About a-team Marketing Services
The knowledge platform for the financial technology industry
The knowledge platform for the financial technology industry

A-Team Insight Blogs

Broadridge Partners Tookitaki to Deliver AI Based Data Reconciliation Platform

Subscribe to our newsletter

Responding to the ongoing industry challenge of data reconciliation, Broadridge Financial Solutions has released Data Control Intelligent Automation, an artificial intelligence (AI) and machine learning (ML) platform built for deployment across reconciliation, matching and exception management applications. The solution has been developed with Singapore-based Tookitaki, a provider of AI and ML technology.

The platform will allow customers to license modules on the platform that provide intelligent automation applications. The initial modules are Break Management and Recon Perform. Both modules provide enterprise wide capability, working across not only Broadridge reconciliation solutions, but also in-house and third-party developed solutions.

Alastair McGill, general manager of Data Control Solutions at Broadridge, says: “Intelligent automation will drive performance and productivity gains from incumbent reconciliation systems, especially where organisations have multiple vendor solutions in place.”

The Broadridge platform uses a distributed computing framework to deliver a high-performance and scalable matching and exception process. It is agnostic to the underlying reconciliation system and can be deployed on premise, on Broadridge managed servers or in the cloud. The Break Management module accelerates the investigation process, reducing resolution times by continuously improving break classification according to client-defined business reasons. Recon Perform automates reconciliation builds with an automatic matching scheme that uses supervised ML models and continuous matching scheme improvement, saving time and cost for firms managing large volumes of reconciliations. 

The Tookitaki element of the solution includes the company’s patent-pending explainability framework, which offers a ‘glass-box’ approach to ML models that allows users to view decisions made by the platform’s engine through a simple interface.

Subscribe to our newsletter

Related content

WEBINAR

Recorded Webinar: Unlocking Transparency in Private Markets: Data-Driven Strategies in Asset Management

As asset managers continue to increase their allocations in private assets, the demand for greater transparency, risk oversight, and operational efficiency is growing rapidly. Managing private markets data presents its own set of unique challenges due to a lack of transparency, disparate sources and lack of standardization. Without reliable access, your firm may face inefficiencies,...

BLOG

Private Market GPs Unhappy with Data Availability, Unsure About AI Value

General partners (GPs) within the private equity space are dissatisfied with the quality of data available to them at a time when technology is rapidly transforming the sector. Despite being upbeat about the prospects for deals in the coming year, fund allocators are more pessimistic about their operations amid a shortage of digital operational and...

EVENT

Data Management Summit London

Now in its 16th year, the Data Management Summit (DMS) in London brings together the European capital markets enterprise data management community, to explore how data strategy is evolving to drive business outcomes and speed to market in changing times.

GUIDE

MiFID II handbook, third edition – How compliant are you?

Six months after Markets in Financial Instruments Directive II (MiFID II) went live, how compliant is your organisation? If you took a tactical approach to cross the compliance line on January 3, 2018, how are you reviewing and renewing systems to take a more strategic approach and what are the business benefits of doing so?...