Data
Management

In today’s, big data driven world data management is a key for the success of the organisation.

Today the most important and most challenging of the roadblocks faced by financial institutions is Data Management. Data explosion has led to many opportunities that can be capitalized by financial institutions and can be used to glean insights which earlier was not possible. But as more and more data is generated the data issues does not seem to be effectively tackled nor properly understood by management.

Different functions of the banks such as compliance, marketing, risk management, finance etc. all rely on the accuracy of data for decision making purposes. All of these functions look at data from different perspectives, which results in issues related to data quality, aggregation, definition, storage and control.

We help our clients in effective Data Management by creating a comprehensive data management framework in line with best practices as stipulated by BCBS 239, Basel Guidelines for creating an independent risk data warehouse.

• Data Governance and Ownership – This refers to the accountability and responsibility of data. Many times, data is missing, or there are multiple entries corresponding to a single field, but when the data lineage is tracked down, no-one takes the responsibility. One way of addressing this issue is by creating some kind of incentive so that personnel take data ownership seriously.


• Data Management Goals – The goals of data management should be aligned with the business goals and objectives. Developing a policy with respect to data governance, ownership and management goals brings in the


• Data Architecture and IT Infrastructure – Defining how the data is captured, processed, stored and consumed by different functions or business lines. Most of the financial institutions use different systems for different functions, where same raw data is stored differently and different adjustments are done to the data, making it unusable by the other business function. We support our clients by defining and supporting the data architecture based on the single view of raw data required by all the functions within the bank. Further, we support the clients in anticipating the future regulatory and other stakeholder requirements to develop a robust data architecture and IT infrastructure.


• Meta-Data Management – Metadata is the information about the data itself. Metadata gives information about data such as where is data stored, how it is formatted, how the data was acquired and helps with data lineage. We support clients in properly managing and defining the meta-data in standard format to have uniform view across the institution.


• Data Delivery and Data usage – It refers to the ability of the bank to provide efficient and accurate information to the users and in a short span of time. Different reports use differently formatted data but most of the time the raw inputs are same. Therefore, each process in the data management is performed by keeping in mind data delivery and data usage.