When a financial services company wanted more from their data
We built a new IM framework from the inside out
Life Sciences Case Study
Financial Analytics: Financial Performance Management
Our client, a policy bank and member of the financial services sector, was experiencing difficulty with their information management techniques. The client was getting involved in new areas of business in recent years and with new regulatory requirements they needed their Information Management (IM) strategy to evolve.
We recognized the issues they were having and got to work standardizing the data for analytic needs. Using both internal and external data, we built an enterprise information management framework to help the customer manage and use their data in a more efficient manner.
The model we created has been used for other projects, both within financial services and in other industry sectors.
The client approached us for advice on IM to accommodate their long-term business and IT strategies. This included improving their current IM practice, as well as re-defining the IM strategy in line with their future business expansion in areas such as lending and investment. The IM system we were asked to integrate needed to consider market demands, business expectations, and regulatory needs.
The client was looking for long-term benefits through reduced systematic risk and better use of data, and to create a competitive advantage by leveraging the data successfully.
They wished to manage the quality, consistency, usability, security, and availability of their organization’s data to facilitate business process decisions.
How we helped
We recognized that the client was experiencing two major difficulties; firstly the management perspective for enterprise information, and secondly the technical perspective of managing information. We needed to leverage Deloitte’s mature framework and best practice in Enterprise Information Management to provide recommendations and models to overcome the company’s problems.
We went through four stages with the company to integrate their IM system:
- Data Standards – this involved laying out all data standards within the requirements for managing the information, while at the same time catering for the technical difficulties the company was facing. We standardized all different types of data including the data quality matrix.
- Information Governance – setting up the governance framework for managing this information. This was broken down into areas according to the data standards. For example:
- Management framework with regard to data quality.
- Management framework with regard to the analytic data model.
- Governance framework with regard to data management.
- Applications from a technical perspective – this was based on data standards and governance framework techniques. We used best practice in Enterprise BI, ODS, and ETL to standardize, analyze, and manage the data from a single point of view.
- Applications from a business perspective – there were two main areas within this phase, including regulatory reporting and workflow application for managing the data
The project is currently in stage 3 of 4, and the client is extremely happy with the information management system we have integrated into the business.
The model we created has helped our client understand the roadmap to information governance, based on their current and future needs. We ensured our IM model would align with the client’s new application architecture and it is highly reusable as their data and business expands.
The majority of the data we used was for analysis and reporting and we are in the early stages of going through an exercise with the bank to use some of the information for predictive and future purposes.