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: Best practice approaches to data management for regulatory reporting

Effective regulatory reporting requires firms to manage vast amounts of data across multiple systems, regions, and regulatory jurisdictions. With increasing scrutiny from regulators and the rising complexity of financial instruments, the need for a streamlined and strategic approach to data management has never been greater. Financial institutions must ensure accuracy, consistency, and timeliness in their...

BLOG

AI in Focus as Experts Meet in UK Capital for Data Management Summit London

Artificial intelligence has dominated the data management conversation in the past couple of years as organisations have recognised the technology’s potential to streamline operations, improve decision making and draw value from the data they use. A-Team Group has responded to the growing demand for intelligence on AI and has given the technology a keen focus...

EVENT

RegTech Summit New York

Now in its 9th year, the RegTech Summit in New York will bring together the RegTech ecosystem to explore how the North American capital markets financial industry can leverage technology to drive innovation, cut costs and support regulatory change.

GUIDE

AI in Capital Markets: Practical Insight for a Transforming Industry – Free Handbook

AI is no longer on the horizon – it’s embedded in the infrastructure of modern capital markets. But separating real impact from inflated promises requires a grounded, practical understanding. The AI in Capital Markets Handbook 2025 provides exactly that. Designed for data-driven professionals across the trade life-cycle, compliance, infrastructure, and strategy, this handbook goes beyond...