Democratization of data science: Using machine learning to build credit risk models

Tokyo Century was ready for a change. Credit risk decisions were taking too long and the home office was taking notice. The company needed a full stack data solution to increase the speed of loan authorizations, and it needed it quickly. Moto Tohda explains how Tokyo Century put data at the center of its credit risk decision making and removed institutional knowledge from the process.

Tokyo Century was ready for a change. Credit risk decisions were taking too long and the home office was taking notice. The company needed a full stack data solution to increase the speed of loan authorizations, and it needed it quickly. Zero2HeroTM, featuring Cloudera, and available as a push-button POC on Microsoft’s Azure Marketplace was the answer. Too often we are get bogged down in the weeds of the day-to-day grind. Enterprises aren’t known for their ability to turn on a dime, but a new paradigm has emerged with data, and it’s changing everything from the way we work to fundamental decision making. For Tokyo Century, that means turning its decision makers into data scientists. That might sound impossible until you realize tools from DataRobot can take care of the math and the code while analysts provide the domain knowledge. What Zero2Hero does for Tokyo Century is bring the needed tools from Cloudera, DataRobot, and others into a single, efficient stack that collects data from multiple silos, cleans it and preps it for processing, then applies algorithms to uncover rapid insights. Moto Tohda explains how Zero2Hero and Cloudera helped Tokyo Century move beyond institutional knowledge and hunches and transform it into data literacy across the decision team. This data democratization is driving Tokyo Century to be a more productive and efficient enterprise making the best decisions possible.