TEL AVIV, Israel, June 1, 2017 /PRNewswire/ --
- Earnix survey shows risk modelling top use
- Lack of knowledge is biggest barrier to expanded adoption
Earnix, a leading provider of analytics solutions for the financial services industry, today announced the results of a global survey of insurance executives, which shows wide adoption of Machine Learning across the globe, and the expectation that ML will bring "significant" change to the industry over the next three to five years.
Over half (54%) of the almost 200 insurance executives surveyed said that their organization was using Machine Learning for predictive analytical modelling. Of those deploying the technology, 70% said they were using it for risk modelling; followed by demand models (45%) and fraud detection (36%).
Although nascent, most companies using Machine Learning have realized measurable benefits. Over half of the respondents (57%) said that Machine Learning has made their analytical models far more accurate, which has led to better risk assessments, and ultimately better decisions.
The survey found that the main barrier to wider adoption is a lack of knowledge and expertise within organizations. Eighty-two percent say their organization is relatively inexperienced with Machine Learning.
According to Udi Ziv, CEO of Earnix: "The insurance industry has always been data-driven and the use of Machine Learning is a powerful trend that will quickly become a competitive edge for those who embrace it. Earnix was an early adopter of this technology and is working with its clients to integrate it into their analytics, enabling them to automate more of their processes and predict outcomes more accurately. The combination of advanced analytics with Machine Learning is truly an innovation with direct and measurable benefits."
The survey report, named "Machine Learning - Growing, Promising, Challenging," is available on the Earnix website and can be downloaded at no charge here: http://bit.ly/EarnixMachineLearningPR17
Earnix provides an advanced analytics platform designed for the financial services industry, which integrates real-time decision-making capabilities into the business process, delivering significant results. We enable financial institutions to better compete in a new environment of highly personalized service offerings by using advanced analytics to predict the best set of customer offers: the right product, right price, right time, through the right channel. Today the platform is most commonly used for determining demand-based pricing, and can be used to optimize other offer components such as product features and distribution channel. Machine Learning can be used to reduce cycle time and automate updates of predictive models, which can then be deployed into the production systems using Earnix capabilities. For more information visit http://www.earnix.com.
For More Information:
George Ravich, Earnix Chief Marketing Officer
Dan Williams, Rostrum