Published by Jessica Weisman-Pitts
Posted on January 2, 2024
4 min readLast updated: January 31, 2026
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By Chris Tapley, VP, Financial Services Consulting at EPAM Systems, Inc.
By Chris Tapley, VP, Financial Services Consulting at EPAM Systems, Inc.
The recent excitement and growth around ChatGPT and similar large language model-based (LLMs) tools will fundamentally change how everyday customers interact with banks and other financial services providers. According to recent research, 85 percent of financial services organizations currently utilize artificial intelligence (AI) in some form within their company, whether it’s used to collect data or serve as a customer service chatbot.
Financial institutions must adapt to the rapidly evolving technological landscape by utilizing advancements in AI, machine learning (ML) and other new services and products pushed to market by their competitors. However, a necessary investment, with time and capital, is required to achieve these benefits.
Decision-makers in financial services organizations need to pay attention to the challenging economic environment that pressures them to protect the bottom line while delivering the quality and scope of services customers expect. Therefore, many banks must take direct and deliberate steps to significantly revise their technology stacks and operational processes to control current costs, optimize near-term revenue and position themselves for future growth.
Automation will be a key tool to reduce the cost of critical processes. However, automation itself often requires modernization of the underlying technology infrastructure. If done correctly, this digital transformation has the potential to help banks build their competitive advantage.
However, there are challenges associated with using AI and automation within finance. These include regulatory compliance issues, data privacy concerns and the potential for bias or discrimination. The industry must emphasize responsible and ethical usage of the technology.
Given the vast number of changes and challenges this optimization can require, careful planning and execution are the keys to success. The essential investment areas for banks to effectively implement automation and create a seamless, personalized customer experience include:
Investing in these target areas will help banks automate their processes and future-proof their business in an increasingly competitive landscape. By adopting this roadmap, financial institutions can lower costs, enhance efficiency and deliver superior customer experiences, positioning themselves for long-term success.
Robotic Process Automation (RPA) refers to the use of software robots to automate repetitive tasks in business processes, improving efficiency and reducing human error.
Artificial Intelligence (AI) is the simulation of human intelligence processes by machines, especially computer systems, enabling tasks such as learning, reasoning, and problem-solving.
Digital Customer Experience encompasses all interactions a customer has with a brand through digital channels, focusing on enhancing satisfaction and engagement.
Infrastructure Modernization involves upgrading legacy systems and adopting new technologies to improve efficiency, scalability, and integration in business operations.
Data Management in Banking refers to the practices and processes used to collect, store, and analyze data to improve decision-making and customer service.
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