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iS bank selects driverless AI platform from H2O.ai for income prediction, cash forecasting & check default prediction applications

Andrew Morris, Senior Vice President, EMEA, H2O.ai said that the decision by İşbank to use Driverless AI will be its shining example of how a progressive-thinking finance organization in EMEA is embracing innovative AI and ML technologies to improve the accuracy of its business planning predictions. This makes them even more competitive in this increasingly challenging market. They are looking forward to working closely with İşbank, and its innovation arm Maxitech, on the next stage of this IT business transformational initiative.

Along with the primary selection agreement by İşbank, Maxitech introduced İşbank’s software development subsidiary. Softtech is one of the leading tech companies in Turkey to H2O.ai. Both the parties worked together on assessing how H2O.ai’s Driverless AI platform would enable the business unit to digitally transform its customers in the Turkish marketplace into more AI driven organizations.

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İşbank, officially known as Türkiye İş Bankası, the largest private bank in Turkey, has selected H2O’s Driverless AI platform. This helps them to upgrade its Income Prediction, Cash Forecasting and Check Default Prediction applications, so that they can improve the accuracy of the bank’s business planning with on-going AI projects. In partnership with İşbank’s San Francisco-based innovation arm Maxitech, İşbank has agreed to adopt the H2O Driverless AI platform after one successful project. Also, Maxitech is the lead in this initiative. That successful project showed that the machine learning (ML) performance improvements, revenue increases and cost reductions on existing application development processes.

Ümit Bilik, Chief Data Officer, Head of Data Management & Artificial Intelligence at İşbank said that they are delighted to have selected H2O.ai through the work with Maxitech for this important step towards empowering their AI capabilities. Their selection decision was driven by the proven creation of successful high-performance machine learning models, demonstrable efficiency improvements and H2O.ai’s technical and domain expertise.

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