GenAI set to revolutionise efficiency in BFSI sector: Synechron CTO David Sewell

The financial services sector has always aimed to enhance its efficiency, from compliance to customer support, but the rise of generative artificial intelligence (GenAI) is now transforming this landscape. This technology is not only streamlining operations but also opening doors to personalised financial services and advanced data analytics. 

In an interview with TechCircle, David Sewell, Chief Technology Officer of Synechron, a New York-based information technology and consulting company, shared insights on how GenAI is transforming the banking, financial services and insurance (BFSI) sector and how businesses are adapting to these changes, and what’s next! Edited Excerpts:

How does your company use digital transformation to drive growth and adapt to market changes?

Our business is centered around delivering IT services, with a strong emphasis on leveraging digital transformation to enhance our own operational efficiency and developer productivity. However, our primary focus is on ensuring our clients' success by delivering maximum value to them. For us, digital transformation is about modernising our clients' technology, processes, and organisations so they can benefit from the latest innovations.

One of the most disruptive technologies today is GenAI, but our approach isn't limited to AI. We also work with technologies like blockchain, which, after initially being disruptive, has now become more mainstream — evident in the adoption of digital currencies by central banks. Many of our clients are either integrating blockchain technology into their business processes or exploring how they can connect with central bank digital currencies.

Our goal is to understand these technologies and business processes thoroughly so we can combine them in ways that deliver the most value to our clients. 

How do you think of GenAI as a technology contributing or changing the financial sector? 

The topic of GenAI in the financial industry is vast, with numerous aspects that can positively impact the sector. While technology isn’t entirely new, AI and machine learning have been in use in financial services for over a decade, its applications are evolving. Many of our clients have already been leveraging AI to recognise patterns in complex data, whether it’s analysing financial markets, detecting cybersecurity threats, or understanding customer behaviours to improve service offerings. 

What’s groundbreaking now is GenAI's ability to not just recognise patterns but also generate human-like text and speech. This has the potential to transform various aspects of financial services, particularly in improving operational efficiency. For instance, simple chatbots, like our Nexus Chat, help employees be more productive by providing quick access to information, assistance, and creative ideas.

We’ve also focused on enhancing efficiency within our organisation. Earlier this year, we launched several tools as part of the original Nexus suite, providing employees with easy access to chat interfaces. One particularly time-consuming task we addressed is responding to requests for proposals (RFPs). We developed a tool that automatically generates responses by drawing on our knowledge base, which has proven beneficial not only for us but also for our clients. 

In the HR space, where processes can be cumbersome, we created the Cinechron Unify tool to automate various tasks, making it easier for employees to navigate their HR needs. This tool, launched earlier this year, is applicable to large organisations across various industries, including financial and IT services. 

Another significant area of impact is developer productivity. By using AI as a developer assistant, we’ve seen a 40% improvement in productivity among experienced users. This technology helps developers write and test code, generate architecture principles, and create test data, all of which are crucial in financial services. 

In addition to improving internal processes, we’ve developed solutions to support our clients’ business growth. The Cineco and Amplify tool, part of the Nexus suite, gathers and summarises company information, aiding banks in analysing their customers. As we looked towards the next generation of tools, the Nexus Plus accelerators, we focused on enhancing business processes further. For example, the Earnings Analyzer interprets business performance, while the Legal Agreement Wizard assists legal teams with document processing. 

Other Nexus Plus tools include the LLM Sandbox, which allows firms to create customised chatbots, the Companies Filings tool that automates public company filings, and the Credit Memo Generation tool, which processes loan applications. These tools demonstrate the significant opportunities AI presents, and while we’ve covered many, there’s still much more potential to explore. 

Beyond chatbots, how else can banks and the BFSI sector use GenAI to improve consumer experience? 

Many people are focused on the chat experience, particularly the interactive aspect. However, many firms are still cautious about exposing their customers directly to AI chat, as it's challenging to predict what the AI might say. This uncertainty requires firms to implement strict guardrails and controls when using AI with end customers. Internally, there's less concern, and more GenAI is used in customer experience processes. However, these processes often still involve humans to ensure safety and accuracy. 

Currently, GenAI serves as an assistant to make human interactions more efficient and productive, such as by gathering customer information and summarising it for call center operators. This helps improve the customer experience by providing operators with more relevant information. We have also developed solutions for monitoring call center conversations, advising operators on how to handle conversations, and detecting non-compliant advice, which can then be flagged for further action. 

Despite the increasing role of AI, human involvement remains crucial. AI enhances human efficiency by providing real-time information and ensuring accuracy in customer interactions. 

When it comes to implementing GenAI solutions, data security is a significant concern, particularly for clients in financial services. Although there's a lot of interest, adoption is slow because clients are cautious about how their data is handled. They need to ensure that sensitive information isn't shared with public AI models. While many AI firms offer guarantees about not logging or storing data, concerns remain. 

To address these concerns, we work with clients to understand data models and implement security measures. Some clients choose to use internal AI models rather than public ones, gaining the benefits of GenAI without risking sensitive data exposure to public endpoints. 

What other sectors are you planning to expand into, and what strategic initiatives is your company pursuing to advance technology offerings in different industries? 

Financial services remain our primary focus, and we’re not shifting away from that. However, you may have noticed recent announcements about acquisitions in Eastern Europe and Australia, where we acquired several companies. Some of these companies focus on financial services, while others are involved in different industries. 

As we integrate these companies into our organisation, we’ll naturally begin to adopt the client industries they serve. That said, I can't point to any specific industry we’re targeting right now, as financial services remain our main priority.

Besides GenAI, what other technologies are you planning to invest in or focus on in the near future? 

In financial services, many technologies converge in the realm of GenAI. When we talk about GenAI, we're referring to an entire ecosystem that supports its adoption. 

One key area is cloud technology, which we've been focusing on for years. We help our customers embrace the cloud, but many still struggle to fully realise its benefits, such as agility and cost efficiency. We work closely with them to unlock the value they expect from the cloud. 

Blockchain is another technology we've been heavily involved with. Although it's been around for some time, it's now becoming mainstream, especially as central banks start to create their own digital currencies. We've been working with blockchain since around 2015, developing digital assets for the financial services market and exploring applications like blockchain-based stock exchanges. 

The core technologies we've worked with over the past few years AI, GenAI, blockchain, and cloud haven't fundamentally changed, but they've certainly evolved. Cloud is now the standard for infrastructure across the industry, and AI continues to advance. 

We're also keeping an eye on emerging technologies that could disrupt the industry in the future, such as quantum computing. While widespread adoption of quantum computing might still be five to ten years away, it's crucial to understand the challenges it will bring. For example, quantum computing could potentially break today's encryption protocols, so we need to ensure that financial services adopt encryption methods that will remain secure in the quantum era. 

In summary, we're helping our clients both adopt and grow with existing technologies while also preparing for the future as new technologies become a reality.