The banking, financial services, and insurance (BFSI) sector has seen a significant shift in customer expectations in the last few decades. Customers in the banking industry have become highly selective and focused towards personalized services backed with robust security and support.
According to a report by the American Bankers Association, nearly 71% of bank customers prefer digital channels over physical channels, like branch visits, ATMs, and phone calls. Further, around 72% of customers believe personalization is an important factor in banking services and can lead to high customer retention rates. Lastly, 80% of users believe bank staff should be given comprehensive cybersecurity training focused on identifying and mitigating potential cyber risks.
Given the evolutions in customer expectations and market dynamics, banks have started upgrading and adopting advanced technological measures. One such great measure is Generative AI. This article delves deep into the role of Gen AI in banking and why it is the perfect solution for banking partners to acquire and retain more customers.
Generative AI has emerged as the most prominent solution for meeting the evolving customer requirements in the banking sector. It leverages state-of-the-art models like GANs (Generative Adversarial Networks), VAEs (Variational Autoencoders), and GPTs (Generative Pre-trained Transformers) to produce intuitive and engaging content, like texts, images, audio, video, and codes – all in real-time.
According to a McKinsey report, Gen AI can add between $200 billion to $340 billion in annual revenue for the banking industry, a solid contribution of around 2.8% to 4.7% of the total industry revenue. Further, Gen AI is also expected to enhance front-office employee efficiency to 35% from 27% by 2026, resulting in an additional per-employee revenue of up to $3.5 million.
An EY report states that Gen AI tools can help banks reduce their time-to-product information by 20-40% and increase the quality of their financial services by up to 40%. Lastly, experts from Accenture report have also forecasted that Gen AI will contribute substantially in the upcoming three years, with abnormal benefits, like 22-30% improvement in productivity, 600 basis points increment in revenue growth, and 300 basis points increment in ROE (return on equity).
Generative AI is on the verge of becoming an integral part of the banking sector and finding its applications in various areas of banking. Some of its major use cases include:
Gen AI is here to stay and transform the banking industry with increased productivity and enhanced customer experiences. Given below are some trends and innovations poised to occur in the near future:
Gen AI-Powered Financial Advisory
The ongoing improvements in training data for Gen AI models have enabled the banking sector to take financial advisory and consulting to another level. Robo-advisors are being built that can analyze large, complex, and years of financial data and deliver tailored advice, related to portfolio adjustment, stock analysis, credit card selection, investment strategies, and more.
AI-Driven Underwriting & Credit Scoring
Integration of Gen AI in underwriting has already resulted in faster conversions, reduced drop-offs, and improved employee efficiency. However, banks are also planning to implement Gen AI for credit rating in loan processing, helping them effectively collect past borrower data across different platforms.
Hyper-Personalization In Banking Services
Banks are working on the implementation of deep learning and natural language processing (NLP) technologies to offer hyper-personalized financial services. These include tailored investment recommendations, credit card offers, dynamic loan interest rates, and attractive cashback, thus advancing from current personalization and predicting user requirements in advance.
AI-Powered Fraud Detection & Prevention
With the advent of Gen AI, the process of fraud detection and prevention is expected to become more optimized and secured. Well-trained Gen AI models will enable banks to analyze fraudulent transactions, money-laundering activities, and suspicious patterns faster, and help them generate real-time alerts and automatically block such events in the future.
Evolution of AI Agents
The emergence of conversational AI and deep learning models has propelled the development of virtual agents and chatbots that can respond to human queries similarly. Moreover, these assistants can also handle more complex tasks, like financial planning, system troubleshooting, and spending pattern analysis to help users manage their finances more seamlessly.
Developed by experts from leading institutes, like Carnegie Mellon and Wharton, Alltius stands out as one of the best Gen AI platforms for banks and financial institutions looking to boost customer engagements and conversions. It provides highly-tailored Gen AI virtual assistants and conversational models that can increase sales by 3X and slash support costs by 50% within weeks of its implementation.
Alltius’ product suite comprises sales enablement assist, end user assist, support agent assist, and more – all built to help leading banks and financial organizations, like AngelOne, DBS, Assurance, and Prudential from pre-sales pitch to after-sales support. What’s more, with its AI features and futuristic capabilities, Alltius has helped major banks reduce their monthly customer support costs by $50K.
Generative AI can drastically enhance the capabilities of banks and financial institutions and empower them to meet all the changing expectations of today's banking customers. With the help of Gen AI, bank employees can boost their productivity by automating repetitive banking tasks and focus on value creation and relationship building with customers.
Moreover, with Gen AI assistants and chatbots, banks can address customer queries instantly and provide real-time, personalized, and convenient responses, leading to increased customer satisfaction and loyalty.
