H2O.AI and IBM Deliver a Competitive Edge for Visión Banco with Machine Learning
Paraguay Bank Leverages Automatic Machine Learning Capabilities of H2O Driverless AI on IBM POWER9-Based Systems with GPUs
IBM and H2O.ai 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.
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“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.
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“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.”
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Having been a credit manager, I find it interesting to see how this new credit scoring model operates. We didn’t have tools like this back in the day. If it’s as accurate as claimed, it should go a long way in aiding responsible lending. I’m also interested to see how machine learning, in general, will improve AI products across multiple applications. Say, for example, could we turn the technology to aid IT help desk outsourcing companies. In theory, no one should understand how a machine or piece of software works like another machine. However, will it be able to explain this in an understandable way?
Having been a credit manager, I find it interesting to see how this new credit scoring model operates. We didn’t have tools like this back in the day. If it’s as accurate as claimed, it should go a long way in aiding responsible lending. I’m also interested to see how machine learning, in general, will improve AI products across multiple applications. Say, for example, could we turn the technology to aid IT help desk outsourcing companies. In theory, no one should understand how a machine or piece of software works like another machine. However, will it be able to explain this in an understandable way?