Banking on Generative AI: Three Strategic Frontiers to Conquer in 2024
Financial institutions have long grappled with the challenge of offering best-in-class customer service and personalization with pockets of success. The benchmarks in these areas have often been set by the nimble tech giants, whose mastery of consumer engagement and streamlined operations has left traditional banks racing to catch up. An additional challenge has possibly been the need to accelerate and scale digital transformation across various dimensions in their organizations. Amidst this perpetual chase for dominance in digital engagement, innovation and efficiency, a new force has emerged to challenge the status quo: Generative AI.
Characterized by a goldmine of customer-facing data and myriad of customer facing engagements, the banking industry stands to uniquely benefit from generative AI’s disruptive prowess. According to Mckinsey, generative AI has the potential to deliver significant new value to banks – between $200 billion and $340 billion. As banks constantly battle in their quest to deliver rich customer experience while enhancing operational efficiency, generative AI can potentially become indispensable to their competitiveness and profitability in years to come.
In this article, we discover the three major areas in banking where generative AI is expected to make the most significant impact in 2024 and beyond:
Delivering superior customer experiences
Generative AI promises to be a potent leveler for banks in the customer engagement game, offering them the opportunity to significantly raise their customer experience and engagement standards. However, this opportunity exists for all players in the industry. In words of Tony Moroney, Co-Founder of The Digital Transformation Lab, “The real trick is going to be who can use the creative side of generative AI to create new value propositions, new ways of engaging with customers and delivering experiences.”
From real-time customer support via chatbots to tailored recommendations and communications, generative AI promises to enable banks to deliver accurate, personalized, and effective engagements across board. As the models advance, it will adapt and elevate to be able to manage individual customer requirements better, bolstering satisfaction and loyalty. Banks are taking early steps to build competitive advantage here. JPMorgan Chase has filed a trademark application for a product called IndexGPT, designed to aid in personalized selection and analysis of securities for clients.
Banks can look forward to introducing personalized financial advisory services like investments and savings plan for customers by leveraging large language models for analyzing vast datasets. Gen Al will also play an important role in digital Customer onboarding. Furthermore, transformer-centric models and deep learning capabilities can pave the way for conversational banking.
Revamping sales and marketing practices
Generative AI can prove to be a gamechanger for banks’ sales and marketing activities. Using generative pre-trained transformers and specialized financial language models, banks are expected to significantly revamp their sales and marketing strategies in the coming years. For instance, Gartner predicts that 30% of outbound marketing messages from large organizations will be synthetically generated by 2025.
By analyzing customer behavior and trends at granular level, banks can create personalized product recommendations and hyper-personalized marketing campaigns based on individual transaction histories, interactions, and demographics.
In addition, banks can setup sentiment analysis programs utilizing cutting-edge tools like Lexalytics, Azure Text Analytic, and RoBERTa, and generate contextual content, significantly ramping up their customer engagement and conversion rates.
Enhancing software development efficiency
A robust IT infrastructure and applications are the mainstay of success for banks in today’s digital era. Generative AI can be an indispensable tool for banks’ IT teams, helping accelerate software development while ensuring efficiency and data security. According to a study by Mckinsey, software developers can complete coding tasks up to twice as fast with generative AI.
In 2024, banks are expected to increasingly automate code generation by leveraging generative pre-trained transformers, ensuring faster software development with reduced errors and better code quality. Using models like variational autoencoders, banks can generate synthetic data sets for testing, training, and analytics, giving boost to their data security and compliance.
Furthermore, banks can utilize generative AI-powered tools to create design elements like images, UI/UX designs, and interactive prototypes based on specific design requirements. This will help ensure rapid iterations and streamlining the design process, leading to more user-friendly and visually appealing applications.
Reimagining growth strategy with generative AI
With generative AI wave becoming more prominent by the day, banks cannot risk missing out on the abundant business value it stands to offer. It’s vital for banks to integrate their generative AI roadmap with existing business model and digital transformation strategies, aligning towards larger business goals.
As aptly put by Imtiaz Adam, Founder of Deep Learn Strategies, “We’re going to see a world where financial institutions are leveraging technologies like generative AI to improve customer satisfaction, improve operations, and create a symbiotic relationship between a human banker and AI, resulting in better value for the organization and the client.”
Generative AI-powered banking can usher into a new era of customer service, business efficiency, and innovation, helping banks stay ahead of the curve for years to come.
Reference source: Finance
Compiled by the DTSVN author group - Digital transformation solutions for the Finance and Banking industry.
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