Fintech

Machine Learning Automation

Drives the Fintech Revolution

20190206054039-rsz-shutterstock-728178127

Fintech

While predictive algorithms are now found in most fintech processes — from marketing to underwriting — a challenge has risen to determine the future of the industry. The need to integrate seamlessly with marketers, underwriters, financial analysts and other fintech professionals will force machine learning platforms working in fintech to do more than just pump out predictions: they have to drive results.

Discover how automated machine learning is driving the fintech revolution.

LEARN MORE

ELIZE Solutions captures the knowledge, experience, and best practices of the world’s leading data scientists, delivering unmatched levels of automation and ease-of-use for machine learning initiatives. ELIZE Solutions enables Fintech users and companies to build and deploy highly accurate machine learning models in a fraction of the time.

PARTNERSHIPS

Discover how AI can drive results.

learn more

Fintech

Fintech is exciting. It’s truly a disruptive force in the economy. As the interaction between consumers, businesses, and financial institutions becomes frictionless, there are significant opportunities for fintech organizations to use predictive models. Automated machine learning allows fintech companies to create simpler and more accurate underwriting models, detect fraud in their workflows, and find the right customers for their products.

LendingPaymentsDigital WealthBlockchain

Fintech has fundamentally altered the lending landscape, and machine learning has shined as a game-changing technology for lenders. From making smart underwriting decisions and reducing friction between lenders and consumers to identifying new customers and reducing the churn of existing customer bases, ELIZE Solutions automated machine learning platform helps fintech lending organizations make better predictions, faster.

Download the eBook

Improvements in the flow of capital across borders is one of the most significant benefits of fintech, allowing businesses and consumers to participate in the financial ecosystem in exciting new ways – but significant challenges remain. Fraud has always been a concern in the banking and payments industries. ELIZE Solutions automated machine learning platform allows companies to build predictive models to identify payment transactions that need closer human inspection. By deploying machine learning models in real-time production, ELIZE Solutions helps companies find bad payments before they cause permanent damage.

In an industry dominated by personal wealth advisors, fintech has begun to automate the interactions between advisors and consumers in a way that increases transparency and reduces transactional fees. Machine learning will play a major role in the development of the digital wealth market, addressing the need for increased automation of portfolio management as “robo-advisors” begin to interact more frequently with customers. ELIZE Solutions automated machine learning platform plays a critical role in aligning consumers with the right opportunities to match their risk tolerance and financial profile.

Cryptocurrency and distributed ledger technology is one of the most exciting developments in fintech. Blockchain technology is still in early development, which makes it an ideal candidate for machine learning solutions. These early use cases include detection of identity theft, cyber-attack, and fraudulent and illicit blockchain transactions. ELIZE Solutions is flexible enough to allow blockchain-focused companies to build models that detect all these threats in real-time.

Elize Solutions Cloud, powered by Amazon Web Services

To deliver Elize Solutions Cloud, we have partnered with Amazon Web Services (AWS), the world’s most comprehensive and broadly adopted cloud platform. The flexibility and scale of the AWS platform enables Elize Solutions to deliver a robust, secure, on-demand platform to our customers. This allows rapid deployment of Elize Solutions and allows our users to quickly build and deploy highly accurate machine learning models in a fraction of the time.