There’s a lot being said and written about Big Data’s role in the feverishly exciting world of “predictive analytics”. The excitement is of course palpable. So what’s really new in the big bad world of Big Data and Predictive Analytics today? What revolutionary advances are we seeing today that take on big data and emerge with critical insights?
While we ponder on those significant questions, I want to explore how we at Prime address this so-called “next wave of innovation”. Especially in case of the insurance industry, if it wants to thrive in the world of big data and analytics with better tools and applications, they’ll need to manage complex and large-scale organizational change.
So consider the insurance industry, larger Property & Casualty insurers have always been universally embracing analytics across all financial and risk management areas and most operational areas. While only about half of midsize insurers have similar plans, this lack of analytic capability among smaller P&C insurers will intensify the competitive advantage that larger insurers already enjoy in other areas.
Moreover, even in the underwriting process, the analyses of large data sets and pricing policies performed by actuaries are critically important to note and, therefore, is not new to an insurer’s continued existence and profitability.
What’s New? A Broader Reach
Demographic shifts such as the economic downturn, greater longevity, and new competitive challenges are all prompting many changes in the insurance business. These changes encompass the type of products being sold, how those products are marketed and advertised, how risk is assessed, and how fraud is detected. However, the amount and variety of data available to insurance companies today provide a wealth of new opportunities to increase revenue, control costs, and counter competitive threats.
According to a recent survey conducted by Willis Towers Watson’s titled “Predictive Modeling survey”, in the next two years many property & casualty (P&C) insurers will continue to employ predictive analytics modeling techniques.
“Insurers also project their big data usage to grow across many business functions. Presently, big data is most useful for insurers’ work associated with pricing, underwriting, and risk selection (42%).”
It is estimated that in terms of volume we create 2.5 quintillion bytes of data per day. That’s 2,500,000,000,000,000,000 bytes of data! That’s staggering!
In several ways, harnessing this real-time voluminous amounts of data that flow through the various networks, can work out to be a critical competitive advantage over the long-term for your business.
Prime’s Mantra: Slice and Dice to Gain Insight
Predictive analytics is an enabler of big data. Prime Insurance solutions leverage big data and predictive analytics by utilizing statistical techniques to help develop a model to give predictions for future outcomes and how likely a scenario is to occur. This can help in identifying the probability of a policy-making a claim at some point, which eventually helps enterprises become much more efficient. Some of the distinctive big data techniques and services provided by our consultants include:
- Generalization
- Classification
- Characterization
- Clustering
- Pattern Matching
- Data Visualization
Our Insurance solutions also help with response time and improvement in insurance carrier performance. Underwriters can use advanced tools and methods to provide themselves and customers with information in real-time. With our predictive analytics tools, insurance companies have a big opportunity to capitalize on what they did not previously know, something that could bring in new streams of revenue.
