Fraud Detection:
Fraud is big business. The Coalition Against Insurance Fraud (CAIF) estimates that insurance
fraud costs U.S. consumers at least $80 billion every year. And the Property and Casualty
Insurers Association of America (PCIAA) estimates that at least 10% of insurance payouts are
based on fraudulent claims. Healthcare, workers' compensation, and automotive insurance
are the three areas most affected by insurance fraud. Today, more insurance companies are
leveraging data analytics and predictive modeling to help identify fraud patterns. By
combining internal and external data, insurers are now able to visually link individuals or
organizations and to quickly see patterns that aren't apparent in spreadsheets and tables.
Customer Experience:
Fast and accurate have been the watchwords of the claims world for many years. Customers
expect quick resolution and prompt payment for their loss. But the "new" customer
experience requires much more including 24/7 multi-channel communication, process
transparency, and a higher degree of personalization. Customers want insurers to know them
and understand them and rely on their ability to address their problem, quickly and efficiently.
Cloud
In less than five years many organizations have gone from highly skeptical to fully embracing
hosted or "cloud-first" strategies. The factors driving this increase adoption are:
Claims Ecosystems:
Organizations are expanding their claims functionality with an ecosystem of third-party
applications. The "new" applications require cloud API gateways that manages the interface
between claims management system and third party solutions.
Cloud Capacity:
Hosted solutions provide nearly limitless capacity for storing data.
Data Lakes:
The variety and volume of data collected and stored on a daily basis continues to increase.
The Cloud provides organizations with the ability to store and process large volumes of data
without a predetermined structure.
Artificial Intelligence (AI) and Machine Learning:
Hosted and cloud environments provide massive computing power to analyze and derive
value from the growing quantities of available data.
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