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Logical Glue Locks in Investment from New Look Founder, Tom Singh

Terms of the investment were not disclosed, but London-based predictive analysis specialist Logical Glue has secured funding from Tom Singh, founder of U.K.-based fashion retailer, New Look. The investment will support the continued development of Logical Glue’s machine learning and statistical modeling platform, including its white box, decision-making engine and data visualization technology.

Singh highlighted the platform’s effectiveness in a range of verticals. “Fast, accurate and automated decisions based on data have a place within many industries, from retail through to finance,” he said, crediting Logical Glue for “(bridging) the gap between data science and the boardroom.” Logical Glue co-founder Daniel McPherson called the company’s technology “the machine learning platform of the future,” and added that FSOs would be among the big beneficiaries of a solution that was “delivering better, faster decisions and providing the consumer with the best customer experience.”

Pictured (left to right): Robert De Caux (Chief Product Officer) and Jon Rimmer (UX Architect) demonstrating Logical Glue Ensemble at FinovateEurope 2016.

Logical Glue has developed a cloud-based platform that enables companies to use data to solve “prediction problems.” As the company’s Chief Product Officer Robert De Caux explained during his FinovateEurope demo last year, questions like:  “Will a customer repay their loan? Will they buy my product?” “Is this transaction fraudulent?” are answerable by applying the right predictive analytic tools to data that lenders and banks already have. More importantly, Logical Glue enables lenders and banks to use these tools without having to hire data scientists and coders to build and run them. During the company’s demonstration of its platform, Ensemble, De Caux and UX Architect Jon Rimmer showed the automatic categorization feature during the data input process, and the feature selection tool which helps ensure that only the most historically valuable and predictive features in the data are included during the model building process.

“You’ll find if you have hundreds or thousands of predictive variables that you want to assess, it’s often that if you remove some of them, you can improve your model performance,” De Caux explained. “At a time when companies are drowning in a sea of data from multiple sources they don’t properly understand,” he said, “it’s a great way to reduce costs and improve insight.” In addition to the data input and model building stages, the team from Logical Glue demonstrated how the models can be customized to the company’s specific business preferences, and then easily deployed in the cloud.

Logical Glue gives users three different predictive models to choose from: one geared toward the best statistical technique, one based on the best machine learning technique, and another De Caux called “the best for insight, which allows you to see why a decision has been made.” The company says its technology helps improve acceptance rates for lenders by 40% and grow profits by between 5-20%. Logical Glue adds that the platform also decreases default rates by 15%, boosts recovery collection rates for debt collectors by 18% and reduces manual interventions for underwriters “20-fold.”

Founded in 2012, Logical Glue demonstrated its technology at FinovateEurope 2016.  The company’s partners include fellow Finovate alums ExperianmiiCard and Equifax.