Banks will soon tap tech platforms to offer financial marketplaces: Dennis Gada

Banks are shifting their focus from just enhancing front-end experiences to streamlining the entire customer journey, including middle and back-office processes. Efficient end-to-end processes are essential, particularly in commercial banking, where delays in account opening highlight the need for comprehensive automation.

Modernising legacy systems is critical for agility and innovation, although it poses significant challenges. Banks are also aiming to use their vast, disparate data more effectively for compliance, efficiency, risk management, and customer insights. With the advent of cloud computing and AI, banks are seeking to improve client experiences, introduce better products, and keep growing despite ongoing challenges.

Q. To what extent is AI software becoming part of core banking? Can you give some examples?

Core banking is crucial but complex to modernise. AI acts as an enabler, simplifying and accelerating core banking transformations, which are typically time-consuming and expensive. AI aids in faster modernisation through automated code conversion, testing, and other engineering tasks.

It enhances business processes, transaction processing, and data management, making processes more intelligent and efficient. In transactions, AI helps analyse and detect fraud. For data, AI harnesses underlying system power for better insights.

AI-driven core banking transformation improves customer experience, operational efficiency, and risk management. Infosys applies an AI-first approach across all products, platforms, and processes. Specific applications include cash flow forecasting, hyper-personalisation of customer experiences, personal financial management, and proactive fraud prevention.

On the engineering side, AI improves software development, automated testing, and infrastructure management, leading to more efficient client services.

Q. Can you give us a couple of client specific examples of how AI applications developed by Infosys are being used?

For a leading US wealth management firm, Infosys partnered Microsoft to enable 25,000 financial advisors to access better insights about client contracts, transaction data, and personal financial choices using GPT-4. This has significantly improved advisors' productivity and allowed them to offer tailored solutions to ultra-high-net-worth clients.

In another example, Infosys used AI for a global bank’s commercial credit review process. This manual process, typically taking 30-40 days, was reduced to three-four days by automating the extraction of intelligence from documents, leaving only the final evaluation for relationship managers.

Lastly, for a regional US bank facing $200 million in fraud losses, AI was employed to enhance early detection and implement preventive measures. This led to substantial bottom-line benefits by reducing fraud.

These examples highlight how AI improves productivity and client experiences in wealth management, streamlines credit review processes, and mitigates fraud losses in banking.

Also read: What Indian managers should know about Generative AI

Q. Give us a sense of how your products and platforms business and as-a-service solutions integrate AI.

Infosys offers Topaz, a suite of AI offerings integrated across its services, products, and platforms. For Infosys Finacle, our flagship product for banking and financial services, AI capabilities are continuously enhanced.

These include features like cash flow forecasting, credit risk assessment, payments transformation, and customer churn prediction. New AI-driven functionalities developed from specific client use cases are made available to all clients globally.

A significant portion of payment innovations occurs in India, where the Unified Payments Interface (UPI) generates vast data. Infosys uses such data for insights and anomaly detection, incorporating these features into its core banking suite.

We also improve the software development lifecycle with AI, facilitating faster rollouts and upgrades. We aim for a light-touch implementation model, where our banking software can be installed and configured within hours, using AI to automate the process.

Infosys' vision is AI-first, applying AI to all aspects of product development, deployment, and implementation. This approach enhances product features and functionality, benefiting clients worldwide who use our banking software and other AI-integrated solutions.

Q. Tell us about how IT services around AI solutions are changing the outsourcing model today

We have extensive experience in end-to-end transformations, including large-scale, population-level projects like tax system overhauls and major bank mergers globally. This expertise allows us to provide clients with an “outside-in” perspective on applying large-scale transformation experiences to their business operations.

We help large banks, including in the Nordics and the US, develop AI-first strategies by leveraging their own successful AI-first approach. A strong data foundation is crucial for any transformation, and we undertake large-scale data transformation projects to consolidate data platforms for AI and modernisation purposes.

Infosys’s offerings, such as Infosys Cobalt for cloud services and Infosys Topaz for AI, are central to these transformations. In India, where 70 percent of banks use Finacle, Infosys is at the forefront of financial services transformation. They draw on this experience to assist global clients in replicating successful strategies within their own market infrastructures.

Traditional services like application development, testing, and support are also being enhanced with AI to improve efficiency and speed. This evolution includes adopting managed service models, outcome-based engagements, and unit-based pricing, ensuring full responsibility for business outcomes and cost efficiencies.

Infosys is also investing in regions like the Middle East and Southeast Asia, bringing global capabilities to local clients. The financial services sector remains a flagship business for Infosys, and the transformation strategies applied here are extended to other industry segments within the organisation.

Q. If we were to throw this forward five years, especially in your biggest market, give us a sense of what a bank of the future might look like?

Future banks will be more technology and platform-oriented, shifting from traditional systems and applications to comprehensive platforms that serve both their customers and the broader industry. Retailers and tech companies like Apple already partner with banks, using these platforms to create financial marketplaces.

The widespread adoption of generative AI will significantly impact the financial services sector, driving growth through new products, enhanced client experiences, and improved efficiency. Generative AI can drastically reduce costs associated with business processes, operations, and risk management.

Banks are accelerating their modernisation journeys to address legacy platforms and technical debt. This includes shrinking the core systems and adopting cloud and data transformation strategies to enhance efficiency.

Additionally, banking will increasingly become integrated into various services provided by tech companies, retailers, and financial platforms, embedding itself into people's lifestyles through marketplace offerings. This integration will be facilitated by aggregating platforms, turning banks into more versatile service providers.

Lastly, consolidation in the banking industry is likely as smaller banks struggle to keep up with technological advancements. This will allow for shared benefits from the latest technological developments and ensure competitiveness in a rapidly evolving landscape.