Content that originates directly from customers as well as content from employees about customers can help those in the finance and risk management areas to identify and react to drivers of loss. Text analytics allows connections to be made from information currently trapped in sources such as adjuster notes, claims documents and warranty information.
Key Benefits
Current manual processing of information and dependency on rare flashes of human insight do not leverage all the information collected on cases. Text analytics and sentiment analysis allow the creation of an automatic method of detecting anomalies for:
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Systematic detection of trends and spikes through predictive analytics can lead to insight around possible loss areas.
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Improved claim handling success rates with more efficiency in the claims processing system.
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Substantiation of claims or fraud identification for the adjustors, analysts and investigators by the swift classification of the enormous amounts of free-form data.
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Comparison of sentiment and topic categories against competitor information to determine whether performance levels are appropriate.