Our client operates in the investor services field of corporate and investment banking and uses various types of data. Within this investor services landscape, all systems use their own local data dictionaries and translation rules. As a result, inconsistent data quality and inadequate access to real-time data for end-of-day / batch-driven processing was an issue. These limitations made it impossible to gain a global view of investor services intraday credit risk exposure for clearing and custody services.

The client therefore wanted to develop a data service platform as the basis of an improved strategic risk management system. Working closely with our client as part of a joint team, we developed and delivered a data storage and processing system to aggregate and merge structured and unstructured local data. The system is effectively resolving the challenges of local data dictionaries and translation rules used for different internal and external sources.
Our solution is a data service platform that all the investor services systems can use to gain a standardized view of the transactional and reference data. It is a high-performance data storage and processing system created with leading-edge technologies like Apache Storm, MarkLogic, Solace and Hadoop.
The solution transforms diverse data from disparate sources to create a standardized view with guaranteed data quality for system users. The bank can define business rules and apply them to incoming data streams, revealing exceptions that can indicate the source of concrete records .
Having resolved the flexibility and scalability challenges, the new high-performance data storage and processing system is enabling the client to formalize and clearly document the data processing steps. The data service platform has become the ‘golden data source’ for the business system users, therefore forming the basis of the improved strategic risk management platform.
In addition, the platform provides the extra capacity required to store and retrieve all historical data, process data in real-time and maintain multiple users concurrently.
Full case study (95 kB)