AI Interviewers Debut: Banks Are Experiencing Deep Digital Transformation through "Human-Machine Collaboration"

Shi Shiyu China Securities Journal

The spring campus recruitment for banks in 2026 has kicked off, with several banks offering job positions in artificial intelligence, data mining, and other fields, clearly shifting their recruitment standards towards technical and interdisciplinary talent. Interestingly, the first hurdle for these future AI talents is to undergo scrutiny and selection by an “AI interviewer.”

Industry insiders believe that the accelerated recruitment of tech talent by banks reflects the urgent need for the industry to advance the transformation of financial technology and digital finance. However, amid this trend, issues such as talent shortages and increasing differentiation still need to be addressed by banks, as the industry undergoes a deep dive into “human-machine collaboration.”

AI Interviewer Launch

A few days ago, Li Ming (pseudonym), a recent graduate from a university in Beijing, participated in an AI interview at Ping An Bank. “After entering the system page and taking a photo, I could choose an AI interviewer to enter the interview stage. The AI interviewer asked some relatively basic questions, such as about self-introduction, career planning, and strengths, with 15 seconds of thinking time for each question. The entire interview lasted about 30 minutes, and the AI recorded my answers, expressions, and actions throughout,” Li Ming told a reporter from China Securities Journal.

“My overall impression is that the difficulty of the bank’s AI interview is not high; I was not asked any technical questions, mostly related to personal experiences, career choices, and handling special situations.” Zhang Na (pseudonym), who has participated in AI interviews at two banks, told reporters, “Knowing that the interviewer was an AI, I felt relatively relaxed. Once I finished answering a question, the AI did not follow up, and there was not much interaction throughout. However, if I looked down, fidgeted, or did not maintain eye contact with the screen, the AI would recognize that and issue a reminder.”

“The AI interview is mainly used for initial screening, setting some standardized dimensions to preliminarily assess candidates’ basic qualities. At this stage, AI interviews will not replace human interviews; candidates who pass AI interviews still need to go through multiple rounds of in-person interviews. Our evaluation of candidates’ innovative abilities, stress testing, open-mindedness, and other comprehensive and professional abilities still requires human input,” a business leader from a certain joint-stock bank’s human resources department told reporters.

Recruitment Positions Leaning Towards AI and Technology Fields

If the AI interview represents a superficial change in the talent selection method of banks, then the shift of recruitment positions toward AI and other technology fields is the deeper logic behind this transformation.

Among the state-owned banks, the recent spring recruitment announcement from China Construction Bank shows that branches in places like Beijing, Inner Mongolia, and Jilin are simultaneously recruiting “specialized tech talent,” primarily engaged in data mining analysis, big data marketing, technology research and development, and system operation and maintenance. CCB’s subsidiary, Jianxin Financial Technology, is also explicitly recruiting talent in the fields of artificial intelligence and cybersecurity. Industrial and Commercial Bank of China has created a “Tech Elite” position specifically for tech talent, primarily to reserve talent in system development, application research and development, information security, data mining, and product design.

In joint-stock banks, Shanghai Pudong Development Bank’s spring recruitment for general business reserve positions plans to cultivate core technical talents in areas like research and operation architecture, artificial intelligence, and data operations, with clear recruitment requirements favoring students with backgrounds in AI, data science, software engineering, and financial technology.

Small and medium-sized banks are also making efforts, with Guangzhou Bank’s headquarters focusing on artificial intelligence and algorithm models for its financial technology positions, prioritizing applicants from relevant majors in financial technology, computer science, and artificial intelligence; Beijing Rural Commercial Bank has set up positions for smart elite trainees and financial technology trainees, both requiring candidates to have backgrounds in computer science and technology or artificial intelligence.

Many industry insiders believe that currently, the banking industry is vigorously promoting the development of digital finance, with technologies such as artificial intelligence and cybersecurity becoming core supports for optimizing risk control models and innovating financial products, leading to significant changes in the required capabilities of fintech talent. “The industry is undergoing a deep dive into ‘human-machine collaboration.’ In the past, technical personnel focused more on ‘system development’ and ‘operation support’; now they need to fully apply cutting-edge technologies like AI algorithms and data mining analysis to specific business areas such as customer service, risk control, and product development,” said a responsible person from the financial technology business of a state-owned bank.

Transformation Entering Deep Waters

“Ultimately, digital transformation relies on people to drive it. We need to accelerate the cultivation of a digital talent pool, establish a tiered and categorized training system, and enhance the digital literacy of all employees. We must optimize incentive mechanisms, encourage innovation, tolerate failures, and explore the establishment of career development paths for digital talent, providing ample space for talent growth,” said Zeng Gang, deputy director of the National Institute of Financial and Development Laboratory.

Zeng Gang stated that looking back over the past decade, the digital transformation of China’s banking and insurance industries has evolved from the initial “Internet +” to the current “Artificial Intelligence +” and “Data Elements ×,” achieving qualitative leaps in both the depth and breadth of transformation.

While some banks are accelerating their layout of AI and competing heavily for tech talent, the “technology gap” within the industry is also widening. Many city commercial banks and rural commercial banks are facing the dilemma of “falling behind” in digital transformation.

“We find ourselves ‘willing but powerless’ in promoting intelligent development. For us, the cost of transformation is high, and we have shortcomings in resource investment and technical capabilities. It is quite difficult to build a fintech team, and our salary competitiveness is limited, making it hard to attract top talent in this field,” a responsible person from a rural commercial bank in the western region told reporters.

Dong Ximiao, chief economist at Zhaolian, analyzed that small and medium-sized banks generally face difficulties such as limited funds, few talents, insufficient data, and weak technical strength. For these banks, a following strategy can be adopted, with careful planning before action, exploring application paths for artificial intelligence technology that fit their characteristics, such as focusing digital investment on key regions and core customer needs to improve the input-output ratio.

(Editor: Qian Xiaorui)

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