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: Navigating a Complex World: Best Data Practices in Sanctions Screening

As rising geopolitical uncertainty prompts an intensification in the complexity and volume of global economic and financial sanctions, banks and financial institutions are faced with a daunting set of new compliance challenges. The risk of inadvertently engaging with sanctioned securities has never been higher and the penalties for doing so are harsh. Traditional sanctions screening...

BLOG

Testing Industry Perceptions at Data Management Summit London

Every year at the A-Team Group Data Management Summit we take the pulse of the financial data and tech industry on a range of critical topics of the day. We do this through audience participation questions during the day-long event, urging delegates to interact with speakers and other participants via remote voting on salient questions....

EVENT

ExchangeTech Summit London

A-Team Group, organisers of the TradingTech Summits, are pleased to announce the inaugural ExchangeTech Summit London on May 14th 2026. This dedicated forum brings together operators of exchanges, alternative execution venues and digital asset platforms with the ecosystem of vendors driving the future of matching engines, surveillance and market access.

GUIDE

Regulatory Data Handbook 2014

Welcome to the inaugural edition of the A-Team Regulatory Data Handbook. We trust you’ll find this guide a useful addition to the resources at your disposal as you navigate the maze of emerging regulations that are making ever more strenuous reporting demands on financial institutions everywhere. In putting the Handbook together, our rationale has been...