29 October, 2022: By Ajoy Maitra

Artificial Intelligence has it's potential to redefine the finance sector with cognitive optimization of efficiencies and cut down costs of customer acquisition.

Challenges to data management has necessitated banking ERP system which deals with the complex integration of large volumes of information for a smooth productive workflow. Cloud computing has eased out the consolidation of big data with enhanced security and accessibility for an authorized personnel.

The most vital implementation of AI in banking sector is to enhance security by accurate fraud detection with prevention of data breach or financial loss to an institution.

The global AI in banking market size was valued at $3.88 billion in 2020, and is projected to reach $64.03 billion by 2030, growing at a CAGR of 32.6% from 2021 to 2030.

AI in Bank Lending Process

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Lending being the paramount source of capitalization in banks, it involves detailed analysis of credit worthiness of borrowers and securitization of loans.

Credit scoring and monitoring serves as an advanced customer and credit data profiling to ensure better personalization and digitalization. With customer behavourial data, AI can profile better to determine their worthiness. Cross selling and upselling credit availability for a customer helps banks to possibly meet their business goals.

The most commonly used AI technologies are: robotic process automation (36 percent) for structured operational tasks; virtual assistants or conversational interfaces (32 percent) for customer service divisions; and machine learning techniques (25 percent) to detect fraud and support underwriting and risk management.

With digital lending, AI utilises the structured and unstructured customer data to automate the processing of huge information datasets for better decision making.

Apart from the customer data utilisation, AI ensures better underiting process in reviewing and approving files as per the provided documents. Accessing and analyzing the right information to make better decisions help banks to fast processing of loan files with accuracy.

Enhanced Digital Banking Applications

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AI enhances the digital user experience in using the mobile applications, easing out the daily banking facilities.

The availability of banking mobile applications helps customers to review and monitor their daily banking needs without visiting the branches. Fast processing of requests and chatbots further enhances the experience by addressing the concerns of customers.

Artificial Intelligence allows us to offer an experience that doesn’t require our customers to go through several pages on our website; they can easily get the information through simple conversations. This is a great time-saving convenience for busy users who are already using Messenger.

– Steve Ellis, Head of Wells Fargo’s Innovation Group.

Banking applications provides detailed spendings and savings analysis of an individual. Further adding value to the experience, AI provides insights into investment opportunities, better than normal savings, by analysis market trends and portraying a predictive analysis of the wealth creation.

Cybersecurity in Banking

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Data security and cybersecurity is a vital part of digitalization of services. Digital banking is even more prone to cyber attacks and data breach, wherein AI serves a major role in securing privacy and monetary assets of individuals.

AI improves fraud detection by applications through machine learning and a strong neural network. Real time processing of large amounts of data ensures that the consumer profile is safe for a transaction. Machine learning processes and stores past transactions and behaviours of a customer, IP/MAC address used and further analyses the risk involved for a fraud.