Strategies for Banking Automation: A Roadmap to Optimal Implementation

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.

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