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DataTracks Plans Next Version of Rainbow Software Featuring Artificial Intelligence and Machine Learning

 

DataTracks, a global leader in providing cloud based software application for preparation of compliance reports announces plans for the next version of its Rainbow software featuring artificial intelligence and machine learning capabilities.

Singapore based DataTracks is a global leader in providing software and services to help business enterprises prepare and file compliance reports with regulators (such as SEC in United States). DataTracks counts more than 16,600 clients in 24 countries.

Rainbow 3.0, the current version of the software links to financial books, draws financial and other data into a depository, facilitates writing of compliance reports in a collaborative manner using the data in the depository, facilitates defining data by associating each piece of data with a definition concept in a public or private taxonomy, and facilitates extraction of output in iXBRL, XBRL, HTML and PDF formats for filing with regulators and for printing/publishing to stakeholders. The Rainbow software has been used by clients to produce more than 166,000 compliance reports so far since inception.

Rainbow 4.0, the next version slated for release in 18 months, would incorporate AI and machine learning features to supplement human judgment in associating the most “fit for purpose” definition of financial data.

Founder/Director T R Santhanakrishnan said: “Independent league tables for quality in the United States, places DataTracks within top three positions with a score of 99.44%; a score far better than several competitors in the space. High quality makes it easy for analysts to acquire insight into your financials and help reduce noise and increase signal in the capital market. Using AI and ML are the only ways to further increase quality beyond the current high score. The emphasis here is to supplement (and not supplant) human judgment. We are excited about our investment into the next version of Rainbow; especially for our customers in US and European Union regulatory regimes”.

He added: “It gives me joy to keep Singapore at the leading edge of this aspect of financial technology providing quick acquisition of insight from financial information by investors, and analysts worldwide”.

Pramodh Vittal, member of Executive Board responsible for R&D said: “It was an extraordinary journey, marked by very intense efforts, in getting our quality score to reach current levels. The baby steps were easy: Better recruitment, better training, and better process control. Improving the quality score beyond 90% required analytics to identify patterns and mitigate the impact of likely causes. Improving any further from 99% requires quick and comprehensive comparison with peer decisions and past decisions. That can only be done by deploying AI and ML”.

 

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