Karen Koehler
Image Credit: Shobhan Banoth
Regulatory risk management is a central pillar of the financial sector, ensuring that institutions follow laws designed to prevent fraud, protect customers, and maintain market stability by making each transaction between banks, regulators, and clients traceable and auditable.
However, many compliance systems rely on manual processes, disconnected tools, and outdated infrastructure, making them vulnerable to inconsistent data and undermining the accuracy of regulatory reporting.
Data systems strategist and compliance technology leader Shobhan Banoth has spent nearly 20 years addressing this problem by modernizing the infrastructure behind financial reporting and risk management. Through initiatives like building advanced data pipelines, introducing standardization protocols, and launching models that automatically flag suspicious activity, he’s helped global banks meet regulatory demands with less friction and greater precision.
Read on for a closer look at Shobhan’s formative years, education, and career working at the intersection of regulatory compliance, risk management, and advanced data automation.
An Architect Trained by the Realities of Incomplete Data
Shobhan grew up in a rural village in India, where his family struggled to reliably access essential services like healthcare and education. During a visit to a local health clinic, he saw how the absence of structured patient records led to miscommunication and delays in care, serving as an early lesson in how a lack of consistent information can limit access to even the most basic services.
While studying for a bachelor’s in computer science and engineering from Jawaharlal Nehru Technological University, Shobhan applied that early insight to larger systems. He focused on how weak data infrastructure can compromise the reliability of financial institutions, especially in risk management areas like compliance, where many firms still rely on inconsistent methods like disconnected spreadsheets, manual reviews, and fragmented reporting channels to track activity across business units.
These inefficiencies increase the risk of reporting errors, make it harder to catch financial irregularities, and raise the chances of missing regulatory deadlines. As cybersecurity threats grow ever more complex, the need for better systems has never been greater, with surveys showing 66% of banks report ongoing challenges with their data quality and completeness.
Shobhan has spent his career solving these problems at the architectural level by building systems that strengthen data traceability, auditability, and real-time reporting across large enterprises.
Streamlining Data Remediation at HSBC
Shobhan’s breakthrough contribution to risk management came when he led a major data remediation effort for HSBC. The bank was working to move away from its outdated legacy data systems, which were bogged down by duplicate records, inconsistent formats, and mislabeled information. These issues made regulatory reporting unreliable.
To address this, Shobhan was in charge of the design and implementation of large-scale ETL (extract, transform, load) pipelines that automatically pulled data from multiple sources, cleaned and reformatted it, and loaded it into a centralized database. This allowed HSBC to consolidate fragmented data across departments into a consistent, usable format, creating a stable foundation for meeting regulatory requirements tied to Dodd-Frank, CCAR (comprehensive capital analysis and review), and Basel III.
The new system improved data quality, made audit preparation faster and more dependable, and cut weekly reporting cycles by 10%. Building on that foundation, Shobhan also introduced advanced standardization protocols that streamlined how data was labeled and retrieved across systems.
These improvements sped up reporting and reduced the need for manual cleanup and rework, significantly cutting operational costs.
The result was a stronger, more reliable infrastructure that enabled HSBC to produce accurate and comprehensive data reports, restoring confidence in its internal reporting and paving the way for more advanced regulatory systems in the future.
Automating Risk and Identity Verification Frameworks
Shobhan’s work at HSBC laid the groundwork for his current role as vice president and lead architect of data and information at a Fortune 500 global investment bank. His first tasked was modernizing the firm’s most sensitive compliance systems, particularly in the areas of know-your-customer (KYC) and anti-money laundering (AML), which are essential for verifying client identities, monitoring transactions, and ensuring the firm adheres to legal and regulatory standards.
To streamline these operations, Shobhan built a platform capable of automatically assessing customer risk levels which uses industry-standard identity checking frameworks such as customer due diligence (CDD) for routine assessments, as well as enhanced due diligence (EDD) for reinforcing checks on high-risk clients. He also implemented tiered identity verification protocols that incorporated third-party client data, aligning with strict customer identification program (CIP) requirements.
The result was a 30% reduction in false positives, allowing compliance teams to focus on legitimate risks instead of chasing dead ends. His system also enabled real-time transaction monitoring that met global regulatory standards from organizations like the financial action task force (FATF) and the financial crimes enforcement network (FinCEN).
To further minimize regulatory risk, Shobhan launched a machine learning–driven anomaly detection system that flagged suspicious patterns in customer and transaction data before they escalated. He also introduced real-time data lineage tools, giving compliance teams full transparency into how information moved through the company’s internal pipeline, from initial input to final reports. And to ensure consistency across the board, he built automated reconciliation pipelines that aligned books, records, and reporting layers, cutting data entry errors by 60%.
Together, these systems turned compliance from a slow, manual process into a faster, smarter, and more reliable operation, strengthening the firm’s regulatory posture and improving its reporting accuracy.
Shobhan’s Vision for the Future of Financial Data Infrastructure
Now based in the United States, Shobhan is focused on helping financial institutions rethink their approach to data governance and regulatory architecture. Rather than fixing systems in isolation, his work centers on building end-to-end frameworks that embed data integrity and compliance directly into daily operations.
Looking ahead, he aims to collaborate with experts across both the public and private sectors to explore how technologies like AI can help advance financial analytics and regulation frameworks. His ultimate goal is to move beyond merely improving speed or data quality and build systems that are consistent, automated, and dependable, making compliance more reliable for institutions, regulators, and the public alike.
As financial markets grow more complex and interconnected, maintaining accurate and timely data will only become more critical. Shobhan Banoth is working to ensure that the infrastructure behind that data is stable, trustworthy, and built to last.
To learn more about Shobhan’s research on improving regulatory systems, explore his co-authored papers compiled on ResearchGate, Google Scholar, and IEEE Xplore, as well as his published articles in journals like the Journal of Information Systems Engineering and Management (JISEM).