While AI could reshape how financial institutions serve customers, monitor risks, and strengthen oversight, its adoption without adequate safeguards can amplify existing weaknesses. 

Significance of AI in Finance

• Convenient Customer Interaction: Simpler, more intuitive and responsive through multi-lingual chatbots. 
• Improve Credit Delivery: AI can supplement traditional finance methods (collateral, financial statements, etc.) by drawing insights from a wider set of patterns in transaction behaviour, repayment flows and business activity. 
• Fraud detection and Risk Management: Identify unusual patterns, flag suspicious activity and support faster intervention. 
• Compliance and Supervision: Analysing large volumes of information, identifying patterns and drawing attention to anomalies. 

Associated Concerns

• Bias and unfair Outcomes: While AI systems learn from data, data could carry imprints of past behaviour, existing inequalities and structural exclusions. 
• Black Box nature: Opaque nature of systems can produce outcomes not always acceptable to customer, manager or regulator. 
• Data privacy: Financial data are amongst most sensitive forms of personal information.
• Model and Concentration risk: If multiple institutions rely on similar AI models, a flawed model can impact billions of customers. 
• Cyber risk: Fraudsters  and bad actors can use AI to craft more convincing phishing attempts, create deepfakes, etc.