Tag: data analytics

Reinventing the Customer Experience with Advanced Analytics

Customers expect seamless and excellent customer experiences – that’s where the power of advanced analytics comes into play.

December 3, 2019 by Kelly Nguyen
Three Things to Do as You Start Your Advanced Analytics Journey

As the opportunities surrounding advanced analytics continue to grow, lenders are eager to adopt these capabilities. However, there are key things to keep in mind.

November 12, 2019 by Kelly Nguyen
Five Advanced Analytics Drivers in Your Lending Organization

Better, faster and smarter decisions. It all starts with data and advanced analytics.

October 15, 2019 by Kelly Nguyen
Secrets to Avoiding Data Overload in Consumer Banking

Retail banking leaders want to incorporate more data into their business strategies.However, many companies don’t know how or where to start.

September 24, 2019 by Kelly Nguyen
The Future of Technology and Innovation

The pressure to innovate amid technological progress poses an opportunity for us all to rethink the work we do and the way we do it. Are you ready?

September 19, 2019 by Laura Burrows
State of Credit: 10 Year Lookback

Experian's annual State of Credit Report includes consumer credit data trends and a 10 year look back to when America started to enter the recession.

May 20, 2019 by Stefani Wendel
Experian: Powering Innovative Fintech Solutions

Today's world demands finance redefined - and fintechs have answered the call. Driven by innovative technology and data, what's next for fintechs?

February 14, 2019 by Brittany Peterson
Four Features You Need in an Analytical Environment

Any analytical environment is only as good as the data you put into it. Check these four key features when choosing the right one for your organization.

October 24, 2018 by Jesse Hoggard
Getting Beyond the Binary to Solve the Business Problem of Big Data

You want to use big data, but how do you make your analytics truly actionable to stay ahead of the competition? Using an analytical sandbox is the answer.

October 4, 2018 by Jesse Hoggard
Is Big Data a Big Problem?

There are a lot of people talking about big data who are not fully leveraging the value of their data. How do you use data to innovate and stay competitive?

September 27, 2018 by Jesse Hoggard
Bringing machine learning to data analytics

Risk analysts are insatiable consumers of big data who require better intelligence to develop market insights, evaluate risk and confirm business strategies. While every credit decision, risk assessment model or marketing forecast improves when it is based on better, faster and more current data, leveraging large data sets can be challenging and unproductive. That’s why Experian added a new functionality to its Analytical Sandbox, giving clients the flexibility they need to analyze big data efficiently. Experian’s Analytical Sandbox now utilizes H2O –an open source machine learning and deep learning platform that can model and predict with high accuracy billions of rows of high-dimensional data from multiple sources in various formats. Through machine learning and advanced predictive modeling, the platform enables Experian to better provide on-demand data insights that empowers analysts with high-quality intelligence to inform regional trends, provide consumer transactional insight or expose marketing opportunities. As a hosted service, Sandbox is offered as a plug-and-play, meaning no internal development is required. Clients can instantly access the data through a secure Web interface on their desktop, giving users access to powerful artificial and business intelligence tools from their own familiar applications. No special training is required. “AI monetizes data,” said SriSatish Ambati, CEO of H2O.ai. “Our partnership with Experian democratizes and delivers AI to the wider community of financial and risk analysts. Experian's analytics sandbox can now model and predict with high accuracy billions of rows of high-dimensional data in mere seconds.” Through H2O and the Experian Sandbox, machine learning and predictive analytics are giving risk managers from financial institutions of all sizes the ability to incorporate machine learning models into their own big data processing systems.

May 9, 2017 by Gregory Wright

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