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

Data Analytics for Claims Fraud Detection

Advanced analytics go beyond transforming customer experience and marketing functions and are increasingly being implemented for fraud detection. Cogitate Technology Solutions examines some methods of using predictive analytics to combat fraud.

Often purported to be a ‘victimless’ crime, claims fraud costs insurance companies, and ultimately policyholders, billions and drives up the insurance costs for everyone. While insurance companies have established effective fraud departments, yet undetected claim frauds are on the rise. Claims fraud statistics tracked by several organizations show a consistent increase over the years.

Traditionally, claims fraud detectionis performed by special investigators, insurance agents, claims adjustors and assessors. Armed with limited data about past frauds,heuristics based on a set of fraud indicators, their experience and their instincts, they would personally verify the genuineness of a claim. In reality, there aren’t enough trained eyes to examine all the claims and fraudulent claims slip through. The increase in available data comes with its own challenges as fraud detection becomes onerous and exhausting due to data overload. As multiple data sources are linked, it becomes practically impossible for humans to spot emergent patterns and insurance solutions that can help stem claims fraud are the need of the hour.

Analytics for improved fraud detection

Insurance houses are now beginning to rely on analytics to identify fraud or potential for fraud. The seek to convert available data into actionable intelligence to detect fraud much earlier in the cycle and improve underwriting checks. Analytics helps insurers sift through gargantuan amounts of data to identify patters and data anomalies across multiple data sets. Predictive analytics uses a mix of regression models and advanced techniques to examine the complexity of a claim and to determine if it requires further examination. This helps in assigning appropriate staff based on the complexity of claims while improving the processing speed of legitimate claims and increasing customer satisfaction. 

In combating fraud, three methods of advanced analytics are taking center stage:

Predictive modelling examines data elements to reveal patterns that indicate a high proclivity for fraud. One of the primary ways of fighting fraud, especially in P&C Insurance, is a combination of predictive modelling and text mining. Text analytics are applied to search for keywords in unstructured data such as assessor notes, emails, accident descriptions etc. to identify fraud patterns. Predictive modelling allows insurance providers to move from pay-and-chase to prevention with these prophetic insights.

Social network analysis(SNA), or link analysis, reveals connections to expose collusive activities. SNA helps in identifying proximities and strength of relationships among people, organizations and groups. This, along with studying the flow of information between these entities provides P&C insurance providers valuable insights into any affiliations between insureds and fraudulent groups.

Link and geo-spatial analysis offer a context for a larger and more complete view of claims that might not appear false at the first glance.  Link analysis allows investigators to inspect any possible connections between the parties involved. Geo-spatial analysis investigates the physical proximity of claimants and provides location-based information about the claim. Geo-spatial analysis also helps in identifying the exact area affected by a disaster and weed out fraudulent P&C insurance claims for surrounding areas that are not actually part of the affected area.

If companies cannot afford a custom enterprise fraud analytics system, there are out-of-the-box analytics for insurance solutions available that can improve upon rule-based manual systems. For the power of analytics to be harnessed to its fullest potential, insurance companies must implement correct data-driven practices. They will need to break data silos, combine structured and unstructured data and cross-link multiple data sources to arrive at the full picture of the insureds across underwriting, Claims Management Software and policy management. To understand how Cogitate Technology Solutions can help you with implementing analytics for fraud detection, please visit www.cogitate.us.