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September 24, 2024Adoption of AI and ML in Banking Sector
The financial sector is rapidly integrating artificial intelligence (AI) and machine learning (ML) systems to enhance efficiency and reduce costs, remarks Ramesh Behari; in a column in The National written by Peter Esila. This top Telikom PNG technician says advances in big data, cloud computing, and the digital economy have made it easier for banks and financial institutions to deploy these technologies. AI and ML are being used in various capacities, such as forecasting financial variables, improving investment management, and automating compliance processes, which were traditionally labour-intensive.
Transforming Risk Management and Compliance
AI and ML are reshaping risk management and compliance within the financial industry, Behari said. Behari noted that these technologies enable real-time data analysis, enhancing the accuracy and speed of compliance decisions, particularly in response to the stricter regulations imposed after the 2008 financial crisis. Behari further explained that as these systems continue to evolve, they promise significant benefits in terms of operational efficiency and regulatory oversight, although they also introduce new risks that require careful monitoring.
Future Challenges and Policy Considerations
When discussing with business reporter Esila, Behari put forth that while AI and ML offer substantial benefits, such as cost savings and better risk management, they also pose unique challenges, including ethical concerns and potential threats to financial stability. Policymakers, remarked Behari, must develop robust frameworks to manage these risks, ensuring the safe and equitable deployment of AI/ML technologies. As the technology evolves, ongoing international cooperation and knowledge sharing will be crucial to address these emerging challenges, particularly for less-developed economies, Behari finally remarked.
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