, the transformation and reshaping of financial functions have become inevitable for the development of the accounting industry. Based on the background of the intelligent era, the study analyzes the transformation of the accounting function in supply chain finance and integrates intelligent algorithms to showcase their application in the accounting function. We construct the enterprise credit risk assessment model based on RAGA-PP, combining the evaluation index system and the accelerated legacy algorithm to optimize the projection tracing model. Then, using the XGBoost model, design the method for identifying corporate financial fraud. Empirical analysis reveals that the sample enterprises’ average projection value is 0.8277, indicating a medium-high credit risk, thereby confirming the feasibility of the RAGA-PP model. The XGBoost model exhibits superior stability and recognition accuracy in identifying financial fraud, with its fitness value and loss value reaching 0.483 and 0.688, respectively. Its recognition accuracy surpasses that of comparative algorithms by 12.23% to 14.43%. With the support of intelligent algorithms, supply chain finance can use intelligent models to assist in management and decision-making and provide more value for enterprises.

Keywords

• projection seeking model
• accelerated genetic algorithm
• xgboost model
• credit risk assessment
• financial fraud identification
• accounting function transformation
• 91g50