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 value: Harnessing modern data platforms for data integration, advanced investment analytics, visualisation and reporting

Modern data platforms are bringing efficiencies, scalability and powerful new capabilities to institutions and their data pipelines. They are enabling the use of new automation and analytical technologies that are also helping firms to derive more value from their data and reduce costs. Use cases of specific importance to the finance sector, such as data...

BLOG

Regulations in the Balance as Institutions Remain Sustainability-Focussed: ESG Summit London Review

Despite a perception that ESG is in retreat around the world, financial institutions continue to take the issue very seriously as a matter of risk management, a trend that continues to exert an influence on the data demands of organisations. It isn’t even the compliance imperatives of organisations operating in heavily regulated parts of the...

EVENT

TradingTech Summit New York

Our TradingTech Briefing in New York is aimed at senior-level decision makers in trading technology, electronic execution, trading architecture and offers a day packed with insight from practitioners and from innovative suppliers happy to share their experiences in dealing with the enterprise challenges facing our marketplace.

GUIDE

Regulatory Data Handbook 2025 – Thirteenth Edition

Welcome to the thirteenth edition of A-Team Group’s Regulatory Data Handbook, a unique and practical guide to capital markets regulation, regulatory change, and the data and data management requirements of compliance across Europe, the UK, US and Asia-Pacific. This year’s edition lands at a moment of accelerating regulatory divergence and intensifying data focused supervision. Inside,...