New York-based fintech firm Broadridge Financial Solutions has launched a new data platform, dubbed ‘Tradeverse’, to help trading firms eliminate data silos, unleash the potential of their data across the enterprise and better manage costs, reconciliation, and the data quality and lineage challenges of firms typical complex platform ecosystems.
Broadridge explained that Tradeverse consolidates real-time, multi-asset class data from multiple vendor applications and platforms from orders and executions through settlement into a unified data platform.
Tradeverse promises to reduce errors and simplify access with a common data ontology across front, middle and back offices. It also incorporates robust security to protect sensitive information and maintain data integrity. The clear data structure unlocks insights for key functions – including trading desks, operations, risk, finance, and regulatory – by providing a trusted and transparent data source.
“A Tradeverse implementation we’ve recently completed with a global bank is proving the power of harmonising trade data,” said Hugh Daly, head of data and AI, capital markets at Broadridge. “The solution delivers efficiencies for their regulatory reporting and compliance teams, allowing direct access to the data for business users initiating complex searches using natural language.”
Many enterprise data warehouse projects fail to deliver the expected benefits due to the complexity arising from disparate representations of the source data.
Tradeverse focuses on ensuring data harmonisation by leveraging the application of business logic and constraint of the data ontology. This leads to seamless access to high-quality data, which ultimately accelerates time-to-value for multiple AI initiatives.
In another use case, the securities operations team of a leading capital markets firm is using Tradeverse’s harmonised data platform coupled with Broadridge’s generative AI tool for Operations, OpsGPT, to empower users. This is enabling the teams to identify and implement productivity gains such as settlement fails analysis that was previously difficult to capture in a fragmented ecosystem.
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