Minsheng Bank's Zhang Bin Reveals Tech Hiring Now Concentrated on AI, Security and Architecture

Deep News
03/31

At the 2025 performance exchange meeting held by Minsheng Bank on March 31, Chief Information Officer Zhang Bin provided insights into the bank's digitalization efforts and artificial intelligence applications. He stated that Minsheng Bank's AI initiatives in 2025 primarily revolve around four key areas: strategic guidance, organizational support, capability building, and deepening specific applications.

Regarding strategic guidance, under the leadership of the head office's digital steering group last year, the bank continued to enhance AI governance, establishing core principles focused on value orientation, shared performance creation, open cooperation, and security with controllability. Aiming to become an intelligent bank, Minsheng Bank is exploring and promoting a shift in AI application from being a tool for empowerment to a force for business model transformation.

In terms of organizational support, the bank is strengthening its AI talent pool through a combination of external recruitment and internal training. Since the beginning of 2024, hiring within the bank's entire technology division has been concentrated specifically on three fields: AI, security, and architecture. Furthermore, last year the bank established a standardized training and certification system for AI engineers to enhance the overall AI literacy and skills of its workforce.

Concerning application projects, a collaborative mechanism between business analysts and intelligent solution architects was formulated to support the transition from performance integration to shared performance creation.

For capability building, the bank is continuously optimizing foundational capabilities in computing power, data, knowledge, and models. Key focus areas last year included developing agent and intelligent agent engineering capabilities, alongside security and risk management capabilities. Research was conducted from multiple perspectives, including management mechanisms, platform capabilities, tool ecosystems, and application paradigms. This led to the construction of an intelligent agent foundation that is manageable and controllable throughout its entire lifecycle, enabling efficient internal and external collaboration. This base provides robust, enterprise-level support for unlocking AI value, particularly in building complex applications for critical business scenarios.

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