Case Study: Sumitomo Mitsui Banking Corporation accelerates AI/ML development with dotData

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Sumitomo Mitsui Banking Corporation, a major global bank, faced significant challenges in scaling its data science practice. Its manual processes for feature engineering and model development were extremely slow and time-consuming, allowing the team to explore only 2,000 features and complete approximately 10 projects per year. This hindered their ability to meet the growing demand for AI and ML models across the bank. To overcome these constraints, they turned to the vendor dotData for a solution.

dotData implemented its dotData Enterprise platform to automate the full data science lifecycle, most critically the feature engineering process. This solution enabled the bank to generate two million features per project and accelerated development times by 48x, reducing project duration from two months to just two days. As a result, Sumitomo Mitsui Banking Corporation increased its model output tenfold to 100 projects per year and improved model accuracy by an average of 30%, allowing them to expand AI use across the organization without adding headcount.

Sumitomo Mitsui Banking Corporation

Sumitomo Mitsui Banking Corporation