Recognos Financial, provider of AI based data management solutions for the financial services industry, has launched Recognos ETI, a new data extraction platform designed to unlock greater context and insight from otherwise untapped business data.
Utilising the latest advancements in artificial intelligence (AI), natural language processing (NLP), semantic and other technologies, Recognos ETI allows companies to extract, transform and integrate both structured and unstructured documents and data into useable business intelligence.
"Recent studies have shown that 80 per cent of all data in large organisations is unstructured, including many mission-critical documents such as contracts, prospectuses, and compliance documentation,” says Drew Warren (pictured), President and CEO of Recognos Financial. “Recognos ETI gives users the ability to go beyond traditional analytics to actively ask questions of their data to find the right information faster to improve business performance.”
Using user-defined extraction criteria (the Extraction Taxonomy), the Recognos ETI platform leverages machine learning, natural language processing and semantic techniques to maximise the accuracy and quality of the data extracted. The platform also utilises ‘human in the loop’ machine learning technology to continuously improve the data extraction process and minimise the extraction errors.
“Financial institutions and large corporations continue to spend billions of dollars to manually process important documents, including key AML/KYC compliance information that has become vital for these companies to maintain in light of increasing regulatory scrutiny,” says Ben Knieff, Senior Analyst, Aite Group. “Semantic technology platforms have the potential to significantly reduce costs and mitigate the risks associated with manual processing, as well as improve the overall quality of reference data.”
