About a-team Marketing Services
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

Upcoming Webinar: Generative and Agentic AI in Financial Markets: What the Data Really Shows

Date: 15 October 2026 Time: 10:00am ET / 3:00pm London / 4:00pm CET Duration: 50 minutes Artificial intelligence is reshaping financial markets – but the reality on the ground is more nuanced, more uneven, and more instructive than the headlines suggest. A new A-Team Insight research programme, drawing on responses from senior AI decision-makers at...

BLOG

Semantic Frameworks Slow to Gain Traction Despite Criticality to Data Democratisation: Webinar Review

Semantic layers have become critical to financial institutions as they have expanded the use of artificial intelligence agents and widened staff access to them. The sophisticated interfaces give non-technical users the ability to guide agents to interact with their firms’ data and build efficient workflows. And yet, few organisations have really got their teeth into...

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 2026 – Fourteenth Edition

Welcome to the fourteenth edition of A-Team Group’s Regulatory Data Handbook. Supervisors increasingly expect firms to demonstrate which rules apply, which data supports each obligation, who owns the control and how exceptions are identified and resolved. Policies and implementation programmes must now be supported by records that can withstand regulatory scrutiny. This edition examines material...