H2O.ai and IBM Deliver A Competitive Edge for Visión Banco with Machine Learning

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MOUNTAIN VIEW, Calif. and ARMONK, N.Y., Dec. 11, 2018 /PRNewswire/ -- IBM (NYSE: IBM) and H2O.ai today announced that Visión Banco has deployed H2O Driverless AI, H2O.ai's automatic machine learning platform, on the IBM Power Systems AC922 server, the best server for enterprise AI. This collaborative solution will help position Visión Banco to gain a competitive edge in providing financial services to their customers.

Visión Banco, based in Asunción, Paraguay, provides financial services to small and micro-sized companies in Paraguay. It offers credit card services, remittances, utility and tax collection services, pension plan contribution plans and payment transfer services. Visión Banco's data scientists were challenged to expand the credit card services of existing customers, easily determine credit risks with better accuracy and better predict payment defaults. Since deploying H2O.ai's software on IBM Power Systems, Visión Banco's data scientists have saved time and increased revenue by building and deploying models that have doubled the number of credit products per customer. Additionally, its team was able to pinpoint credit and default risks with greater accuracy than previously.

"We started using H2O Driverless AI for critical use cases: propensity to buy, default prediction and credit risk scoring," said Ruben Diaz, data scientist at Visión Banco. "By using Driverless AI on IBM Power Systems, we have been able to significantly improve the accuracy, in less time, of our credit risk scoring model. These new models are now in production doing credit scoring in real-time. We were also able to double the propensity for our banking customers to accept an offer of credit products, such as credit cards, which is a great result. We plan to use the platform for more use cases in the future."

IBM and H2O.ai began their collaboration earlier this year so H2O.ai and IBM can provide enterprise customers with leading-edge capabilities designed specifically for machine learning workloads. IBM resells Driverless AI, advanced automatic machine learning platform, on IBM Power Systems to allow customers to harness the power of machine learning for competitive gain.

"Visión Banco is an inclusive bank focused on improving communities with the creativity of its teams and operations. Its successful deployment of H2O Driverless AI on IBM Power Systems showcases how automatic machine learning can empower financial institutions to deliver data services to protect and enrich its brands and communities," said Sri Ambati, CEO and founder at H2O.ai. "Our work with IBM to bring accurate and easy to use machine learning on faster and cheaper systems is transforming customers - equipping them to win in a fast-changing world."

"The powerful combination of IBM Power Systems and H2O Driverless AI gives businesses, such as Visión Banco, the ability to apply automatic machine learning to generate extensive value and a competitive advantage," said Sumit Gupta, VP of Cognitive Systems IBM. "We couldn't be more pleased with our collaboration with H2O.ai to create value in our customer base."

IBM Advances AI
Powering the world's two most powerful supercomputers, the US Dept of Energy's Summit and Sierra, the IBM Power Systems AC922 server is the best server for enterprise AI. With the industry's only CPU-to-GPU NVIDIA NVLink interface, the IBM Power Systems AC922 server has up to 9.5x greater memory bandwidthⁱ so data can flow across the system stack. This positions data scientists to train ML/DL workloads up to 4x faster than competitive hardwareⁱⁱ.

AI to do AI
H2O Driverless AI empowers data scientists, data engineers and scientists in all industries to work on projects faster and more efficiently by using automation and state-of-the-art computing power to accomplish tasks that can take months and can potentially be reduced to hours or minutes by delivering automatic feature engineering, model validation, model tuning, model selection and deployment, machine learning interpretability, time-series, NLP and automatic pipeline generation for model scoring.

The latest version of H2O Driverless AI on IBM Power Systems is available immediately for download and use.

About H2O.ai
H2O.ai, a leader in the 2018 Gartner Magic Quadrant for Data Science and Machine Learning Platforms with the most completeness of vision and highest level of customer satisfaction, aims to democratize AI for allⁱⁱⁱ. H2O.ai is transforming the use of AI with software with its category-creating visionary open source machine learning platform, H2O. More than 14,000 companies use open-source H2O in mission-critical use cases for Finance, Insurance, Healthcare, Retail, Telco, Sales, and Marketing. H2O.ai recently launched H2O Driverless AI that uses AI to do AI in order to provide an easier, faster and effective means of implementing data science. H2O.ai collaborates with leading technology companies such as NVIDIA, IBM, AWS, Azure and Google and is proud of its growing customer base which includes Capital One, Progressive Insurance, Comcast, Walgreens and PayPal. For more information and to learn more about how H2O.ai is transforming businesses with AI, visit www.h2o.ai.

Media Contact:
Erika Kamholz
[email protected]
949-282-8560

IBM Media Contact:
Sam Ponedal
[email protected]
916-217-0145

ⁱ Competitive compare: x86 PCI Express 3.0 (x16) peak transfer rate is 15.75 GB/sec = 16 lanes X 1GB/sec/lane x 128 bit/130 bit encoding. IBM POWER9 and next-generation NVIDIA NVLink peak transfer rate is 150 GB/sec = 48 lanes x 3.2265625 GB/sec x 64 bit/66 bit encoding.

ⁱⁱ Results are based IBM Internal Measurements running 1000 iterations of Enlarged GoogleNet model on Enlarged Imagenet Dataset (2560×2560). Hardware: Power AC922; 40 cores (2 x 20c chips), POWER9 with NVLink 2.0; 2.25 GHz, 1024 GB memory, 4xTesla V100 GPU Pegas 1.0. Competitive stack: 2x Xeon E5-2640 v4; 20 cores (2 x 10c chips) /  40 threads; Intel Xeon E5-2640 v4;  2.4 GHz; 1024 GB memory, 4xTesla V100 GPU, Ubuntu 16.04. Software: Chainverv3 /LMS/Out of Core with CUDA 9 / CuDNN7 with patches found at https://github.com/cupy/cupy/pull/694 and https://github.com/chainer/chainer/pull/3762 

ⁱⁱⁱ Gartner does not endorse any vendor, product or service depicted in its research publications, and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions of Gartner's research organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose.

SOURCE H2O.ai