The Reserve Bank of India (RBI) has expressed concerns about the impact of artificial intelligence on financial stability, joining other major monetary authorities in raising red flags.
Speaking at an event in New Delhi on Oct. 14, RBI Governor Shaktikanta Das highlighted potential risks posed by the increasing use of AI and machine learning in financial services, according to a Reuters report.
Indian central bank AI concerns
Das pointed to concentration risks stemming from the dominance of a few large technology providers, which could lead to systemic risks if AI systems fail or experience disruptions across the industry.
While AI helps improve customer service and reduce costs, Das warned of other new vulnerabilities, including increasing amounts of cyberattacks, data breaches and the challenge of auditing opaque AI-driven algorithms.
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Das’ concerns echo those of other global financial institutions.
In a July report, the European Central Bank (ECB) outlined its concerns regarding the impact of AI on financial stability.
The ECB said while AI does “bring benefits to the table,” when AI suppliers are too concentrated and the tools are widely used in the financial sector, “operational risk, market concentration and too-big-to-fail externalities may increase.” It added:
“Widespread AI adoption could heighten the potential for herd behaviour, market correlation, deception, manipulation and conflicts of interest.”
It also warned that widespread AI adoption could lead to herd behavior, market manipulation and inflationary pressures.
One of the examples given is the inflated demand for energy worldwide due to the computational power required for sustaining AI, pushing up energy costs.
AI-driven financial stability challenges
More recently on Sept. 20, the Central Bank of Canada also released a brief on its concerns regarding AI and financial instability.
“AI adoption could also lead to financial stability issues,” it reported, particularly as “banks and financial institutions are investing in AI to improve customer service, to enhance compliance and risk management, and to better assess credit and liquidity risk.”
However, it also pointed to operational risks becoming concentrated in a few third-party service providers and spreading through an entire financial system:
“The predictive ability of AI can deteriorate unexpectedly, suffer from hallucinations or be biased and discriminatory. And AI makes everything move faster, which could amplify severe market runs and herding behavior in times of market volatility.”
As AI continues to penetrate the financial sector, central banks and financial regulators globally are urging collaboration between financial institutions, regulators and tech developers to mitigate these risks and safeguard the long-term stability of the global financial system.
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