Insurance Fraud Detection: How Software & AI Help Identify Fraud

Insurance fraud detection has been recently prioritized by companies of different sizes. Insurance fraud is becoming a huge issue for both brokers and policyholders. The industry loses billions of dollars annually because of suspicious activities and fraudulent claims. Fraudsters steal around $80 billion per year.

Traditional cybersecurity measures implemented by the majority of insurance providers are not enough. The inability to understand different sources, fraud types and the way they are committed makes insurance fraud prevention even more challenging than ever before.
So, this time we are going to discuss some of the most common insurance fraud detection means, and types, and the impact they may have on both brokers and policyholders.

The Importance of Insurance Fraud Detection and Prevention

Why is insurance fraud protection so important? Both companies and policyholders are at risk of being created. On the one hand, the industry evolves. It goes online offering faster and simpler ways to deliver insurance. On the other hand, fraudsters have plenty of extra ways to take advantage of online products involving insurance.

Criminals develop fraudulent approaches for fake claims process. This makes it hard for fraud bureaus to perform proper fraud pattern recognition. Most companies use brick-and-mortar insurance fraud management strategies that cannot guarantee efficient predictive modeling and accurate decision-making.

To benefit from effective insurance fraud detection, we need to clarify what we are actually fighting with. So, here are some of the most common fraudulent techniques:

• Ghost Brokers Fraud. The idea is pretty simple. A fraudster pretends to be a broker with the aim of gaining money from a potential policyholder. Generally, this type of scam is spread across social media to target users’ vulnerable data and perform insurance claims fraud.
• Multi-Accounting and Fake Registrations. Criminals use several devices to sign in. Generally, they register using stolen identities. Then, they damage one of the registered devices on purpose to make a fake claim. When the insurance money is pocketed, criminals wipe the device off.
• Fraudulent claims. Scammers make false or exaggerated claims. While every company has its own process of identity verification and claim processing. Proper insurance fraud detection can be a challenge. A proper risk assessment strategy is needed. Traditional investigation techniques no longer make sense in the digital era.
• Intentional Damage Claim. Some fraudsters intentionally lose or damage their items. We have seen plenty of those examples in movies. While we are still living in the insurance-as-a-service world, this particular type of fraud will always be a huge problem for brokers.
• Car Insurance Fronting. It is a more specific type of scam also known as fronting. It happens when more mature drivers claim a more favorable quote even if someone else was driving a damaged vehicle.

Whatever the type of insurance fraud, brokers need an effective tool for policy evaluation and anomaly detection to enrich their digital insurance fraud detection techniques. Otherwise, the consequences of insurance fraud cases can be dreadful.

JuicyScore was designed to prevent not only the most common types of insurance fraud but also minimize specific online cyber threats that are hard to detect using traditional safety means and enhance the process of fraud investigations.

Unauthorized subagent work detection

The system is capable of identifying many agents using a single account, analyzing applications based on device types, and preventing personal accounts from being created on unsafe devices.

###Agent’s fraud detection

Let’s say, a fraudster is trying to pick the combination of client’s personal data, which diminish the cost of the policy before selling it to a customer. JuicyScore helps to prevent these types of scam as well.

Offline-2-Online insurers check implementation

The O2O solution is applicable to all the agent’s flow as well as to all the offline branches flow.

Detection of high-risk applications in the flow

The software detects virtual machines, randomizers, non- local DNS servers, device and internet connection manipulation attempts, indicators, correlated to the aggressive driving style.

Prevention of illegal purchase of several policies

Our solution helps to prevent multiple fraud claims or policy purchases handled via the same device. What’s more, the system automatically detects accounts related to the fraudulent device.

Detection and blocking of fraud rings

An integrated feature for scammers’ detection and blocking. Companies start losing money.

Detection of insurance payments based on false statements

The ultimate anti-fraud toolkit detects circumstances associated with high motivation to receive an insurance payment, based on a false reason (frequency of attempts made to obtain loans in a short period of time).

The Impact of Insurance Fraud

All parties involved pay the price for insurance fraud. Both brokers and policyholders are put under pressure by online scammers. On the one hand, fraudulent claims can cost brokers a fortune. On the other hand, extensive scammers’ activities can lead to the total destruction of the insurance system.

Financial Losses for Insurance Companies

According to recent fraud analytics, the insurance industry loses $408 billion per year because of scammers. Insurance firms lose money as a result of fraudulent claims, and they must make up the difference by raising rates and premiums.

Besides, brokers need to spend thousands to recover after fraud. Sometimes, companies have to pay fines and extra fees for not meeting safety standards or putting their clients’ policies at risk.

Economic Impact on Policyholders

As for policyholders, they can suffer from the following issues:

1. Increased Premiums. Every time insurance fraud happens, brokers increase premium costs for all customers. In the bottom line, even fair policyholders need to pay more to cover their insurance policy costs.
2. Limited Coverage. Companies may establish stricter exclusions or limitations after being digitally abused. It will impact even honest clients who did nothing wrong.
3. Delayed Claims Processing. Digital forensics and fraud investigation techniques can be time-consuming. Besides, they call for extra resources from the company. As a result, clients can suffer from delays with policy processing.

Undermining Trust in the Insurance Industry

With every little fraud, the trust between a broker and a customer erodes. The situation becomes even more serious in case of wrong addressing or inability to guarantee prompt insurance fraud detection. Clients start losing confidence and would rather leave a broker for a new one with even higher rates.

This is why companies need comprehensive insurance fraud prevention software. We offer an all-in-one technological solution for anomaly detection, behavioral analysis, and device-assisted monitoring designed with insurance companies in mind.

