Abstract
To predict behavior, machines organize and analyze data. It transformed BFSI merchandise delivery. Corporate banking AI automates tasks, detects fraud, boosts investment profits, has chatbots, and predicts market trends. This research examines AI's role, functions, applications, trends, benefits, and drawbacks in finance and banking. The financial industry is transformed by AI in customer experiences, fraud detection, risk management, and task automation. Finance AI helps but falters in data quality, accountability, and compliance. Fintech solutions like digital wallets, blockchain, embedded finance, AI-driven chatbots, RPA, fraud prevention, and personalized services are improving financial services. AI enhances banking and financial customer service, fraud detection, risk management, and task automation, according to this study. Data quality, regulatory compliance, AI-driven chatbots, RPA, and fintech integration are covered. The chapter concludes that AI can improve banking efficiency and accessibility.
TopIntroduction
The banking industry is quickly transitioning to technology as it encompasses global wealth stored in databases and transactions that efficiently transmit information over networks. Emerging technology, especially artificial intelligence (AI), has the potential to enhance various aspects of the sector, such as accounting, sales, contracts, and cybersecurity. Artificial intelligence in banks is increasingly working with financial technology (FinTech) companies to provide enhanced banking solutions to customers as part of their digitalization initiatives. The banking business (Manoharan, G., Durai, S., et al., 2023) has experienced significant advancements due to the utilization of state-of-the-art technologies in recent years. They are broadening their industrial scope to encompass retail, Information Technologies, and telecommunications to offer mobile banking, e-banking, and real-time money transfer services.
Cognitive technology combined with AI enables banks to capitalize on digitalization and rival agile Fintech startups (Lourens, M., Raman, R., et al., 2022). Artificial intelligence is being utilized in banking apps due to factors such as heightened competition in the industry, a focus on process-oriented services, consumer desire for personalized solutions, improved employee efficiency, the integration of software robotics (Rajchandar, K., Kothandaraman, D., et al., 2024) to enhance operations, and the facilitation of effective decision-making and actions.
According to a McKinsey analysis on a global AI survey, 60% of financial services organizations have at least one AI capability in place to speed up business operations. With the ability to improve client experience, minimize errors, and streamline procedures, AI is poised to transform the banking industry. Therefore, all banking institutions must make investments in AI technologies to offer customers cutting-edge experiences and first-rate services.
The following are some ways that AI in banking risk management aids in preventing cyberattacks:
- •
Data analysis: AI algorithms search massive data sets for threats and anomalies.
- •
Real-time monitoring: To promptly identify and manage threats, AI in digital banking maintains track of account activity and transaction data in real-time.
- •
Fraud detection: AI systems look at transactional data and customer behaviour patterns to identify fraudulent behaviour.
- •
Compliance and regulatory requirements: By automatically recording transactions and creating reports, AI aids banks in ensuring compliance with regulations.
- •
Predictive analytics: To determine the possibility of defaults and market volatility, AI develops risk models and does predictive analytics (Lourens, M., Sharma, S., et al., 2023).