Imagine a world where financial institutions process complex documents in seconds, customer queries are handled effortlessly by intelligent chatbots, and compliance reports are generated with unparalleled accuracy. This is the promise of Generative AI, a technology that promises to revolutionize the finance sector.
The past two years has seen an explosion of innovation within the sector, as organizations seek to mitigate many of the complex processes that have traditionally stymied efficiency.
According to research from NVIDIA, 91% of financial services institutions today are either assessing AI or using it in production to drive innovation, improve operational efficiency, or enhance customer experiences.1
With such widespread adoption, the question is no longer whether to implement Generative AI, but how to leverage it effectively.
The proliferation of Generative AI
It’s key for IT decision makers to pay attention with technology firm EPAM seeing several promising use cases emerge.
“The ability of Generative AI to summarize text is one of the strongest features of the technology for financial institutions, given the huge volumes of documents they routinely deal with,” says Michael Nicholls, Principal, Financial Services Consulting at EPAM.
“Associated with this is the ability to query materials using natural language, rather than a business intelligence tool, or having to ask IT to run a query. This has the potential to turbocharge productivity.”
The customer perspective
EPAM also sees potential for the extensive use of Generative AI chatbots to help customers find out about a product, check their accounts, or even initiate transactions. These use cases would free highly skilled people from routine tasks, enabling them to focus on higher value activities.
The ability of Generative AI to parse huge volumes of data and produce easily digestible reports and thematic analyses will help financial institutions solve some of their most pressing challenges, such as complying with anti-money laundering (AML) regulations.
“One of the use cases that I’ve seen come up multiple times is related to KYC [know your customer] requirements,” says Othman Baalache, a Director in Cloud Technology Consulting at EPAM. “We’re working on applications that leverage OpenAI on the Microsoft Azure platform.
“With one Middle Eastern client, for instance, we’ve developed a tool that automates the extraction and classification of data from its vast trove of KYC documents. Working with Microsoft, we’ve developed a powerful tool that helps illuminate manual interventions and human error to create a faster and more accurate reporting process.”
However, for financial services companies looking to develop AI applications such as these, its first necessary to ensure that the right foundation is in place.
Avoiding Generative AI pitfalls
The IT fundamental of “garbage in, garbage out” applies just as much to Generative AI as to earlier business applications. AI success therefore comes down to ensuring that models use only high-quality data.
EPAM stresses that security is another non-negotiable. “Having a proper governance framework across the usage of Generative AI tools is vital,” says Baalache. “Microsoft Azure, for instance, provides a framework that allows firms to control the use of AI within the organisation – a step I would always recommend. Azure also supports various security frameworks, such as NIST [National Institute of Standards and Technology], so firms can benefit from strong guardrails around their implementations.”
More generally, financial institutions should lean on the advice and expertise of their business partners.
Nicholls concludes: “Everyone is on the same journey, and firms are working hard to be the first to deploy killer use cases. Working with technology partners that have broad industry experience can provide firms with a holistic and rounded view of AI implementations, helping them to avoid pitfalls and leapfrog the competition.”
Learn more about how EPAM is helping financial services organizations keep pace with emerging technologies, rising customer expectations, and ever-changing regulations.