Sunday, December 22, 2024
Sunday, December 22, 2024
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AI advancements could pose substantial ‘financial stability risks’

Reliance on AI may contribute to instability in capital flows and exchange rates, RBI governor says

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  • One of the primary concerns is the potential for concentration risks, as a few dominant technology providers might control a disproportionate share of the market.
  • It may also introduce vulnerabilities, such as heightened exposure to cyberattacks and data breaches, which could compromise the integrity of financial systems.
  • Financial sector urged to prioritise the establishment of adequate risk mitigation practices to navigate the challenges posed by these technological advancements and ensure sustained stability in the global economy.

The increasing integration of artificial intelligence (AI) and machine learning in global financial services offers significant opportunities for enhancement in customer experience, operational efficiency, and risk management.

However, as highlighted by Shaktikanta Das, the Governor of the Reserve Bank of India, this technological advancement also presents substantial financial stability risks that cannot be overlooked.

One of the primary concerns is the potential for concentration risks, as a few dominant technology providers might control a disproportionate share of the market.

This concentration could precipitate systemic risks; a failure in one major system could have ripple effects throughout the financial sector, threatening overall stability.

Market volatility

The reliance on AI also introduces vulnerabilities, such as heightened exposure to cyberattacks and data breaches, which could compromise the integrity of financial systems.

Moreover, the inherent opacity of AI algorithms complicates the process of auditing and interpreting the decisions made by these systems.

Such complexity can lead to unforeseen consequences in the financial markets, underscoring the urgent need for robust risk mitigation measures within banks and financial institutions.

The unpredictable nature of algorithm-driven outcomes can exacerbate market volatility and undermine stakeholder confidence.

Das further emphasises the impact of divergent global monetary policies, which may contribute to instability in capital flows and exchange rates. Such fluctuations can disrupt the delicate balance of financial stability, particularly in a landscape where private credit markets have expanded rapidly with minimal regulatory oversight.

The lack of stress-testing in these markets poses an additional threat, as they remain unprepared for potential downturns.

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