How Data Analytics Solutions Complement Fraud Detection

By Insurance CIO Outlook | Tuesday, July 28, 2020

Modern data analytics addresses the vulnerabilities of insurance, propounding a comprehensive fraud detection and mitigation capability.

FREMONT, CA: Conventionally, the process of fraud detection in insurance was accomplished by the claim agents who depended on certain facts and a significant amount of intuition. In the current scenario, not only is the process time-consuming but also ineffective in addressing the complexities involved in the modern insurance sector. However, the massive advancements in analytics solutions offer an alternative to the conventional means of insurance fraud detection. Modern data analytics solutions offer tools to make fraud detection possible in various insurance verticals such as policy renewals, fraud detection, and in periodic checks.

Fraud detection requires collection as well as the processing of a massive amount of data from claims, underwriting, law enforcement, and several other insurance verticals. Further, the addition of data from various verticals creates additional pressure on the fraud detection capabilities of the insurance firms. Fraudsters are also eyeing third-parties as possible vulnerable points to gain access to the insurance data sets. Thus, insurance firms need to ensure that the possible loopholes within the organization, as well as pertaining to their respective third parties are covered.

An insurance firm contains a massive collection of historical data. If there is a means to refine and process such data in a way to gather insights into past fraud patterns, insurance firms can better prepare to counter any such incidents in the future. Data analytics can also utilize technologies such as artificial intelligence (AI) to extract insights from such data sets that are relevant to fraud detection efforts. Insurance firms can feed the AI-algorithms with the repositories of past data and generate relevant insights to fight similar fraud attempts in the future.

Advanced analytics solutions can also be deployed to capture real-time anomalies and draw conclusions by analyzing data from various sources. Further, deployment of predictive analytics capabilities can enable the insurance firms to reduce losses by identifying frauds before the claim is paid.Insurance firms understand the need for advanced analytics solutions to counter various kinds of insurance frauds. Incorporation of a data analytics solution that addresses the general as well particular security needs of an insurance firm will provide an operational edge to the firm.

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