The Earnix Blog

The Earnix Blog is a community blog for financial industry professionals that share a passion for predictive analytics

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Five Insights Gleaned from the Casualty Actuarial Society Ratemaking, Product, and Modeling Seminar

Earnix recently attended the Casualty Actuarial Society Ratemaking, Product, and Modeling Seminar (CAS – RPM) event in Chicago, Illinois. While the conference covered many innovative topics on trends in telematics, usage-based insurance, and regulation – Earnix was there to present  specifically onRead More »

Earnix Summit – The Evolution Revolution

As new technologies enter the market, how can we, as leaders in financial services organizations, compete and do things smarter, faster and cheaper? During the 6th annual Earnix Analytics & Innovation Summit held in London, we saw firsthand how some of theRead More »

Customer Experience and Machine Learning: Practical Applications

The notion of using analytics to improve customer experience has changed the landscape and thought process of businesses over the past several years. As machine learning becomes further democratized, or more pervasively available, it is making its way into many enterprise softwareRead More »

Personalized Customer Analytics: The Key to the Future

As the Chief Analytics Officer for Earnix, a Tel Aviv-based provider of advanced analytics solutions for the financial services industry, I am focused on how financial services companies can use data and analytics to figure out what their customers really want andRead More »

Challenging The Status Quo: How Banks Can Win In The PSD2 World

In less than six months, the second Payment Services Directive (PSD2) will have been implemented into law in all European Union member states. The Directive is a landmark moment in banking, introducing competition to the payments market and overturning the status quo.Read More »

Are You Making these 7 Mistakes When Deploying Your Models?

I am always excited to see more organizations wanting to use analytical models at the center of their business processes. Like most things in life, the road to success is not straight; sometimes there are a few road bumps to navigate. TheRead More »

How Insurers Can Better Understand Multi-Product Customer Behavior – Machine Learning Can Help

It’s all about the data. That’s the message I kept hearing at the CAS Ratemaking and Project Management conference in San Diego this spring. The message was so strong, that I was asked to present my seminar, “Multi-Product Optimization: Challenges and Opportunities”Read More »

Conversion & Retention Modeling Done Right: The Four Keys to Success

These days, many industries are spending millions of dollars in research to achieve their customer-centric goals. The insurance industry is no different. Insurers are continually raising the analytical bar to gain a better understanding of their customers. Being able to accurately predictRead More »

On the Breakfast Menu: AI and Prescriptive Analytics in Financial Services

In early March, Earnix hosted an executive breakfast in New York for consumer banking executives who work with analytics related to offer management and pricing. Two speakers presented their views on the state of analytics in financial services. One provided a long-termRead More »

Analytics Hackathon – A New Way for Insurance Analysts to Sharpen Skills

The insurance market has never been faced with so many new technologies, bringing with it increased opportunities to leverage analytics in the industry. Yet, for many insurance professionals, keeping pace in this very dynamic market is challenging, which is why Earnix isRead More »
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Machine Learning Survey 2017

This first-of-a-kind survey uncovers how insurance executives understand how the industry leverages Machine Learning today and how they expect Machine Learning to impact the industry in the near future.

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Open Banking: A Platform for Personalisation

Read the Earnix Open Banking report to learn how to prepare for the new open banking environment as well as see three Earnix open banking use cases.

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