Juicyscore’s Solution for Insurance Fraud Detection

JuicyScore was designed to assist online companies in identifying high-risk applications, stopping multiple accounts, and providing alternative data for data scoring.

Our insurance fraud detection software comes as the world's most stable Device ID capable of minimizing different error types at a time.
We deliver an advanced technological stack that includes a wide range of randomization, anonymization, and virtualization detection tools.

Finally, we create methodologies for data analysis and validation. It helps to identify a device under external control and minimize potential fraud risks.

Leveraging AI for Fraud Recognition

JuicyScore makes use of cutting-edge AI and machine learning technology. It is a comprehensive toolset for preventing fraud created to help digital platforms combat scammers. It guarantees state-of-the-art security measures in a number of insurance verticals for brokers of any size.

The toolkit handles the following:

• AI-Driven Algorithms. They can recognize different types of insurance fraud. The software uses hundreds of different device authentication parameters to create an accurate end-user profile based on a variety of tech data and behavioral elements.
• Machine Learning-Based Techniques. They are implemented to lower the fraud risk by performing automated threat detection in real-time. The system analyzes hundreds of settings, characteristics, and indicators supported by the device.

Data Enrichment for Deeper Fraud Insights

We construct an adaptive assessment model using the intricate JuicyScore data vector. It helps brokers generate and process enough information to assess the reliability of policyholders’ accounts. In the end, companies can use data for in-depth data analysis and appropriate decision-making.

Key Features

The insurance fraud detection software acts as a digital consultant. It is a component of a more comprehensive fraud prevention strategy that also incorporates algorithms to spot device manipulation and randomization.

The solution generates values based on various parameters and integrated indexes. By applying authentication procedures, the technology automatically conducts thorough tracking. Fraudulent activities are quickly identified, including the use of multiple accounts, data randomization, virtualization of devices, and credentials theft.

Device Fingerprinting

The system assesses and evaluates a range of primary and secondary hazards related to online insurance fraud. For the best device fingerprinting, JuicyScore can keep an eye on important device-assisted parameters.

Our data vector specifies the kind of carrier (tablet, desktop, laptop, or mobile), screen size, display quality, RAM, and other crucial specifications that enable fingerprinting to be performed correctly.

Claims Behavior Modeling

As a result, the system alerts brokers to suspicious activities or potentially fraudulent claims. Teams can uncover device cloning or randomization, remote access, different routing tactics, and more with the use of our technologies.

How It Works

The system employs filters to classify high-risk flows into niche-specific groupings based on device attributes (OS, browser version, Internet connection quality, behavioral variables, etc.).

Using JuicyScore, companies can evaluate each user trying to complete a certain action. With time, organizations create and modify their custom risk assessment models that are highly informative. In the end, businesses may develop a low-cost anti-fraud strategy that lowers overhead, increases loyalty, and boost trust.

Authentication

The system automatically identifies potentially risky lead sources. It may also handle the process of user blockage in case of high risks detected.

JuicyScore can identify numerous insurance applications launched from the same device or person thanks to a wide stack of device authentication technologies, which also make it possible to block scammers.

Flow Segmentation

As a part of our integrated flow segmentation model, the solution identifies high-risk applications. It helps companies to establish a portfolio featuring fewer high-risk clients. Companies will receive an accurate profile of device and user-assisted features in addition to technological and behavioral signals that enable informed decisions in reference to claim approval or rejection.

Flow Quality Assessment

JuicyScore enhances the protection against insurance fraud by considering multiple factors each time a client makes a claim. An enriched understanding of technological and behavioral characteristics can be obtained from the context of an access request. The system instantly sends “red flags” if potentially risky anomalies are detected.

Efficiency

For maximum efficiency, the system uses constantly updated indexes that refer to specific types of data. JuicyScore processes different factors by combining a variety of aggregated variables.

These include dwell/flight times, average typing or content reading rates, devices that are duplicated or randomly selected, devices that are utilized on the same device for an extended period of time, and other significant behavioral data.

In the end, companies get a comprehensive toolkit for the ultimate insurance fraud detection and prevention.

Get Started with JuicyScore Today

Use JuicyScore to create a successful anti-fraud plan for your online insurance company. To get started, complete the following simple steps:

1. Install the mobile SDK or JavaScrip web app on your digital device.
2. Configure anti-fraud tools according to your requirements.
3. Start collecting and analyzing required data to identify and stop online fraud.

Provided by JuicyScore, the technology guarantees revenue loss prevention for companies and trust between brokers and clients. Contact us to schedule a demo.

FAQs

How quickly can I see the effect of implementing your fraud detection software?

To start getting the first results, you only need to install our solution on your website or mobile app. The system will start gathering the necessary data right at once. It takes seconds for our data vector to provide a specific value that refers to a specific risk level.

How does JuicyScore keep up with evolving insurance fraud schemes?

JuicyScore comes with a dynamic data vector. It means all indexes are constantly updated and renewed. We use our partners’ experience to enhance the solution with up-to-date techniques that deliver real value to our customers.

Can your software learn from an insurer’s historical claim patterns?

Our system uses AI and ML-driven technologies to learn. Some of our clients provide results and stats that we use to keep our solution up-to-date.

What support and training options come with your fraud detection solution?

JuicyScore is super easy to use and integrate. No special skills or expertise are needed. Our team helps companies at every stage of data vector integration. We also provide ongoing assistance in installing, fine-tuning, and running our anti-fraud toolkit.