Broadridge teams with Singapore fintech to reduce trade reconciliation inefficiencies

Partnership with Tookitaki leverages machine learning to bring greater efficiency to the middle and back office

23 December 2019


Broadridge Financial Solutions, a $4 billion global financial technology provider, has teamed with Singapore-headquartered startup Tookitaki Holding—one of the stars of the 2018 FIA Innovators Pavilion—to launch a platform based on Tookitaki's machine learning technology to address reconciliation, matching and exception processing inefficiencies in the middle and back office.

The partnership is the latest example of a larger pattern across the financial markets industry of established firms like Broadridge looking to startups for expertise in emerging financial technologies.

Tookitaki, which was founded in 2014, applies machine learning technology to operational processes in financial services. In 2018 it was one of 15 fintech startups selected for FIA's annual showcase in Chicago, and in November 2019 it announced $19.2 million in equity funding from a group of venture capital firms including Viola Fintech, SIG Asia Investment, Nomura Incubation Investment, Illuminate Financial, Jungle Ventures and SEEDS Capital, an investment arm of the Singapore government.

Intelligent Automation

Trade reconciliation, which relates to the identification and resolution of trade breaks between a buyer and seller of a security, is mission-critical to the operations teams at all financial firms. However, even the best reconciliation platforms require significant human intervention to build models, investigate errors and resolve exceptions.

Trade breaks usually occur because of mismatched trade values, incorrect accounts or insufficient funds. For a large financial services firm that does hundreds of thousands of trades a day, even a small percentage of trade breaks can involve hours of manual effort to reconcile.

Broadridge's new platform, which it calls "Data Control Intelligent Automation," uses Tookitaki's machine learning technology to add a layer of enhancement across any reconciliation system, platform or workflow, regardless of vendor.

The platform, which can be deployed on-premise, on Broadridge-managed servers or in the Cloud, presently has two modules that firms can license—Break Management and Recon Perform—with plans to launch more in the future. Both provide enterprise-wide capabilities and work across Broadridge's reconciliations product, as well as in-house and third-party developed solutions.

Efficiency Gains

"Data Control Intelligent Automation will drive performance and productivity gains from incumbent reconciliation systems, especially for organizations that have multiple vendor solutions in place," said Alastair McGill, general manager of data control solutions at Broadridge.

"By leveraging artificial intelligence and machine learning we are helping to eradicate breaks in the exception management world, automatically finding the underlying cause of a problem and resolving it efficiently to ensure the underlying cause is addressed," he added.

Machine learning is a branch of AI that has the capacity to analyze vast amounts of data quickly to find patterns to make predictions, solve problems and reduce errors. Machine learning models are able to identify patterns, gaps, tendencies, and behavior from historical data and optimize automatically through experience and with limited or no human intervention.

Broadridge's machine learning-powered Break Management module accelerates the investigation process and reduces resolution time by continuously improving break classification according to client-defined business reasons. 

The Recon Perform module offers automatic matching scheme configuration using supervised machine learning models. Its algorithms build and create matching schemes based on historical data, perform high-speed data matching, improve matching schemes based on daily activity and suggest the most efficient exception resolution.

The machine learning algorithms continuously test, learn, enhance and retest reconciliation models to optimize exception classification and resolution, Broadridge said.

Explainable AI

Tookitaki, which derives its name from the Bengali word for hide-and-seek, worked with Broadridge to offer the automatic matching and break detection functionality with supporting audit trails.

In addition, its patent-pending "explainability framework" allows Broadridge customers to view decisions made by the platform's engine through a simple interface, a function that is particularly helpful in today’s environment of prudential regulations and data reporting. This interface makes it easier for users to monitor, create, revise and approve matching and resolution schemes, the companies said.

"This offering is unique to the industry and provides an unprecedented level of transparency to build confidence and trust in the application," said Tookitaki founder and CEO, Abhishek Chatterjee.

Other organizations that have worked with Tookitaki include Société Générale, which has implemented Tookitaki's reconciliation suite after the company took part in the bank's Catalyst program, and HSBC, which added Tookitaki to an accelerator program in 2018 to help develop solutions for the bank. Leading to its selection, Tookitaki developed a proof of concept for manual reconciliations across HSBC's global reconciliation utilities to reduce false alerts in know your customer operations.

Venture Capital Perspective

Illuminate Financial, a venture capital firm that specializes in early stage fintech, made its first investment in Tookitaki in March 2019, when it led a $7.5 million funding round for the company. As part of that investment, Mark Rodrigues, a general partner at Illuminate Financial, took a seat on the company's board of directors.

Rodrigues explained that Illuminate Financial sees tremendous potential in the company because of the way its use of technology can be applied across the financial services industry worldwide. Reconciliation processing is not an area that is strategically important to banks, so it makes sense for expertise in reconciliations to emerge from a service provider that can apply its solutions across many companies.

Tookitaki's use of artificial intelligence was not the main selling point, he added. "Our investments are not driven by the technology. We look at what business problem a company is addressing and how it can scale."

Another key point: the quality of its leadership. Chatterjee, the company's founder, has many years of experience in the banking industry in the U.S. as well as Asia, and that gives him the ability to see the universal nature of the reconciliation challenge. 

"We are very bullish on this company and the business problems it is solving," said Rodrigues. "It is rare to get a startup this sophisticated and this global. We think it could reach a $1 billion valuation."

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