In an era where artificial intelligence is reshaping industries, the financial world stands at a critical crossroads, balancing innovation with accountability. At the forefront of this transformation is Geol Gladson Battu, Assistant Vice President of Securities Services Technology at Citigroup, author of From Code to Compliance, and a leading advocate for responsible, production-grade AI. His work demonstrates how transparent, auditable, and regulation-aligned AI can redefine compliance, fraud detection, and risk management for the world’s largest financial institutions.
Bridging Technology and Trust in Financial Systems
Battu’s journey began in engineering roles at Infosys and Zwitch Payments, where he mastered the fundamentals of secure, scalable data systems. But it was at Citigroup, over a span of eight years, that his career reached global impact. There, he led modernization programs that replaced legacy reconciliation and surveillance processes with AI-driven automation frameworks.
The results were measurable: predictive models that reduced false positives by up to 30%, shortened reconciliation cycles, and improved audit transparency. These weren’t mere proofs of concept; they were enterprise-grade deployments that balanced cutting-edge performance with the rigorous compliance demands of global banking.
“AI in finance is not just about speed or automation: it’s about trust,” says Battu. “Transparent, resilient, and ethical systems shape a financial future that serves both institutions and people.” His approach emphasizes embedding trust from the ground up, ensuring that AI solutions not only enhance efficiency but also withstand regulatory scrutiny. By focusing on scalability and security early in his career, Battu laid the foundation for innovations that address real-world challenges in high-stakes environments like banking.
This bridging of technology and trust has positioned him as a key figure in transforming how financial institutions approach digital evolution. His hands-on experience highlights the importance of integrating AI with existing systems without compromising on reliability or ethical standards.
Operationalizing Responsible AI Through Innovation and Research
The seed for Battu’s personal brand was planted in a recurring tension: banks wanted AI’s efficiency, but regulators demanded explainability. He realized the key was not just building intelligent systems but ensuring they were traceable, auditable, and compliant from design to deployment.
His pioneering work focused on reducing false positives in fraud detection, enhancing reconciliation accuracy, and enabling regulatory reporting automation. The breakthroughs came from treating AI not as a standalone algorithm but as part of a larger ecosystem of governance and auditability.
That philosophy underpins his book From Code to Compliance, a practical guide that bridges the gap between data science and financial regulation. The book and his research papers presented at IEEE ICCNT 2025 and IEEE ETNCC 2025 offer reproducible frameworks for explainable AI, AML risk scoring, and regulatory audit readiness. His papers, cited more than 50 times on ResearchGate, are helping practitioners and academics alike design AI that regulators can trust.
Battu’s contributions extend beyond theory; they provide actionable strategies for implementing AI in compliance-heavy sectors. By addressing the “black box” nature of many AI models, he advocates for tools that allow stakeholders to understand decision-making processes, thereby fostering greater adoption in risk-averse industries.
Academic Excellence and Future Frameworks for Trustworthy AI
Beyond corporate leadership, Battu’s influence extends to academia and research. He is a Doctorate (DBA) candidate at Indiana Wesleyan University, holds an MSc from the University of South Florida, and contributes as a peer reviewer for IEEE and other journals. His patented design, a UK-registered system for AI-driven financial fraud detection using scalable cloud infrastructure, underscores his ability to innovate across both theory and implementation.
His philosophy is clear: “Regulation and innovation are partners; when we embed compliance into design, we unlock sustainable automation at scale.”
Today, through his practitioner-led FinTech consultancy and advisory work, Battu helps institutions design, pilot, and scale responsible AI frameworks. His services span from model validation playbooks and data governance design to explainability and regulatory mapping workshops. The model is built on measurable KPIs, reducing false alerts, ensuring audit readiness, and improving decision transparency.
Looking ahead, Battu envisions an ecosystem where governance, explainability, and auditability are not afterthoughts but foundational design principles. “My goal,” he says, “is to shift the narrative from ‘AI is risky’ to ‘AI is manageable and auditable.’”
As financial institutions worldwide grapple with evolving regulations and rising risks, Geol Gladson Battu offers a replicable model for what trustworthy AI can look like, not just in concept, but in production. His work is a reminder that the future of finance won’t be defined by algorithms alone, but by the integrity, transparency, and accountability built into them.
