How Insurers Are Using Technology to Deal with Insurance Claims Fraud

 This post details the growing menace of insurance claims fraud. It is a problem that nearly all insurers are battling, but with limited success. The fact that fraudsters are always a step ahead by misusing technology to achieve their nefarious deeds makes it even more difficult to manage the problem. Technology is the only way of mitigating the instances of claims fraud and empowering insurers to deliver their services more effectively.

Insurance claims fraud is an area of serious concern for insurance providers, as the instances of such scams are proliferating globally. Scammers indulge in inflating claims by manipulating facts and making a pile of cash illegally. It forces insurance companies to invest heavily in system upgrades, technology, and manpower to proactively detect such fraud attempts and mitigate potential losses.

The Challenges: 

Insurance providers have been relying primarily on the judgment of agents and industry experts to detect instances of frauds. While this was a reliable method in the past as there were limited number of cases, in the modern world it is impossible to keep a track on fraud using human resources.

• It is virtually impossible to scrutinize all claims manually.
• Fraudsters are using newer and more sophisticated ways of perpetrating such crimes.
• This has entailed the need to use technology to deal with this growing and serious crime.

 

The rise of technology such as data analytics has created a world of endless potential for organizations operating in the insurance sector. While cost concerns and regulations have been the reasons for slow adoption of data analytics by the insurance sector in the past, all that is rapidly changing because of the intense pressure on the industry to cut down the colossal losses caused by claims fraud.

There is a lot of regulatory importance placed on protection of personal information, with new layers of security being added regularly. This has made it extremely tough for insurance companies to access data from various sources for fraud predictions. Data analytics has proved to be a game-changer for the industry and is helping insurers manage claims fraud instances better.

Fraud Analytics Software

Insurers are incorporating insurance fraud analytics software into their business processes to detect fraudulent practices and detect such incidents early and proactively.

Fraud analytics software systems can reduce claims fraud by gathering data from various sources and collating it into meaningful and valuable information. Predictive capabilities of the software can help companies apply the process to a large area of business operations and improve fraud detection significantly. The software can be used for:

• Identifying optimal risk level
• Gaining qualitative insights from data
• Mitigate fraud risk at insurer’s end
• Eliminating fraud risk at the agent’s end
• Moving from manual to automated underwriting
• Establishing accepted limits of risks
• Automating procedures to identify risk assessment for determining various factors such as coverage, profitability and others

 

Understanding Legacy Systems

One of the biggest challenges of adopting analytics software is the need to upgrade systems to the latest versions. With technology evolving rapidly and continuously, this might entail a fairly substantial investment. Also, there are concerns around use of a third-party service or software because of privacy protection issues. Insurance companies might not have absolute control over data which can result in significant liability.

Insurance Fraud Detection Solutions:

Advanced claims fraud detection solutions are driven by technology. It works in the following ways:

Detection of Anomalies:

Multiple metrics are created to compare the behavior of various entities. The system makes use of statistical analysis to detect any anomalies that deviate from the normal behavior patterns of agents and customers.

Analysis of Claim Notes

Analytics can help in extracting information by going beyond structured data. In simple terms, it means that it can pull data about circumstances of a specific incident, the parties involved, the damage caused, treatment costs and other related data vital for claims settlement.

Investigation of Anomalies:

Agents and customers pointed out as anomalous on more than one count are singled out and detailed analysis carried out to find out the reasons for the anomalies. Business rules can be set up to prevent misuse and future frauds.

Conclusion

Insurance frauds are generally carried out in a very organized manner across the globe. In the modern world, it will be difficult to detect them without using sophisticated analysis methods. Insurers must leverage newer technologies to prevent, detect, and filter frauds. This will help improve claim adjustment expenses and improve the efficiency and performance of the industry.

The Nexus of Forces and Insurance Fraud Analytics

Gartner Inc coined the term Nexus of Forces to describe the concept of how the collective power of four forces - social media, mobility, cloud computing and information patterns –is rapidly shifting the nature of digital business and creating new business opportunities. With great transformative impact individually, the intersection shows extraordinary potential for transmuting industries and pushing fresh opportunities for information innovation.

A key transition element for many industries, the nexus empowers insurance providers to alter and adapt business processes in real time through this blend of technology, data and analytics. Gartner also makes the case for strategic use of the nexus instead of piecemeal, incremental investment in the individual constituents. Many insurance providers have invested heavily on data insights, but the true potential of these forces lies in the future-focused insurerem bracing these advancements fully for a competitive edge.

Among the many advancements made possible through this confluence, one of the foremost is strengthening insurance fraud management systems by deploying innovative fraud technology and enhanced modeling. As insurance fraud grows more sophisticated, the nexus allows insurance providers to deploy more aggressive and proactive insurance fraud management systems. Innovative strategies that leverage a combination of data, new technologies and capabilities to support insurance fraud analytics and prediction hold rich potential for the innovative insurance provider.

Some key information innovations for reducing underwriting and claims fraud include predictive modeling and anomaly detection through enhanced analytical and prognostic capabilities. Business rules-based detection and classification supported by evidence-based data assist faster identification of fraud. Similarly, pattern detection and identification assist identification of new specious behavior and improve modelling.

Scoring algorithms that use historical and other claims data to generate the fraud probability score of a claim and predict probability of fraud are such advancement. Solutions based on complex machine learning models and neural networks are trained to identify and predict fraud using historical and other claims data, as well as learn new patterns of fraud and protect against future risks.

Early identification of fraud networks through social network and trend analysis helps in discovery of fraudulent parties involved in suspected fraud and in the creation of an association-based network graph based on location, address and individuals. Once a fraud collusion network is identified, multiple filters can be applied on the network graph to gather more data which may not be available via traditional BI practices and help further hone claims fraud analytics capabilities.

Cogitate Claims Fraud Network Analysis (CFNA) allows faster identification of fraud through the use of multiple scoring tools, neural networks and fraud collusion networks. CFNA uses artificial intelligence, machine learning, advanced insurance fraud analytics and social network analysis for claims fraud analytics and protects insurers against spurious claims.

Claims reflect in CFNA within 24 hours of the First Notice of Loss (FNOL) and with automated backend processing, fraud probability scores and network graphs are generated right at the FNOL stage. Segregating fraudulent and non-fraudulent claims to assist faster settlement of claims ensures enhanced satisfaction for the customer and significant economies for the insurer. Early referral of fraudulent claims to the Special Investigation Unit (SIU) and automated assignment to adjustors and SIU helps in faster claims settlement and brings further savings in operational costs for insurance providers.

To learn about the many ways Cogitate can help insurance carriers reduce loss ratio and bring in significant savings, contact us today