Financial whitewash, as the behaviour of enterprises to conceal their true operating conditions through manipulation of financial data, not only undermines market fairness, but also increases the systemic risk faced by investors. The traditional method of relying on financial ratio analysis has obvious limitations in dealing with the complex, changing, and hidden means of financial modelling. For this reason, this paper constructs a financial index whitewash identification dataset applicable to the financial sector based on the machine learning perspective, and proposes an LSTMM model that integrates the long and short-term memory network (LSTM) and the multilayer perceptual machine (MLP) for the identification study.In terms of data construction, this paper is based on public violation cases and multi-dimensional financial data, screening out the whitewash and non-whitewash samples, and combining the enterprise history and industry comparison data to form the indicator dataset with time-series characteristics. In terms of modelling, the LSTMM model integrates the temporal feature extraction capability of LSTM with the nonlinear representation advantage of MLP, which significantly improves the recognition accuracy and stability. The experimental results show that the proposed method outperforms the traditional model in a number of performance indicators, which validates its application value in financial whitewash identification.This study provides an effective method for intelligent analysis and anomaly detection of financial data, which is of practical significance for improving the level of financial regulatory technology and market risk prevention and control capability.

Xinyi Jiang. Construction and LSTMM Modelling of Financial Indicator Glittering Dataset for Financial Sector from Machine Learning Perspective. Machine Learning Theory and Practice (2025), Vol. 5, Issue 1: 44-52. https://doi.org/10.38007/ML.2025.050105.

[1] Ren B. Research Progress of Content Generation Model Based on EEG Signals[J]. Journal of Computer, Signal, and System Research, 2025, 2(4): 97-103.

[2] Liu Y. The Impact of Financial Data Automation on the Improvement of Internal Control Quality in Enterprises[J]. European Journal of Business, Economics & Management, 2025, 1(2): 25-31.

[3] Hua X. Optimizing Game Conversion Rates and Market Response Strategies Based on Data Analysis[J]. European Journal of AI, Computing & Informatics, 2025, 1(2): 37-43.

[4] Zhou Y. Research on the Innovative Application of Fintech and AI in Energy Investment[J]. European Journal of Business, Economics & Management, 2025, 1(2): 76-82.

[5] Huang J. Resource Demand Prediction and Optimization Based on Time Series Analysis in Cloud Computing Platform[J]. Journal of Computer, Signal, and System Research, 2025, 2(5): 1-7.

[6] Sheng C. Research on AI-Driven Financial Audit Efficiency Improvement and Financial Report Accuracy[J]. European Journal of Business, Economics & Management, 2025, 1(2): 55-61.

[7] Zhang Q. Research on AI-Driven Advertising Optimization and Automated Decision System[J]. European Journal of Business, Economics & Management, 2025, 1(2): 62-68.

[8] Xu D. Design and Implementation of AI-Based Multi-Modal Video Content Processing[J]. European Journal of AI, Computing & Informatics, 2025, 1(2): 44-50.

[9] Li W. Audit Automation Process and Realization Path Analysis Based on Financial Technology[J]. European Journal of Business, Economics & Management, 2025, 1(2): 69-75.

[10] Liu X. The Role of Generative AI in the Evolution of Digital Advertising Products[J]. Journal of Media, Journalism & Communication Studies, 2025, 1(1): 48-55.

[11] Yang, D., & Liu, X. (2025). Research on Large-Scale Data Processing and Dynamic Content Optimization Algorithm Based On Reinforcement Learning. Procedia Computer Science, 261, 458-466.

[12] Shen, D. (2025). AI-Driven Clinical Decision Support Optimizes Treatment Accuracy for Mental Illness. Journal of Medicine and Life Sciences, 1(3), 81-87.

[13] Liu F. Research on Supply Chain Integration and Cost Optimization Strategies for Cross-Border E-Commerce Platforms[J]. European Journal of Business, Economics & Management, 2025, 1(2): 83-89.

[14] Xiu L. Research on the Design of Modern Distance Education System Based on Agent Technology[J]. Pinnacle Academic Press Proceedings Series, 2025, 2: 160-169.

[15] Chen, X. (2025). Research on the Application of Multilingual Natural Language Processing Technology in Smart Home Systems. Journal of Computer, Signal, and System Research, 2(5), 8-14.

[16] Fu, Yilin. "Design and Empirical Analysis of Financial Quantitative Trading Model based on VMD-DCNN-SGRU Architecture and Integrated System." In 2025 4th International Conference on Distributed Computing and Electrical Circuits and Electronics (ICDCECE), pp. 1-7. IEEE, 2025.

[17] Yang D, Liu X. Collaborative Algorithm for User Trust and Data Security Based on Blockchain and Machine Learning[J]. Procedia Computer Science, 2025, 262: 757-765.

[18] Liu Z. Research on the Application of Signal Integration Model in Real-Time Response to Social Events[J]. Journal of Computer, Signal, and System Research, 2025, 2(2): 102-106.

[19] Hui, X. (2025). Research on Improving the Matching Efficiency between Cancer Patients and Clinical Trials Based on Machine Learning Algorithms. Journal of Medicine and Life Sciences, 1(3), 74-80.

[20] Huang, Jiangnan. "Online Platform user Behavior Prediction and Decision Optimization based on Deep Reinforcement Learning." In 2025 4th International Conference on Distributed Computing and Electrical Circuits and Electronics (ICDCECE), pp. 1-6. IEEE, 2025.