Latest news with #FrameworkforResponsibleandEthicalEnablementofArtificialIntelligence
Mint
3 days ago
- Business
- Mint
Can AI wrongly flag legitimate transactions as ‘suspicious'? RBI flags key concerns in latest report
In its latest report, the Reserve Bank of India (RBI) has flagged some concerns relating to the impact of artificial intelligence on the world of finance. The report says that automation can potentially amplify faults across high-volume transactions. For example, an AI-powered fraud detection system that incorrectly flags legitimate transactions as suspicious or fails to detect actual fraud due to model drift can cause financial losses and reputational damage, as mentioned in RBI's FREE-AI Committee Report, Framework for Responsible and Ethical Enablement of Artificial Intelligence. Another danger that the RBI's report proposes relates to the credit scoring model. It says that a credit scoring model that depends on real-time data feeds could fail on account of data corruption in upstream systems. While emphasising the importance of monitoring, it says that if monitoring is not done consistently, AI systems can degrade over time, delivering sub-optimal or inaccurate outcomes. The Financial Stability Board (FSB) has also highlighted that artificial intelligence can reinforce existing vulnerabilities. One of such concerns is where AI models, learning from historical patterns, could reinforce market trends, thereby exacerbating boom-bust cycles. When multiple institutions make use of similar AI models or strategies, it could lead to a herding effect where synchronised behaviours could magnify market volatility and stress. Excessive dependence on AI for risk management and trading could expose institutions to model convergence risk, just as dependence on analogous algorithms could undermine market diversity and resilience. The opacity of AI systems could make it difficult to predict how shocks transmit through interconnected financial systems, especially at times of crisis. AI deployments blur the lines of responsibility between various stakeholders. This difficulty in allocating liability can expose institutions to legal risk, regulatory sanctions, and reputational harm, particularly when AI-driven decisions affect customer rights, credit approvals, or investment outcomes. For example, if an AI model shows biased outcomes due to inadequately representative training data, questions may arise as to whether the responsibility lies with the deploying institution, the model developer, or the data provider. For all personal finance updates, visit here
Indian Express
4 days ago
- Business
- Indian Express
RBI committee recommends measures for AI adoption in financial sector
To encourage the responsible and ethical adoption of Artificial Intelligence (AI) in the financial sector, a Reserve Bank of India (RBI)-constituted committee has recommended several measures, including the establishment of financial sector data infrastructure, data lifecycle governance, consumer protection and cyber security measures. These proposals were put forward by an RBI committee, set up in December last year, to develop a Framework for Responsible and Ethical Enablement of Artificial Intelligence (FREE-AI) in the financial sector. The committee has given 26 suggestions which are based on six pillars – infrastructure, policy, capacity, governance, protection and assurance. 'A high-quality financial sector data infrastructure should be established, as a digital public infrastructure, to help build trustworthy AI models for the financial sector,' the committee said. This may be integrated with the AI Kosh – India Datasets Platform, established under the IndiaAI Mission. The committee has recommended the establishment of an AI innovation sandbox, development of indigenous financial sector-specific AI models, adaptive and enabling policies and adoption of AI liability framework. It has suggested that regulated entities should develop AI-related capacity and governance competencies for the board and C suite. Regulators and supervisors should also invest in training and institutional capacity building initiatives to ensure that they possess an adequate understanding of AI technologies and to ensure that the regulatory and supervisory frameworks match the evolving landscape of AI. To ensure the safe and responsible adoption of AI within institutions, the committee has proposed that regulated entities should establish a board-approved AI policy which covers key areas such as governance structure, accountability, risk appetite, operational safeguards, and consumer protection. Regulated entities should augment their existing business continuity plan (BCP) frameworks to include both traditional system failures as well as AI model-specific performance degradation. The committee has recommended that REs should implement a comprehensive, risk-based, calibrated AI audit framework, aligned with a board-approved AI risk categorisation, to ensure responsible adoption across the AI lifecycle, covering data inputs, model and algorithm, and the decision outputs.
Time of India
4 days ago
- Business
- Time of India
RBI bats for AI policy backed by boards of regulated entities
Mumbai: A Reserve Bank of India (RBI) report on the use of artificial intelligence (AI) in the financial sector has recommended that regulated entities formulate a board-approved AI policy and advised regulators to promote AI-driven innovation that supports financial inclusion , particularly for underserved and unserved populations. In its December 2024 monetary policy statement, the RBI had announced the formation of a committee to develop a Framework for Responsible and Ethical Enablement of Artificial Intelligence (FREE-AI) in the financial sector. "The Committee has developed seven Sutras to serve as foundational principles for AI adoption. Guided by these Sutras, the Committee has proposed a forward-looking approach with 26 actionable recommendations across six strategic pillars," the RBI said. "The report envisions a financial ecosystem where innovation and risk mitigation are aligned." The seven sutras outlined as core principles are: Trust is the foundation; People first; Innovation over restraint; Fairness and equity; Accountability; Understandable by design; and Safety, resilience and sustainability. The eight-member committee, chaired by Pushpak Bhattacharyya , professor at IIT Bombay, recommended that the RBI issue a consolidated AI guidance document. This would serve as a single point of reference for regulated entities and the broader fintech ecosystem on the responsible design, development and deployment of AI solutions. The committee also proposed the establishment of a permanent, multi-stakeholder AI standing committee under the RBI to provide ongoing advice on emerging opportunities and risks, and to monitor the evolution of AI technologies. To address AI-related risks, the report suggested expanding product approval processes, consumer protection frameworks and audit mechanisms to include AI-specific considerations.
