Industry Veteran Aligns Innovation with Risk Management in Finance

Across today's financial sector, banks face the dual challenge of managing risk effectively while pushing forward with technological innovation. In 2021, Archana Pattabhi designed and delivered a data science solution at a global financial institution that addresses the risk of end-user computing (EUC). This practical approach changed how banks manage EUC risks while automating essential processes.

The solution, recognized as a runner-up in the innovation sector for 2021, tackles a common problem in banking: the spread of end-user computing applications operating outside formal IT oversight. By automating more than 800 manual touchpoints, Pattabhi's work cut the time needed for regulatory reports from nearly a week to just 30 minutes, showing how smart technology can reduce risk and boost efficiency simultaneously.

Understanding the EUC Challenge

End-user computing involves systems where staff without programming expertise create functional applications, typically using spreadsheets and databases to meet business requirements without consulting IT. Banks often turn to these methods because they enable non-technical departments to skip technology delays and produce reports independently, cutting time and costs.

This practice, however, introduces considerable risks. "EUC applications typically lack robust security controls that exist in enterprise systems, leaving them open to unauthorized access and cyber threats," Pattabhi notes. Missing documentation, inadequate audit trails, and poor version control worsen these problems, exposing banks to compliance failures.

The price of poor EUC management has proved steep across the financial sector. Regulators have levied heavy fines against banks for risk management and data handling weaknesses. A global financial giant faced a $400 million penalty for "serious and longstanding deficiencies and unsafe practices," and a different bank paid over $61 million when a spreadsheet mistake caused it to overestimate its access to U.S. dollar funding.

A Data-Driven Solution

Pattabhi's data science solution tackles these issues by removing manual steps and meeting compliance standards. The system pulls data automatically from multiple sources, runs programmed logic, and creates necessary reports in a secure setting.

"We designed the workflow leveraging top-tier open-source data science tools and utilized GIT for version control, enabling streamlined collaboration and ensuring the integrity and scalability of our codebase," Pattabhi explains. "This guarantees audit traceability and documents data origins clearly." The bank deploys the solution in controlled environments, protecting sensitive financial data integrity.

The system does more than satisfy regulations—it produces business insights by identifying unnecessary costs and outdated billing, delivering extra value through expense reduction. Such analysis would be nearly impossible for staff to perform manually across numerous data sources with hundreds of touchpoints, illustrating how automation improves analytical power while cutting down on human error.

Safeguarding Financial Assets

Pattabhi's work protects bank assets and information from weaknesses, cyber threats, and data loss through automation and fixing applications that once ran independently without technical standards. This forward-looking strategy shifts banks from reacting to problems toward preventing them.

"Banks must map their digital landscape and rank EUC applications based on impact and handling of regulated or sensitive information," Pattabhi stresses. She maintains that EUCs used for critical regulatory reporting and high-risk operations need immediate attention, as a bank cannot afford manual processes that might expose client data and harm its standing.

The solution works across various EUC applications with little adaptation needed, offering a blueprint for solving comparable issues bank-wide. This flexibility means automation benefits and risk reduction can spread to other departments without major new spending.

Future-Proofing the Industry

Pattabhi aims to position data as a strategic asset that fuels innovation and generates income. "Well-managed data forms the base for successful AI implementation," she points out, connecting today's risk management work with tomorrow's technological progress.

Her plans include building AI-powered risk systems for predictive analysis and risk measurement. This method supports fact-based decisions about technology investments, maximizing returns while keeping risks in check.

Pattabhi champions responsible AI use that aligns with social values, recognizing that progress must respect ethical limits. "Strengthening a bank's digital capabilities with proper controls creates a path to safe, dependable, and robust systems with clear performance measures," she says.

This work demonstrates Pattabhi's dedication to solving difficult challenges while promoting innovation and lasting growth in banking. By showing that risk management and technological progress can support each other, her approach provides a blueprint for how banks can handle increasingly complex regulatory and technical demands.