Sep 23–26, 2019

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

Moto Tohda (Tokyo Century (USA))
4:00pm4:30pm Tuesday, September 24, 2019
Location: 1A 08
Secondary topics:  Financial Services



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.

Photo of Moto Tohda

Moto Tohda

Tokyo Century (USA)

Moto Tohda is the vice president of information systems at Tokyo Century (USA), where he oversees the entire IT for the US operations of Tokyo Century Corporation. Moto wears many hats, and he always strives to balance business objectives with IT initiatives. His past IT initiatives include security, disaster recovery, and many implementations of the ERP-related systems. His newest endeavor is to bring data back to users through data visualization and user-driven predictive analysis models.

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