BST Awards 2020: Best buy-side reconciliation platform/service—Gresham Technologies
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Thanks to its Clareti solution, Gresham Technologies has secured the title for best reconciliations platform at this year’s Buy-Side Technology Awards, beating last year’s winner, Smartstream Technologies. This year’s success is the London-based reconciliations specialist’s first across all of WatersTechnology’s awards programs.
Clareti uses end-to-end automation to accelerate reconciliations and matches datasets from the simplest to the most complex data flows. Gresham Technologies’ CTO, Neil Vernon, says the platform leverages heuristic machine-learning technology for detecting data irregularities and modeling complex datasets.
All functions, including data governance, quality control and reporting practices can be managed through the single Clareti platform. The company has built out self-service capabilities to enable both business users and IT experts to add new customers, controls and connectivity on the platform in a matter of days rather than weeks or months.
Clareti is built on a data-and-compute grid, which allows several services to be managed from a single server, freeing up memory on the platform. In turn, this enables reconciliations data to be processed instantaneously and facilitates quicker response times. “It allows us to get data to the user interface (UI) very quickly,” Vernon says. “It’s not hitting a database or a disk—the vast majority of what a user sees comes directly from memory.”
The Clareti front-end is underpinned by React, an open-source framework created by Facebook for building UIs. Vernon says React UIs can operate effectively over large datasets.
Over the past 12 months, the firm has been developing “out-of-the-box” capabilities on the platform for nostro reconciliations and custodial reconciliation. In 2021, Gresham will focus on improving its exception management functions and offer new capabilities for regulatory workflows, such as the acquisition, validation and testing of regulatory reconciliations data.
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