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ZestFinance And Microsoft Team Up To Make Explainable AI Widely Available For Lenders

The AchieVer

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Banks and lenders that want to put more profitable ML models to work no longer have to be held back by concerns over ML’s lack of transparency. Today, ZestFinance announced a strategic collaboration with Microsoft to deploy Zest’s machine learning (ML) software tools directly on Microsoft Azure and Machine Learning Server platforms to deliver the first fully explainable AI for highly regulated industries, starting with the financial sector.

Financial institutions will now be able to use Zest’s ZAML suite of tools to build, deploy, and monitor transparent ML credit models on Azure and Machine Learning Server. The collaboration combines the intelligent capabilities of Microsoft’s technology with Zest’s deep focus on explainable ML. Zest has spent the last 10 years building comprehensive and thoughtful software tools that help lenders run powerful ML credit models with full transparency and compliance.

Check out the results of our recent test of ZAML against three other common explainability techniques. The tl;dr? ZAML is more consistent, more accurate and faster than the competition.

Close to 40 million Americans struggle to obtain credit because the simple models that lenders rely on dismiss applicants with little to no history on file. ML credit models use more data and better math to spot worthy borrowers that legacy models overlook. By safely tapping into new customers and re-scoring risk across the credit spectrum, Zest customers see an immediate impact, increasing approval rates by 15% or cutting credit losses by 30%, on average. ML will have an immediate financial impact: Lenders in the U.S. currently lose $750 billion in credit charge-offs each year.

“Microsoft has built amazing ML services for the enterprise that enable IT organizations to manage and scale their infrastructure easily to meet diverse business needs,” says Douglas Merrill, CEO and founder of ZestFinance. “With Zest explainability, businesses can start using Microsoft's ML platforms more broadly for high-stakes use cases that demand transparency and auditability.”

With more efficient models running in the cloud, financial institutions will be able to provide more credit at lower cost across their entire credit portfolio. Prestige Financial Services, a $1.1 billion (assets) auto lender, put a fully explainable ZAML credit scoring solution into production earlier this year. Within six months, Prestige doubled its lending volume without added portfolio risk, expanding credit to deserving consumers previously overlooked by legacy models. “Our success was enabled by cutting-edge explainable AI from ZestFinance with battle-hardened infrastructure from Microsoft that is familiar to manage and easy to scale for our business,” says Rob Eagleston, CTO of Prestige Financial Services. Download the case study.

Zest-powered explainability, compliance, and monitoring tools are available now on Microsoft Azure and Machine Learning Server customers. To schedule a demo or sales call, email us at [email protected]



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