Fraud is a business proposition that has earned the attention of criminals. Fraud costs everyone else. The insurance industry invests into fraud monitoring solutions to protect the everyone's interests.
In response, fraudsters are using increasingly sophisticated techniques to avoid detection. In this never-ending battle of wits, it has never been more important for insurers to reinvent and seek more effective solutions to this menace; to protect their businesses and clients.
Find out more about the state of fraud in the industry, the threat(s) fraud poses toward insurance companies, and practical steps insurers can take to protect themselves from this ever-present and evolving challenge.
Overview of the Problem
Fraud is a growing problem, and it's not going away. Insurance fraud is a global issue affecting every industry sector—from auto insurance to health care benefits to life and property.
The costs associated with fraud can be significant: they range from millions of dollars in losses per year to billions over time. This depends on how much insurers are exposed to them (with higher exposures leading to more significant losses).
Fraud is complex because it requires multiple actors working together for it to thrive: insurers who need data about what's happening within their systems; underwriters who create policies; brokers who represent clients' interests; agents working directly with consumers or businesses; adjusters trying their best despite all these other forces working against them. And then there are the fraudsters, who don't care about the consequences of their actions.
This last group will do whatever it takes to get what they want. In fact, they don't care how many people they hurt in the process. In some cases, they may derive joy in harming others or seeing them suffer.
Besides the direct cost implication of fraud, insurers have to contend with additional costs in investigating fraudulent claims, recovering duplicitous claims, and possibly facing numerous lawsuits.
But that's just the tip of the iceberg. As a result of too much fraud, insurers put in place stringent measures to curb fraud. Sadly this erodes some level of convenience for users, i.e. fast claim processing and payout. Down the line, it can hurt whatever competitive edge insurers had in wooing clients.
Thanks to AI and big data, insurers can reliably and effectively stop fraudulent claims without sacrificing speed.
The Cost of Insurance Fraud
According to the Coalition Against Insurance Fraud, the cost of insurance fraud to the American economy is $80 billion annually. However, the figure may be higher since this accounts for detected and reported figures.
On a global scale, financial fraud, which insurance fraud falls under, costs the economy approximately $5.127 trillion.
Insurance fraud is a vice that occurs in various forms and is orchestrated by many actors, small-time or sophisticated criminals, and organizations. Some of these entities aim to make money through fraud. However, sophisticated ones may act out of pure malice or to sabotage certain industry players.
No matter how the fraud works or who causes it, it's the policyholders and insurers who feel the pinch.
The Anatomy of Fraud Detection and Prevention Solutions
Fraud monitoring is the process of detecting and preventing insurance fraud. It can be broken down into two categories:
Detection - The detection of suspicious claims, which may indicate a fraudulent claim is being made. More reasons are now quickly proving that AI-powered insurance detection software is a premier solution to fraud detection.
Prevention - Preventing, or stopping, a fraudulent claim from occurring in the first place.
Out of these several effective solutions are emerging to better counter this evolving threat.
An audit is a method of detecting fraud by analyzing historical data of events or transactions. Companies can do it internally or externally, preferably with the help of technology.
An internal audit is performed by an organization's staff and compares policies and claims with actual performance. External audits are conducted by external parties who have no vested interest in the results being obtained by an entity for which they are auditing; this type of audit is often more thorough than an internal one because there are fewer opportunities for bias to creep into results from within an organization's walls.
Companies may perform audits manually or with the help of computer software applications that analyze data sets generated through manual inputting processes into databases (known as "data mining").
Computerized methods allow users to quickly parse through huge amounts of information while reducing human error associated with manual entry methods such as handwriting inputs made on paper documents like invoices by clerks before entering them into their systems manually later when needed again.
This is the process of monitoring activity and looking at historical data to detect fraud. The type and frequency of monitoring depend on the insurer's individual needs, but there are some general guidelines:
Real-time monitoring allows companies to look at transactions as they occur. For example, an insurer has a fraud detection system that alerts them when someone tries to use fraudulent information (e.g., Social Security numbers or bank account numbers). In that case, the system will notify the team immediately after the transaction has taken place for them to take appropriate corrective measures.
Retrospective/post-facto analysis allows insurers to analyze their historical claims data for patterns that indicate potential fraud before an actual instance occurs. A retrospective approach involves reviewing past claims information from one year back through multiple years to catch any suspicious activity up front and take action on those instances proactively rather than reactively after something has gone wrong.
