Customer behavior is a complex subject that affects the insurance industry in fundamental ways, from product development, marketing and distribution to in force management, financial reporting, and risk management. Insurance industry is using advanced analytical techniques to better understand customers. However the gap is beginning to narrow as more and more insurance companies are realizing the benefits of using advanced analytics for designing products, segmenting and developing metrics for risk management. Furthermore, advanced analytics have given birth to a host of new and emerging technologies that are radically different from legacy technologies that most insurance companies use today. For example, in-memory technology makes it possible to run queries in minutes instead of hours and natural language processing serves as a more targeted, semantically –based complement to pure statistical analysis.
The overall effect of these developments will be greater depth and breadth of analytics talent throughout organizations, significant improvements in management processes, and new products that deliver greater value to customers and to society. According to a recent McKinsey report a new wave of innovation and applications of advanced analytics is emerging in all types of product lines and business functions. Additionally in a market report, conducted by Chilmark Research, describes that healthcare organizations of all sizes are now transitioning to new models of reimbursement, and are facing an influx of clinical data via newly deployed EHR sources. They understand that they must now harness new clinical data sources, but find themselves lacking in IT resources with a deep understanding of clinical data integration and analytics.
Healthcare organizations are looking more toward predictive analytics techniques, which take an understanding of the past to predict future activities and model scenarios using simulation and forecasting. For example, analytics can enable the compilation of information about trends, patterns, deviations, anomalies and relationships and reveal insight.
Frost & Sullivan, projects the usage of advanced health data analytics solutions in hospitals will increase from 10 percent adoption in 2011 to 50 percent adoption by 2016, representing a 37.9 percent compound annual growth rate and a 400 percent uptick in baseline.
The challenge for health insurers lies in infrastructure. As they start integrating platforms to capture more data, many find that healthcare systems and connectivity are fragmented. A lack of infrastructure to capture data is the biggest challenge for most people. In an industry that has been largely dominated by paper-based transactions, electronic documents are still evolving. According to a recent E&Y survey report: In India, the market for online life insurance is expected to increase from approximately INR2b in 2013 to INR80b by 2020.
With the above facts I would like to share a recent end-to-end BI solution using Informatica and Tableau that we have implemented for a leading health insurance firm. They required a scalable BI data model to support their current ERP migration. Accessibility of reports developed and maintained was critical. The department was in search of an effective front-end tool that has powerful visual analysis features. Developed reporting /visualization solution using Tableau that improved customer experience across all touch points. Some of the benefits with the solution implemented include improved efficiency of claims and underwriting operations, helped investigating claim patterns to detect probable fraud. Reduced the cost of managing data across the enterprise and eliminated 20% of legacy reports.