While AI can improve efficiency, cut costs, and enhance decision-making, concerns around its transparency, accountability, cybersecurity vulnerabilities, and dependence on third-party providers cannot be ignored.
One of the most pressing issues is AI’s “black-box” nature, which makes it difficult to understand how decisions are made. This opacity raises concerns about fairness, accuracy, and reliability.
“The black-box nature of AI systems can make it difficult to assess the system’s reliability or contest its decisions. This lack of transparency can lead to trust concerns and challenges in validating the fairness and accuracy of AI decisions, making it challenging to audit or interpret the algorithms that drive the decisions,” the survey read.
Such ambiguity could erode trust in AI-driven banking processes and complicate regulatory oversight, it added.
Accountability & cybersecurity threats
The difficulty in tracing AI-generated decisions also creates accountability challenges. If an AI system makes an incorrect or unfair decision, it is unclear whether responsibility lies with the banks, developers, or third-party service providers.
Beyond accountability, cybersecurity threats loom large. AI’s capabilities could be exploited for fraudulent activities like synthetic identity fraud, rogue trading, or market manipulation—posing systemic risks to the financial sector.
Also read: Banking sector strong, but Economic Survey 2025 sounds a note of caution
The report also flags concerns about AI’s impact on human resources. As automation takes over key banking functions, excessive reliance on AI could lead to a gradual erosion of human expertise, making it harder for banks to step in during crises.
Additionally, dependence on third-party AI service providers creates risks. If a single provider experiences technical failures or security breaches, it could disrupt banking operations on a large scale.
Given these challenges, the Economic Survey 2025 underscores the need for stronger regulatory frameworks, transparent AI models, and robust oversight. While AI’s role in banking is transformative, its safe and ethical implementation must be prioritised to prevent unintended consequences.
