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AI in Finance

Bank on AI: Updates in Technology News

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The Rise of Artificial Intelligence in the Financial Sector

By Dennis Gada

Investment Growth in AI Technology

The financial sector’s spending on artificial intelligence (AI) technology has seen remarkable growth. Current investments are estimated at approximately $45 billion, and projections indicate that this figure could exceed $126 billion by 2028. This growth reflects the industry’s increasing reliance on AI to drive operational efficiency and enhance customer experience.

Improving Operational Efficiency

Many financial services organizations are focusing on automation of routine operations such as data entry, transaction processing, customer service, and reporting. This shift not only saves millions but also significantly improves execution times while reducing error rates. AI enhances back-office activities, including document verification and customer identity checks, leading to faster and more accurate results at a lower cost.

Transforming Customer Experience

Beyond efficiency, AI is revolutionizing financial services by providing organizations with real-time, actionable insights. This enables hyper-personalized experiences that cater to individual customer preferences. The ability to make informed decisions rapidly is becoming crucial. AI systems continuously learn from data, improving the reliability and granularity of predictions, which helps banks manage their short-term liquidity requirements more effectively.

Risk Management and Credit Assessment

AI also plays a pivotal role in managing a spectrum of risks, including credit, operational, and market risks. For example, AI algorithms can analyze diverse data points, such as utility payment patterns, rental histories, and social media interactions, to assess customer creditworthiness without relying solely on traditional credit scores. This allows banks to expand lending opportunities to a wider demographic.

Fraud Detection and Prevention

While AI can be exploited for illicit activities, it also serves as a powerful tool against fraud. Machine learning algorithms can identify unusual transaction patterns—such as those originating from atypical locations or involving rare connections—in real time. This proactive approach helps detect and prevent fraud, minimizing financial losses. As AI solutions continuously learn, they enhance their accuracy in identifying suspicious activities and reducing false positives.

Compliance Automation

In an era of stringent regulations, AI offers financial institutions an efficient way to manage compliance challenges. AI-driven tools can automate compliance monitoring, regulatory reporting, and various processes, ensuring adherence to present mandates while preparing for future regulatory demands. Automated data collection, analysis, and reporting simplify compliance activities, while transparent audit trails bolster operational integrity.

The Path to Successful AI Integration

Despite the benefits, many banks struggle with integrating AI holistically into their operations. Most organizations tend to adopt ad hoc solutions rather than a comprehensive strategy. To fully realize AI’s potential, financial institutions must integrate technology seamlessly across core operations. Creating an environment that supports AI infrastructure—modular, adaptable, and underpinned by a strong data foundation—is essential. Cultivating a culture that values human-AI collaboration is equally important for success.

The writer is the EVP and global manager of banking and financial services, Infosys.

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