Retrospective analysis can also involve using different software tools designed specifically for this purpose - but without exhaustive manual intervention from human resources staff members who may lack expertise in analyzing large amounts of complex data sets generated by complex systems such as CRMs (customer relationship management).
Investigators can use monitoring tools at any point during an investigation phase—before someone makes an initial claim and even after the insurer's company has paid out the claim—to collect data from multiple sources and analyze it so that the Third Party Administrators (TPA's) or whoever is responsible for managing claims doesn't miss anything important about potential issues related to the suspect policyholder's claim history (or lack thereof).
The Future of Financial Fraud Detection
The future of financial fraud detection is promising and complex. However, criminals are becoming more sophisticated, the technology they use is improving, and the global economy is growing increasingly complex.
Fraudsters are targeting a more comprehensive range of financial products and services and are becoming more creative in their methods. Insurance organizations need to have a comprehensive approach to fraud monitoring, detection, and prevention. This way, they can stay ahead of fraudsters and protect their customers.
Several vital elements need to be in place for effective fraud detection:
- An understanding of the criminal ecosystem
- A robust analytics platform, investigative capabilities
- A team of dedicated experts
Even with all these, insurance organizations should also work with law enforcement and other industry stakeholders to coordinate efforts and share intelligence.
Lifestyle Analytics – The New Frontier in Fraud Monitoring
Lifestyle data is a broad term for information about an individual's daily activities and preferences. This includes things like what they eat or drink, where they go on holiday, and whether they wear a particular type of clothing or jewelry at any given time.
Lifestyle data can be used in fraud monitoring to identify and prevent fraudulent activity.
Lifestyle data, when combined with other information, can offer insights into the life of an individual that could help identify fraudulent activity. How? By understanding what makes people tick — their preferences for certain foods or brands; how much money they make each year; where they spend their time (on vacation or at work); their marital status; whether they're parents of children under 18 years old; etc.
With this information, insurers can, with the help of AI, advanced analytics, and predictive modeling, get data-informed insights into their clients' varying risk profiles.
Lifestyle Data Sources
The sources of fraud data are constantly changing. For example, social media may be a great source of lifestyle data in the near future, but it isn't right now. Online shopping is still an important source of information and will likely remain so for some time.
However, online search engines are constantly being improved by companies like Google and Bing, increasing the possibility of access to more consumer preferences than ever before. Social media is another excellent source of raw and credible insights on consumer lifestyles, and social media fraud monitoring is now a thing.
So, which is the most accurate and reliable source of fraud data? The answer depends on the purpose for which it's being used. But one thing is certain: there is no single source that provides all the answers.
The Issue of Legality and Ethics – What's the Redline?
As service providers, it's the insurer's duty to protect their clients' interests; therefore, it's understandable when such concerns are raised. In the modern world, data privacy and security are of paramount importance. However, there are many questions about the ethics of using such technology.
There are numerous government regulations concerned with protecting consumers' interests. However, for the most part, they only cover what's legal or not. What's accepted as ethical may be illegal; similarly, an unethical matter may be perfectly legal.
Given how broad ethics is as a topic, it would be impractical to delve into the issue entirely. However, these five pillars can help determine what's ethical according to universally accepted standards:
Five Pillars to Determine Ethical Standards
- Veracity: The principle that humans have the power to make choices for themselves is fundamental to ethical thinking. Insurers should always respect individuals' autonomy by allowing them to make informed choices about their own lives and actions. In line with these, they should maintain a transparent disclosure policy with their clients regarding all data collected for analysis, how it is used, and with whom they share the data.
- Beneficence: While serving their clients, insurers should help them without harming or taking away their rights.
- Nonmaleficence: In their business, insurers must take appropriate measures to protect their clients. In the case of user data, it may mean having strong security safeguards to protect the data.
- Fairness: Insurers should act in a manner that benefits society as a whole; and, in their service, work towards improving the social conditions of their clients and community.
- Confidentiality: According to this principle, everyone deserves privacy, and insurers must ensure they protect their client's privacy at all costs. In the context of using lifestyle data in risk assessment, insurers can employ data anonymization to achieve this.
When assessing whether their fraud monitoring techniques using lifestyle data are ethical, insurers should consider the following:
What are their organizations doing with the information they collect? Are they keeping it for themselves or sharing some with other companies or organizations? If so, how do insurers ensure that they (3rd party companies) comply with their privacy policies when handling personal data?
Do Insurers Have a Responsibility to Collect Lifestyle Data on Their Customers?
