Data Lineage is the New Risk Map in Banking: Charting the Hidden Flow of Information with Vijayalakshmi Duraisamy

With the world of banking technology becoming more and more sophisticated, and millions of data points flying across thousands of systems per second, it is no longer a nicety but a need to know where the data comes from, how it is changed, and where it finally ends up. Data lineage, once a behind-the-scenes operational issue, has become a frontline countermeasure against risk, data quality breakdowns, and compliance failures. With financial institutions being increasingly scrutinized by regulators and investors, tracing out data journeys from source to consumption has become central to operational resilience, transparency, and decision-making.

Leading this change is Vijayalakshmi Duraisamy, a well-experienced data analyst with more than six years of intense work in data lineage projects at the enterprise level. Evidently coming from the specialist table, she has been at the core of demystifying the complex layers of data movement within some of the most sensitive bank products, particularly in the mortgage and personal loan sectors. In one case, her team covered 16 mortgage products sold across segments like NAM, LATAM, APAC, and EMEA—each with varying regulatory and operating frameworks. "Data doesn't travel from point A to point B," she said. "Frequently, system 1 communicates with system 3, and only upon being aggregated do they progress to system 4. Without a clear lineage, it's like driving a city with no map."

To this, her work has not only stayed theoretical or on paper. In 2022, her data lineage analysis allowed for the strategic sunsetting of intermediary apps after her client had exited the market. This clean-up operation was said to save more than $20 million in maintenance and server charges. In addition, throughout 2023–24, her remediating efforts enabled data flow transparency and data quality testing for business processes that were associated with more than $80 billion in assets—an influence that points to the magnitude and severity of her efforts.

One of her best works is the end-to-end lineage design for a new personal loan product launch. In addition, she helped spearhead a data quality remediation initiative that used lineage as the key tool to spot logic errors and data integrity breaks. These are not back-office tasks; these are bedrock exercises in risk management and compliance.

According to the reports, her expertise also extends to niche tools such as Celonis and DC Catalog, which facilitate visualization and traceability of data flow and materiality across system layers. "These platforms give a centralized view," she adds, "but the correctness still relies on the analyst's knowledge of the business and functional logic contained in each hop."

She has not made this journey without encountering some resistance. Processing data streams in banking typically involves patching together connections between third-party systems—including rates and treasury feeds and external data standards providers. "The real challenge is when you scale up," she said. "Mapping data for one product is fine, but doing that across product processors and regional variations adds a whole new dimension."

Apart from technical contributions, Vijayalakshmi has made a contribution to scholarly work with a paper entitled "Database Systems, Data Warehousing and Data Mining," which has been accepted for presentation at the forthcoming ICAITCA'25 conference. It is said she has also organized internal knowledge-sharing presentations on warehouses and database structures, further establishing herself as both practitioner and thinker within the data management community.

Looking to the future, her vision for the future of data lineage is evident. "This isn't just a documentation task anymore," she stressed. "It's a live tool for business improvement, problem-solving, and even system simplification. In the future, more companies will leverage lineage to establish data quality rules and to identify where derivation logic needs to be normalized."

Vijayalakshmi Duraisamy's research highlights a larger reality of our financial world today, data lineage is not an IT appendage anymore. It is, in every respect, the new risk map.