Big Data Proactive Risk Management

Analytics Insurance Industry - War on Insurance and Healthcare Fraud

Insurance claims fraud is a significant and growing challenge for the entire insurance and healthcare industry, including life, health, and property & casualty. Estimates are that claims fraud in the U.S. P&C industry alone cost insurers US$64 billion in 2012 and averaged 14% of total net premium written. Insurance fraud exists in every line of business but is especially pronounced in individual or personal lines of business, including homeowners, private passenger and commercial auto, and workers' compensation.

Big Data Analytics and Predictive Modeling

"Business Analytics" refers broadly to the expertise, technologies, and quantitative methods applied to iterative exploration and investigation of past business performance to gain insight and drive business tactics and strategies. It makes extensive use of data, statistical and quantitative analysis, and predictive modeling to drive decision making and ultimately improve business performance. 

Predictive Analytics is an area of statistical analysis that involves extracting information from historical data and using it to predict future trends and behavior patterns. The core of predictive analytics relies upon capturing relationships between explanatory and predicted variables from past occurrences and exploiting the captured relationships to predict future outcomes. While the accuracy and reliability of the results depends on the quality of both the data analysis and the underlying assumptions, combining advanced Business Intelligence and Big Data capabilities with predictive analytics creates powerful business analytics tools.

Integrated Big Data analytics―the marriage of analytics and external data―is emerging as a game changer in the insurance industry because it combines analyses from multiple business intelligence interfaces and enables users to predict, often with surprisingly high accuracy, the future behavior of almost any category of business events. Business Analytics has four major application areas in the insurance industry: claims and risk management, underwriting and pricing, demand management for distribution channels, and producer acquisition and value management. Of these, claims and risk management is among the operational areas of insurance best suited for the many and varied benefits of predictive analytics. Through the use of applied analytics, carriers are finally catching up with the rest of the financial services industry in using technology to reduce fraud through new, powerful capabilities, such as link and pattern analyses.

Insurance Companies can design and implement fraud management strategies from an enterprise solution perspective in order to leverage the full power of Analytics and Big Data across underwriting, contact center operations, and claims processing.

Accelerate, apply, and achieve big results from your Big Data initiative. Big Data represents an opportunity to change how you work, play, and live by tracking new signals within the digital noise. Many organizations lack the expertise to connect Big Data projects with the business imperative. Complex IT infrastructure can inhibit organizations from tracking new signals cost-effectively and at the pace of business. If that weren’t enough, organizations often lack a way to apply those signals within their daily business operations.

You can achieve tangible results for your top business priorities by accelerating how you acquire, analyze, and act on data insights and applying those insights continuously through your people and processes.  Data volumes will continue to explode to 6 trillion terabytes. IT spending on Big Data will grow by 30%, shifting toward analytic tools and apps, and be increasingly delivered by cloud.