On October 30, a financial news update reported that Agricultural Bank of China held its third-quarter 2026 earnings briefing today.
Huang Jianqin, General Manager of the Inclusive Finance Department, stated that Agricultural Bank of China will adhere to balancing development and security, deeply grasp the new opportunities brought by digital intelligence technology, proactively address potential risks in technology application, and promote the deep integration of artificial intelligence with inclusive finance. The bank aims to achieve stable lending, optimized structure, improved quality, and sustainability, continuously consolidating its position as the leading bank with the largest total supply of inclusive financial services, the broadest service coverage, and leading sustainable development capabilities.
First, stable lending. By fully utilizing the ability of multimodal large models to identify and analyze unstructured data, the bank can thoroughly verify genuine entities, genuine operations, genuine needs, and genuine purposes, precisely allocating limited credit resources to inclusive groups with real operations and real financing needs, thereby meeting market demand.
Second, optimized structure. The bank uses artificial intelligence technology to improve the accuracy of customer group identification, adjust requirements for years of operation and collateral guarantees, and optimize customer structure and guarantee structure. It precisely matches corporate operating cycles with repayment rhythms, improves loan term structure, alleviates the pain point of "short-term loans used for long-term purposes," and optimizes term structure. It builds large models to parse unstructured information on the technological innovation qualifications of technology-based small and micro enterprises, intelligently identifies cross-border trade and cross-border settlement data of foreign trade small and micro enterprises, and applies multimodal technology to analyze business district foot traffic and acquiring transaction flows, guiding credit resources toward key areas such as technological innovation, foreign trade, and consumption, thereby optimizing the investment structure.
Third, improved quality. The bank uses large models to preemptively assess signals such as industry changes and capital anomalies, strengthens big data anti-fraud identification, multi-lender borrowing warnings, and penetrating monitoring of fund flows, and rigorously implements pre-loan on-site due diligence, genuine customer access, and fund usage control, strictly preventing various risks such as impersonation loans, falsified materials, fabricated operations, and misappropriation of loans. Adhering to the principle of AI-assisted lending, artificial intelligence handles information collection, cross-verification, and report generation, while key credit decisions retain manual review and professional judgment, ensuring that decisions are explainable, traceable, and accountability is definable.
Fourth, sustainability. The bank fully leverages the role of artificial intelligence in risk pricing, aligning loan interest rates with customers' true risks and their operational affordability, scientifically and reasonably determining inclusive loan interest rate levels, and achieving a dynamic balance between risk and return while effectively reducing the comprehensive financing costs of small and micro enterprises. Through intelligent approval, intelligent operations, intelligent risk control, and other means, the bank continuously reduces the business costs and risk costs of inclusive loans characterized by "small amounts, high frequency, and dispersion," creating room for the sustainable development of inclusive finance. It applies artificial intelligence to analyze and explore customer needs in payment settlement, insurance and wealth management, and investment advisory, expanding "credit plus" comprehensive financial service capabilities to better meet the diverse financial needs of small and micro enterprises.
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