As customers become more knowledgeable, their expectations grow. To address the new demands of today’s customers, insurance companies are looking to differentiate themselves by delivering great customer experiences while controlling risk. Technology innovations and the emergence of IoT are also influencing how insurers are working today, in their quest to become insight-driven.
It’s all about risk control, and now, through configurable machine learning models, event processing and streaming analytics, they can uncover the insights that transform the way they do business.
With InsightEdge, a unified real-time analytics and transactional processing platform, insurance companies can ingest and analyze sensor data across multiple streams and analyze patterns in real time. The result is simplified and accelerated streaming telemetry ingestion for gaining full business value from IoT adoption.
By collecting and analyzing data about policy holders, firms can protect them and provide optimum personalized service. Predictive and geospatial capabilities based on insurance telematics can determine the personalized premium for each customer based on risk profile. Simplifying data ingestion and running advanced analytics on the data in motion provides real-time information for dynamic pricing for the individual customer or as a base for a profile group.
Insurance fraud bears a great financial burden both on insurers as well as their policy holders. Fraudulent claims typically lead to higher overall insurance costs, which impacts not only the financial health of the business, but also those who are seeking equitable insurance coverage. Whether the fraud is around medical billing, claims, or life insurance, fraud detection and prevention is a strategic objective for every insurance company. By combining predictive analytics and machine learning with InsightEdge, insurers are better equipped to recognize the increasingly complex patterns of hidden fraud, where suspicious claims and fraudulent payments can be stopped in time, reducing pay and chase situations.
Promote the long-term success of the business by measuring, evaluating, and reporting on insurance risk metrics in real time.
Delivering instant insights with InsightEdge enables the insight-driven organization and promotes adherence and compliance with regulatory requirements, such as SOX, FINRA, and BCI. This also helps to improve risk analysis with the ability to build a fast data analytics pipeline to perform aggregate risk analysis on various portfolios, leveraging the combination of geo-spatial analysis, Monte Carlo simulations and advanced analytics.
InsightEdge a unified real-time analytics and transactional processing platform, can help to evaluate the risk in the portfolio by leveraging the combination of geo-spatial analysis and Monte Carlo simulations, running directly against transactional data, while leveraging low latency advanced analytics to power the insight-driven transformation.
In addition, efficient IoT sensor data ingestion and aggregation, along with advanced analytics enables a dynamic analysis, the generation of the optimal risk model, and customer engagement personalization.
Unifying AI & ML with transactional processing, InsightEdge can help run sophisticated models to analyze policy-holders’ behavioral patterns (such as driving habits), to predict which behaviors are most likely to result in an event that requires payment, such as an accident.
With real-time streaming analytics, machine learning, and advanced predictive analytics insurers can predict policy-holder and regulatory-related risk to avoid the unnecessary loss emanating from avoidable claims payments and non-compliance, to protect the financial health of the business.
Learn how InsightEdge is being used by Financial and Insurance Services to become insight driven.
Due the the highly regulatory nature of insurance, it’s critical for this Insurance Company to have an understanding of all of its risk across policies. This is especially especially difficult due to the company’s transactional nature which creates variable pricing models based on the bundling of services, meaning very few standardized policy practices.
The customer required the ability to secure, analyze and utilize the huge amounts of data, requiring a unification of transactional, operational and analytical processing.
GigaSpaces in-memory real-time analytics platform delivered the performance and agility to help accelerate innovation and advance digital transformation and customer satisfaction initiatives including