2026 Golden Stone Awards | Industrial Bank: Consumer Rights Protection Intelligent Review Platform—A leap from "keyword matching" to "deep business understanding"

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Special Topic: 2026 Golden Stone Award and Excellent Cases in Financial Consumer Protection

The results of the “2026 Golden Stone Award and Excellent Cases in Financial Consumer Protection” event hosted by Sina Finance are out. This issue features outstanding cases of financial technology innovation services. Among many financial institutions competing, Industrial Bank stood out by submitting the case of the “Consumer Rights Protection Intelligent Review Platform” and was awarded the “Outstanding Case of Financial Technology Innovation Service.”

Below is a brief summary of the case:

In recent years, with the continuous strengthening of financial regulation and increasing awareness of consumer rights protection, the banking industry’s consumer rights protection work has entered a new stage of “prevention first, full-process control.” Commercial banks’ consumer protection efforts must shift from passive “post-event remedies” to proactive “pre-event prevention.” As a core part of pre-risk control, the importance of consumer protection review has become even more prominent. With the expansion of business scale and the establishment of a comprehensive consumer protection system, the number of consumer protection reviews at Industrial Bank has increased by over 50% annually in recent years. The review process has evolved through three stages: decentralized and manual—systematic and online—intelligent.

To further address pain points in traditional reviews such as high reliance on manual work, insufficient risk recognition depth, and lagging business adaptation, Industrial Bank leveraged financial technology advantages to successfully launch the “Consumer Rights Protection Intelligent Review Platform” (hereinafter referred to as the Industrial Consumer Protection Intelligent Review Platform), achieving a collaborative mechanism of “AI pre-review + manual recheck,” marking a new stage of intelligent consumer protection work.

The platform has bridged the gap from “keyword matching” to “deep business understanding.” By building a unified consumer protection knowledge base, internalizing regulations and case studies into standard metrics, it fundamentally solves the problem of inconsistent standards; with its powerful chain-based semantic understanding, it deeply insights hidden risks in review materials, overcoming the challenge of shallow recognition; it enables rapid automatic review and risk localization, freeing reviewers from tedious preliminary checks and greatly improving efficiency.

The core of the platform is deep semantic understanding, which simulates human thinking to accurately identify potential risks such as exaggerated claims, incomplete disclosures, or consumer misguidance, rather than simply matching “prohibited words.” Consumer protection review experts can also continuously “teach” AI through rule optimization and model fine-tuning, allowing its review capabilities to evolve.

(Example of review conclusion from the platform architecture—only one shown)

In terms of technological innovation, the platform solves the challenge of cross-modal data alignment, supporting parsing of various formats such as images, PDFs, TXT files, and compressed packages, ensuring compatibility with different document types. Using chain-based contextual engineering techniques, it dynamically decomposes review tasks, plans logical reasoning paths, and makes decision processes traceable and explainable, significantly enhancing the coverage of potential risk detection. Additionally, the knowledge graph-based “Review Brain” system systematically integrates legal regulations and case knowledge to ensure professional and reliable review judgments.

In mode innovation, the platform deeply integrates AI large model’s powerful semantic understanding and data processing capabilities into the review process, automatically examining texts, contracts, and clauses to achieve precise risk identification and early warning. Transitioning from “manual dependence” to “human-AI collaboration” not only improves review efficiency and quality but also promotes knowledge sharing through output review results, enhancing the professional skills of process initiators and reviewers.

In management innovation, the platform shifts consumer protection work from passive “post-event correction” to proactive “pre-event prevention,” ensuring products and services meet compliance requirements before entering the market. By moving from “experience-based judgment” to “standardized benchmarks,” and replacing subjective experience with a unified, stable algorithm model, it significantly improves the professionalism, standardization, and consistency of review operations.

In mechanism innovation, the platform establishes a new working model of “from human effort to intelligent empowerment,” creating a “AI pre-review + manual recheck” collaborative mode that leverages human-AI strengths. During AI pre-review, the system automatically analyzes submitted materials, forms preliminary review opinions, accurately locates risks, and provides relevant legal basis and modification suggestions. During manual recheck, reviewers consider specific business scenarios to verify AI opinions, decide whether to adopt or adjust AI recommendations, ensuring the accuracy and applicability of review results.

From the final results, the Industrial Consumer Protection Intelligent Review Platform has been widely implemented across the bank, covering core businesses such as agency sales of wealth management products, personal loans, credit cards, interbank investments, and corporate finance. It supports review of various materials like posters, marketing scripts, and agreement texts, with 100% coverage of internal communication channels. The review efficiency has increased by over 80% compared to manual review, and the potential risk detection coverage exceeds 90%.

In terms of compliance value, it helps prevent products and services from “going to market with issues,” ensuring the compliance of financial products and services, and enhancing brand value. Economically, it improves review quality and efficiency, reduces manpower costs, and significantly shortens the time for marketing materials to go live, avoiding market opportunities lost due to delays. In training, it transforms experienced reviewers’ expertise into AI rules, enabling standardized and sustainable consumer protection review capabilities. Socially, it upholds higher compliance standards to protect consumer rights from the source, reducing risks caused by unclear terms or insufficient disclosures, and improving the inclusiveness and fairness of financial services, thereby increasing public confidence and sense of security in financial services.