Subramanian (Subi) Kuppuswami, Director & Regional Head, UK & EMEA at Maveric Systems, provides valuable insights into the necessities, the benefits and the future of data-led AI in regional banking.
What does “Digital Intelligence” really mean in the context of today’s financial institutions?
Digital Intelligence is the convergence of clean, connected data – both structured (such as transaction records and customer profiles) and unstructured data (like emails, social media interactions and call transcripts) with machine-driven insights to drive smarter and more informed decision-making across every layer of a financial institution. As this convergence deepens, so does the level of contextualisation, allowing banks to interpret data within relevant business and customer contexts, thereby unlocking richer, more actionable insights.
This contextualisation is critical in enabling banks to understand customer behaviors more precisely, detect emerging patterns with greater accuracy and respond proactively to market changes. This integrated approach not only improves operational efficiency and risk management but also empowers banks to deliver highly personalised financial products and services tailored to individual needs and circumstances.
The real shift comes when Digital Intelligence, enriched by contextual understanding, is embedded into existing systems with minimal disruption, allowing banks to transform without dismantling what already works. Leveraging Digital Intelligence successfully will be critical for seamless innovation and modernisation in the banking and financial services industry.
How are banks and financial institutions are adapting to this new era of data-led AI?
Financial Institutions and banks are responding dynamically and quickly to the growing demands of the financial landscape and are getting defined by their ability to modernise data infrastructure effectively by harnessing AI to turn vast amounts of data into actionable intelligence. Those that successfully integrate AI into their data infrastructure are not only streamlining operations and reducing risk but also unlocking new revenue opportunities and transforming customer experiences.
Maveric Systems developed an advanced AI-powered Customer Support Transformation Solution for a global bank, significantly improving First Call Resolution (FCR) rates and reducing call handling time, transforming their customer service operations, driving greater operational efficiency and enhancing overall customer satisfaction.
What are the most impactful use cases of data-led AI you have seen in banking and FIs so far?
While we are advocating AI@Scale to create a holistic business impact, these are some of the use cases we are encountering:
- Anti Money Laundering (AML) solutions which enable banks to gain full visibility across transactions, compliance triggers and CRM touchpoints.
- We are seeing use cases in fraud detection and financial crime prevention. At Maveric, we analyse real-time data to spot suspicious patterns, reducing false positives with behaviour-based models, and uncovering fraud networks through graph analytics.
- Elevating customer interaction and personalisation through 24/7 chatbots that deliver hyper-personalised banking experiences. We have enabled predictive engagement with tailored financial advice that offers seamless service via conversational AI.
- Credit-risk solutions leveraging alternative data such as social behaviours that can reduce approval times while enhancing accuracy
- Driving operational efficiency and workflow automation, equipping relationship managers with call summarisation tools, enable task execution via agentic AI and in some cases, streamline sustainability reporting in green finance.
- Reshaping wealth management through robo-advisory and automated trading to drive trades, deliver personalised investment portfolios and enable risk-managed automation across advisory services.
- Enhancing regulatory compliance and risk monitoring, supporting internal risk assessments to ensure explainability, transparency and consent-driven use of personal data.
What are the data challenges institutions face before AI can be truly transformative?
Most institutions still face data silos, legacy infrastructure and low data governance maturity, and many are not willing to move their data or allow it to train public large language models (LLMs). The goal is to source open market data, train the LLM, and then deploy these models at the customer’s location. The other challenge is cloud adoption. While banks use cloud for analytics and marketing data, they keep operational and transactional data on-premises. These factors are slowing down cloud adoption and scale, while also facing challenges with reducing bias and ensuring explainability with broader data sets.
To enable AI, Financial institutions and banks need to first establish a cohesive and adaptable data backbone. At Maveric Systems, we consolidate data from multiple systems via APIs and CDC mechanisms, while providing a manual interface and rule-based workflows that align with the organisation’s regulatory hierarchy. In essence, it bridges the gap between the old and new, making AI adoption far less disruptive and more intuitive.
How should institutions measure ROI from their AI investments?
This is one of the most challenging topics for the CXOs of financial institutions. The speed at which the AI tech is evolving is making this even more challenging. In that sense, the ROI from AI driven initiatives lies in both hard and soft returns. We see successful and tangible ROI from measurable factors such as reduction in false alerts and manual case reviews, faster time to compliance and enhanced customer personalization.
Customer satisfaction surveys represent a valuable means of measuring ROI, as this metric is consistently monitored across industries to evaluate the quality of customer experience (CX).
ROI should also capture long-term enablers like scalability, futureproofing and auditability, all of which are core to their platform design.
Where do human roles evolve in an AI-first bank, and is there a fear of redundancy?
Human traits such as ethical judgment, creativity and contextual understanding remain essential for long-term success. AI augments humans. In financial institutions, especially within compliance and risk teams, the role of people is shifting from manual execution to informed supervision. With regulatory compliance where instead of combing through thousands of transactions, officers can now rely on AI to surface high-risk cases, while using intuitive interfaces to view the entire history and data lineage associated with a particular alert or status change, as seen in Maveric’s solution.
The future is not man versus machine, it is man plus machine, working in tandem.
The prevailing mantra is to keep the human in the loop, empowering individuals to make smarter and more efficient decisions rather than replacing them.
Looking ahead, what should be the AI roadmap for financial institutions in the Middle East over the next 2–3 years?
AI investments in financial institutions across the Middle East are accelerating at an unprecedented rate, yet many of them are struggling with talent shortage and technology capabilities critical for successful scaling of AI adoption. Having said that, significant investments are leading to establishing a robust foundation in talent, technology and transformative capabilities such as data modernisation.
Value creation for business is what will set apart the winners in the next 2-3 years. We definitely see most of our customers looking to adopt AI.
The UAE and Saudi Arabia (KSA) are leading this transformation, where regulatory support and a strong digital vision are driving innovation and a rapid adoption of AI technologies.
What is your message to banking leaders in the Middle East embarking on this journey?
If data is the new oil, AI is the refinery but only when the pipelines are well laid out. With the right partner and architecture, you can start experiencing the AI transformation at scale today, not years down the line.
About The Author
As Director & Regional Head for UK & EMEA, Subramanian (Subi) Kuppuswami heads Maveric’s regional growth and operations strategy. With over 28 years of global experience, Subi has extensive consultative sales, account growth, P&L, business solutions and client relationship experience in the US, UK, Europe and APAC across Banking & Financial Services, Telecom and Manufacturing domains.
Article Originally Published in MEA Finance (Page no 24 -25).
