Data Model for Listed Derivatives Saves Millions Annually
Sagence’s conceptual and semantic data modeling expertise helped a global investment bank see an annual savings of millions of dollars in penalties and on over payments to exchanges.
Dealing with one of the most complex exchanges in the world, the listed derivatives operations team of a global investment bank was incurring millions of dollars in expenses and fees from incomplete and manually processed membership and fee structures. These transactional issues resulted from siloed storage of trade configuration data, exacerbated over time by structural factors and growth within the organization. In events of uncertainty, payment schemes for trades from both internal and brokerage clients defaulted to the highest possible fee structures.
Sagence tackled this problem by developing a conceptual and semantic data model for exchange membership and trade fees. Working extensively with the technology and operations team managers, we created use case scenarios to develop specific systems requirements and evaluate technological feasibility. From the business and functional requirements gathered, our team designed and modeled data flows from external vendors, exchanges, and internal systems to establish an enterprise-wide data store. This process entailed mass reconciliation of several feeds and sources that varied in levels of sophistication, from manual PDF publications to direct data feeds. This work formed the foundation of a data model that supported a transformational shift in managing the complex exchange data.
The enterprise-wide data store Sagence established enabled an open data environment that increased data integrity and enhanced exchange-traded derivative workflows. Overall, these changes led to annual savings of millions of dollars in penalties and on over payments to exchanges.