How Banks Are Meeting Evolving Customer Expectations With Gen AI?
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.
Why Is Gen AI the Most Promising Solution?
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).
Popular Use Cases Of Gen AI In Banking
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:
- Marketing & Sales
With the help of Gen AI, banks can process large sets of customer data and build tailored marketing campaigns, helping them deliver personalized experiences to their customers. Moreover, with advanced features like predictive analytics and machine learning, Gen AI models can forecast the sales of a particular financial product or service, allowing banks to customize their strategies accordingly.
- Onboarding
Onboarding has always been considered a boring and time-intensive process, often resulting in dropouts of customers midway through the ongoing onboarding journey. But with the help of Gen AI models and virtual assistants, banks will be able to assist customers at every step of onboarding by automating redundant tasks and providing innovative solutions, like e-KYC and digital signatures.
- Product Development
Another popular use case of Gen AI in banking includes product development. Gen AI models can produce codes and programs for end-to-end product development. In addition, Gen AI tools can also develop synthetic data for training other models and encrypting customer profiles. And above all, Gen AI-powered product development will be data-driven and analytics-based, leading to personalization in services.
- Financial Advice
Unlike human agents and banking personnel, Gen AI models can search through huge data sets and bring out meaningful information quickly. Therefore, banks can use Gen AI to offer financial recommendations to customers tailored according to their income level, age, credit rating, and personal interests.
- Customer Services
Banks and financial institutions can leverage Gen AI to provide customer support and product assistance. AI virtual assistants and chatbots can provide round-the-clock support and instant resolutions to queries. This frees up time for human agents to focus on other valuable activities, like relationship-building with customers and strategy development.
- Risk & Compliance
The banking sector is prone to various risks, such as fraudulent transactions, money laundering, and non-compliance with regulations. Gen AI can help banks identify and mitigate these risks effectively by offering intelligent AML (anti-money laundering) monitoring tools, e-KYC solutions, computer vision and OCR for biometric detection, and robust data privacy and encryption protocols.
- Supporting & Automating Corporate Tasks
When it comes to automating corporate operations, Gen AI can perform many tasks – code audit and review, code documentation, knowledge management, memo writing, and much more. In addition, Gen AI tools can assist HR in hiring new talents by reviewing CVs, shortlisting candidates, and preparing conversational forms or questionnaires.
The Big Picture Of Gen AI In Banking – Upcoming Trends And Innovations
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.
How Alltius Helps Leading Banks With The Best Gen AI Services?
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.
Conclusion
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.
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