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Data Collection And Insurance Fraud Detection


Data Collection And Insurance Fraud Detection

While insurance companies are primarily tasked with risk management in order to grow their businesses and succeed, a focal area of concentration is increasingly that of the risk of fraud. The rise of technology has, unfortunately, provided enhanced opportunities for fraudulent practices both by company staff members as well as those who are insured.

Data Collection and Insurance Fraud

In years past, fraud detection and management was assigned to claims representatives who had to rely upon such subjective information as word-of-mouth as well as their own intuitive instincts. Thankfully, it is now possible to streamline this process with greater objectivity and precision thanks to technology that utilizes data collection and disseminates the information over a wider scope within the company such as underwriting, renewal of policies and overall company administration. These systems are available across a broad spectrum of insurance company technological types including captive insurance technology.

Captive Insurance Technology

When considering captive insurance technology for fraud detection, it is important to take into consideration the potential for error as well as misinformation since a captive insurer is wholly owned and controlled by those whom it insures. There is a smaller margin for risk tolerance since full disclosure is standard protocol.

The function of collected data is as varied as the types of insurers that use it. The cost of collecting and maintaining data for fraud surveillance must be weighed against the reasonable risk to the company’s bottom line. If the instances of fraud are more prevalent in a given insurance company, then analysis of the pertinent data for weighted elements that may indicate future trends may be worth the cost of the system needed to perform the analytics. In the realm of captive insurance technology, having adequate systems in place to protect the assets of the insured against fraud is almost always considered a prudent investment.

Data Collection

One of the problems frequently encountered is that of the changing face of criminal behaviors. This can make it difficult to predict future fraudulent activity with any degree of accuracy. For this reason, analyses should include algorithms to assess the viability of data integrity.

Despite the challenges outlined above, insurers are seeing improvements in fraud detection and prevention as these systems are used. Many companies are seeing data analyzed in real time. Others are able to scan for fraud up front before a claim is approved or a policy issued.

While no technological system will ever fully replace the human factor in evaluating claims or policies, agents and field representatives now are feeling a greater sense of support and empowerment in making decisions whether in-house or on site.