Unmasking the Black Box Problem of Machine Learning - InformationWeek

Financial and banking services company Standard Chartered turned to a model intelligence platform to get a clearer picture of how its algorithms make decisions on customer data. How machine learning comes to conclusions and produces results can be a bit mysterious, even to the teams that develop the algorithms that drive them -- the so-called black box problem. Standard Chartered chose Truera to help it lift away some of the obscurity and potential biases that might affect results from its ML models. "Data scientists don't directly build the models," says Will Uppington, CEO and co-founder of Truera. "The machine learning algorithm is the direct builder of the model."