Surprising as it may seem, insurers are responsible for collecting lifestyle data on their customers. It's not just about keeping premiums low and ensuring customers are happy but also about them being good corporate citizens.
With the fierce competition in the industry nowadays, insurers that somehow provide more value to their clients are the most likely to thrive. The extra value shows up in conveniently and accurately priced premiums, personalized newsletters, or discounts to help clients navigate life's challenges. The possibilities are endless!
The only way insurers can do this is by accessing their clients' lifestyle information. With a better understanding of how policyholders use their products, they can assess fraud risk better and create policies with acute cognizance of the risk involved. Eventually, this will save everyone's time, resources, and money, with the added benefit of convenience.
How Monitoring Tools Feed Data for Further Review By Private Investigators
As a business that's set up to operate on a large scale, the massive amount of data is unavoidable; consequently, detecting insurance fraud is difficult.
Insurance companies often have limited resources and must balance their efforts between investigating suspicious claims and handling legitimate ones.
Monitoring tools can help investigators identify data that will lead them to evidence of fraud. This can include unusual patterns in the claims process or patterns that suggest fraudulent activity.
Special investigation units (SIUs) in particular can benefit immensely from monitoring tools. One of the main arguments downplaying the importance of SIUs is the concern that some of the fraud cases they are responsible for barely hold water and in some cases, the convictions may be overturned.
From the management's perspective, this is bad for business due to money lost in damages, other lawsuit costs on top of a damaged reputation. With monitoring tools, however, SIUs can fortify their cases sufficiently to guarantee successful conviction of fraudulent cases.
Some of these tools may take on an active or passive role.
Internet of things (IoT) enabled devices are particularly gaining more prominence as effective monitoring tools to curb insurance fraud. The best thing about them is that they can take on both active and passive roles without becoming too intrusive.
A crash sensor onboard a vehicle or a dashboard camera, for instance, may not seem as too invasive to policyholders than, say, if insurers mandated full-time surveillance on them. Similar devices like Fitbit or health monitoring tools on smartphone devices are just as effective in providing useful information to insurers without breaching what most consumers consider the "red line" regarding what's acceptable and not infringing on their privacy.
As it shall be expounded later, an opportunity is a key variable that enables fraud. Using monitoring tools that submit reports to the insurer immediately after an incident occurs, insurers can take away or minimize the opportunity element, effectively nipping the problem in the bud.
It's also important to understand that monitoring tools can effectively take on post-event audit roles.
Even with the most advanced tools and talent, there's a big chance that a significant amount of fraud goes through the system undetected. Faced with this possibility, more insurers actively involve monitoring tools even after processing claims.
What to Consider When Choosing a Fraud Monitoring Tool
Choosing the right fraud monitoring tool can be easy for some and difficult for others. However, at the core, insurers must determine their organizations' needs and seek solutions from various solution providers.
These are some of the considerations to factor in the ultimate decision:
A monitoring tool is only good if it can consistently and reliably filter fraudulent claims and transactions from genuine ones. The more accurate it is, the more time and resources are freed for insurers to focus on cases that matter and provide exceptional services to their clients.
This refers to the tool's ability to handle a significant increase in traffic or data. A tool that is not scalable could become overwhelmed and become difficult to use, potentially prompting more costs to refine it further. Additionally, a tool that is not scalable could also present a security risk if not properly designed and implemented.
As an ever-present factor in any investment, insurers should be able to assess whether the monitoring tool is worth what it's touted to achieve and actually deliver. A cost-benefit analysis may be sufficient, but a closer look at the solution's pricing strategy can help prevent insurers from falling for seemingly enticing but costly products early enough.
Proven Reliability/ Track Record
Most insurers know of well-packaged offers that deliver nothing in the end. To ensure they get value for their money, it's important to consider a monitoring tool's or the solution provider's credibility in the market. This is a sure indicator of the efficacy of their products. Common pointers on reliability include testimonials, reviews, or recommendations from previous clients who can comment about the product based on experience.
Other essential factors to consider include: the tool's ease of use, after-sales service, and implementation of the solution, including the possible installation/ training costs
Insurance companies need to stay on top of fraud and risk management. Fraud has become a significant issue that could have a lasting impact on the bottom line.
By using the best insurance fraud monitoring solutions, insurers can stay ahead of the game and protect customers from fraud.
Insurance fraud solutions can save insurers massive amounts of money lost to fraud that they can redirect to boost their corporate strategy, whether it's increasing shareholder value or creating better products and services for their clients.
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