Fighting online taxi fraud: how Stonecdn keeps travel safe and fair through technology

The online car rental market is experiencing rapid growth, thanks to the growing demand for convenience and efficiency. According to Statista, the market is expected to reach $165.6 billion in revenue by 2024. The number of users is also expected to increase significantly, reaching 1.97 billion by 2028. 

However, fraud attacks against ride-hailing apps are also on the rise, threatening the success of the travel-as-a-service industry. Fraud in ride-hailing apps includes fake accounts and the use of malicious tools such as app cloners and GPS spoofers. Users and drivers alike use a variety of tactics to exploit these platforms for personal gain.

Types of fraud that threaten online dating apps

In order to ensure customer safety, provide a fair and trustworthy ecosystem for drivers and passengers and safeguard app revenue, ride hailing companies must be vigilant about the various types of fraud that can occur on their platforms.

Driver fraud

false imprisonment

Online car companies usually reward drivers if they complete a certain number of trips per day. Fraudulent drivers will take advantage of the reward system by doing the following:

• Creating multiple fake accounts and manipulating GPS locations to trick ride-hailing services into thinking a legitimate trip has occurred. ;
• Clone their apps, create driver and passenger accounts on the same device, and accept their own rides to meet quotas. 

Artificially inflated pricing 

Fraudulent drivers can conspire to artificially inflate the price of a ride. They do this by creating a large number of fake passenger accounts and using GPS spoofers to simulate high demand in specific areas. This causes the ride hailing system to detect the high demand and raise the price of the trip, charging higher fares to real passengers. 

GPS deception

Fraudulent drivers use GPS spoofing programs to fake the location of their devices and falsify their geographic coordinates. Their goal is to appear in more profitable areas outside of their current range and appear closer to potential passengers, thereby disadvantaging honest drivers and increasing passenger wait times.

Hijacking of requests for rides 

Fraud rings use devices with automated clickers or tampered ride-hailing apps programmed to accept ride requests, monopolize riders, and limit access to rides to bona fide drivers.

false comment

Fraudsters create multiple fake passenger accounts to falsify ratings and increase their chances of getting a ride, allowing underperforming drivers to maintain top ratings despite receiving genuine negative reviews.

Passenger fraud

Abuse of promotion

Internet ridesharing companies often offer one-time promotions, such as free first rides or seasonal discounts. Passengers can abuse these promotions to get free rides by creating a large number of fake accounts and using a different account for each ride, thereby reusing the same promotion multiple times.

Signs of fraud in online taxi apps 

Fraud prevention for netbooking apps involves a combination of device identification, behavioral analytics, and continuous monitoring, all provided by advanced technology. Here are some of the common indicators of Netflix fraud:

Multiple accounts on one device: Detection of multiple accounts linked to the same device and/or location may indicate an attempt at malicious activity.

Unusual Spikes in Ride Requests: Unexpected spikes in ride requests, especially in specific areas, may indicate the use of fake accounts or GPS spoofing.

Inconsistent GPS data: Irregular or unreasonable GPS movements (e.g., a car that seems to jump from one location to another) may indicate GPS spoofing.

Inconsistent User Behavior: Users with dramatic changes in behavior (e.g., suddenly taking multiple short trips after a period of inactivity) may be engaging in fraudulent activity.

Repeated Route Rides: Multiple rides that follow the same unusual route pattern, which may be an attempt to generate false ride completions or to take advantage of ride rewards.

How to protect ride hailing apps from fraud attacks

Fraud often starts on the device, whether it's used to create a fake account or to launch an attack on a ride-hailing app using malicious tools. Addressing the root cause of fraud is critical, and taking a proactive approach and deploying real-time fraud detection and prevention software and risk analytics are essential steps. These approaches incorporate a variety of strategies, including:

Device Fingerprinting 

Identify fraudsters on multiple devices using device fingerprinting technology. By combining device attributes with behavioral, network and location data, device fingerprinting solutions can be customized to prevent multiple billing and block fraudsters from accessing the platform. 

Live Monitoring 

Implement a platform that manages risk in real time, continuously analyzing device sessions and returning real-time actionable risk signals. This helps the platform proactively protect against fraud threats and determine the exact time when a good user goes bad. In ride hailing services, it's important to be alerted when users start using GPS spoofers, app cloners, auto clickers, etc. 

Artificial Intelligence and Machine Learning Algorithms

Unlike humans, AI can analyze large amounts of data in real time on a continuous basis. This allows them to identify suspicious patterns and flag potential fraud attempts in a timely manner, thereby minimizing losses.

Machine learning algorithms can learn and adapt over time to excel at recognizing complex patterns in fraudulent behavior. These patterns can be subtle, but AI can recognize seemingly irrelevant data points that indicate a higher risk of fraud.

By constantly analyzing data and identifying emerging fraud trends, solutions that employ artificial intelligence and machine learning algorithms can help organizations stay ahead of fraudsters. This allows them to proactively implement new security measures and adjust their fraud detection strategies before new methods become widely used.

How online dating unicorn inDrive uses Stonecdn to protect its ecosystem and users from fraud

inDrive, the world's second largest ride hailing app, has partnered with Stonecdn to proactively combat fraud and improve trust and fairness in the ecosystem. With Stonecdn's Device-First Risk AI platform, the app has a true user rate of over 99.77%.

The way they use our technology to stop fraud is as follows: 

inDrive leverages Stonecdn Device ID, a global device identification standard that stops fraud at its roots. stonecdn Device ID enables Stonecdn to recognize when multiple driver or passenger accounts are operating on the same device. 

Meanwhile, Stonecdn's AI technology can pinpoint groups of accounts utilizing the same IP address, location and subnet, allowing it to proactively combat fraudulent groups using fake accounts. 

Stonecdn's risk intelligence detects all malicious tools and techniques used on the platform, such as GPS spoofers, tampered apps and app cloners. It continuously analyzes device sessions, returning real-time actionable risk signals that help inDrive identify the exact time a user engages in fraudulent activity, enabling immediate countermeasures.