Has Big Data Analytics Helped Insurers Prune Their Losses From False Claims?


False claims cost insurance companies approximately USD 34 Billion every year. Home and auto insurance fraud top the list. No wonder more and more companies are investing in anti-fraud technology in which big data analytics plays the lead catalyst’s role.
But how is big data holding up against traditional fraud detection techniques? A WNS survey on the fraud detection techniques used by Property and Casualty insurers in the U.S. confirms that big data analytics trumps traditional methods in detecting fraud. 
According to the survey, insurers using big data analytics in the claims cycle reported higher benefits such as 40 percent improvement in the average referral time and 50 percent more average referrals. 
Insurers who deployed big data analytics in the investigation stage noticed their average claim investigation cost come down by a staggering 67 percent. The average investigation time for each claim had shortened considerably as compared to insurers who were using traditional methods. In the investigation stage, all insurers who had deployed big data witnessed a reduction in the false-positive and false-negative rates. They also saw a higher number of investigations per investigator.
With big data analytics, companies can calibrate and test their approaches continuously instead of relying on an established model. It gives insurers the flexibility to apply effective models as the situation demands to unravel fraudulent activities. 
If big data has such an impact in the claims cycle, what would be the business outcome if it is deployed across the policy life cycle? Connect with the author here.[Source]-https://www.wns.com/insights/blogs/blogdetail/357/has-big-data-analytics-helped-insurers-prune-their-losses-from-false-claims
big data analytics courses in Mumbai at Asterix Solution is designed to scale up from single servers to thousands of machines, each offering local computation and storage. With the rate at which memory cost decreased the processing speed of data never increased and hence loading the large set of data is still a big headache and here comes Hadoop as the solution for it.

Comments

Post a Comment

Popular posts from this blog

Why, when and how to return Stream from your Java API instead of a collection

Introduction Collections are basic and commonly used data structures. Programmers from the beginning of their career learn how to use them to receive, process and return data. Getting more advanced in Java programming, they find stream() method to convert a collection into a stream and learn how to process data using some of the stream’s useful methods like map, flatMap or reduce. They could also notice that other APIs in Java return a stream too e.g. String.lines(), Matcher.results(), Files.find(), Random.ints(). If you have experience with consuming streams but haven’t produced them yet, this article is for you. I’m going to show you some scenarios where streams can be very convenient and examples on how to use them. Additionally, I shortly mention error handling and resource management. The article is based on standard Java library java.util.stream. It’s related neither to reactive streams nor to other implementation of streams like e.g. Vavr. Also, I’m not going to cover a...
Read more

What is Kubernetes?

Kubernetes (also known as k8s or “kube”) is an open source container orchestration platform that automates many of the manual processes involved in deploying, managing, and scaling containerized applications. In other words, you can cluster together groups of hosts running Linux containers, and Kubernetes helps you easily and efficiently manage those clusters. Kubernetes clusters can span hosts across on-premise, public, private, or hybrid clouds. For this reason, Kubernetes is an ideal platform for hosting cloud-native applications that require rapid scaling, like real-time data streaming through Apache Kafka. Kubernetes was originally developed and designed by engineers at Google. Google was one of the early contributors to Linux container technology and has talked publicly about how everything at Google runs in containers. (This is the technology behind Google’s cloud services.) Google generates more than 2 billion container deployments a week, all powered by its ...
Read more

Best way to learn Java programming

Having said that I am writing this post dedicated to all my young (or I should say beginner) fellows who want to attain a certain level of proficiency in java technology and somewhere would like to take my advice on this. Keep in mind that if you do not like the way to learn java, I am proposing in this post, then just ignore me. Period. OR better, suggest me what you think is the better way to learn java fast or easily. Here I am assuming the people reading this post will be, who are very new to language, so I will start by listing first thing first. Make sure you have prepared your Java development environment ready i.e. You have installed JDK/JRE and you have an IDE like Eclipse. 1) Learn the language basics This is the first step for very obvious reason. If you don’t know the basics then you will never know either what to do next or what you are doing wrong. Initially, I do not expect from you to become the master of all java basic stuffs like keywords, core concepts o...
Read more