Strategies for banking automation: A roadmap to optimal implementation
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:
Robotic Process Automation (RPA): Financial services providers should focus on RPA as it helps streamline repetitive and time-consuming tasks, thus improving operational efficiency and reducing human errors. It can automate routine processes like loan processing, account opening, and customer onboarding. In addition to saving time and costs, RPA allows employees more time to focus on more strategic tasks, such as interacting with customers on a personal level, analyzing market trends, developing new commercial strategies and making decisions to keep the financial services provider competitive.
Artificial Intelligence and Machine Learning: AI and ML technologies are fundamental to successfully implementing automation in the financial industry. These technologies can be used in various aspects of banking, including fraud detection, customer service, credit risk assessment and personalization. Banks should allocate resources for researching and developing in-house AI and ML solutions or partner with dedicated vendors to stay ahead in the swiftly evolving landscape. It is also important to note that all generative AI models should serve as assistive tools, not the sole decision maker.
Digital Customer Experience: Building upon the importance of personalization, investing in digital customer experience becomes crucial. This includes implementing AI-powered chatbots for customer support, enhancing mobile and online banking platforms and leveraging advanced analytics for personalization. After a virtual assistant verifies the customer’s identity, a customer can communicate with these chatbots in real time and receive details on their accounts that would otherwise require human attention. Financial services can increase customer satisfaction, loyalty and revenue by prioritizing the digital customer experience.
Infrastructure Modernization: Legacy systems can slow down the adoption of automation. To overcome this challenge, financial institutions must invest in modernizing their infrastructure, including upgrading these legacy systems, embracing cloud-based technologies, and implementing API-driven architectures. Banks should prioritize seamlessly integrating automated solutions, such as AI-powered personalization tools.
Data Management and Analytics: Data is critical in automation and personalization. Banks should invest in robust data management systems and advanced analytics tools to make sense of all the data they collect. This will enable them to gain important insights, make informed conclusions, and improve the accuracy of their predictive models, leading to better personalization and customer experiences.
Collaboration and Partnerships: Banks should explore collaborating with FinTech startups and other technology providers to accelerate their automation journey. Leveraging strategic partnerships, banks can benefit from innovative solutions and expertise that may not be available within their organization, including speeding up time to market, diversifying their offering and enhancing customer experiences. This cooperative approach can help banks improve their AI and personalization tools, ultimately improving their ability to offer highly customized and responsive services to their customers.
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.
