The machine learning dilemma: So much data, where do we begin?

first_img 23SHARESShareShareSharePrintMailGooglePinterestDiggRedditStumbleuponDeliciousBufferTumblr According to industry headlines, the answers to many challenges facing credit unions today lie deep within their member data.However, with volumes of data spanning a credit union’s systems and applications – and multiplying by the minute – bringing it all together under one technological roof is easier said than done.So how can credit unions better manage their data, implementing the right strategies and infrastructure to transform data into both operational efficiencies and better member experiences?“Machine learning technology is quickly advancing and promises to benefit credit unions and their members in many important ways – from fraud detection and risk management to member services and marketing,” said Phong Q. Rock, Sr. VP, corporate strategy and business development for Feedzai. “However, leveraging all that machine learning has to offer requires credit unions to first ensure the quality of their data.” continue reading »last_img