With an increase in mobile payments and digital transactions, hackers and cybercriminals are targeting mobile apps to create vulnerabilities in them. Therefore, implementing fraud detection is extremely important these days for android app developers.
Mobile app fraud occurs in the form of account takeover fraud, in-app purchase fraud, and install frauds. Thus, there comes the need for AI fraud detection strategies and tools to protect app users from such malicious activities.
Recently, frauds have increased significantly in the mobile app development domain.
This blog is about how AI-driven fraud detection works in Android devices, along with a few types of frauds that are most popular.
A Sneak peek of Fraud in android apps
Mobile app fraud has become a rising concern because of the increase in digital transactions.
Hackers are trying to steal user information by creating fake apps, manipulating app metrics, and deceiving users by showing them that your app is a legitimate one.
Once the application gets published on the App Store or Play Store, certain fraudsters adopt a reverse engineering approach by repackaging it, republishing it on the Play Store, and tricking users into downloading the application.
Downloading such apps results in financial losses and brings reputational damage to Android app developers and organizations.
How does AI-driven fraud detection work in Android apps?
AI works as a BLESSING for mobile app fraud detection as it uses powerful algorithms to detect anomalies and patterns.
It’s trained on leaps and bounds of data, it can detect when such fraudulent threats occur, or suspicious transactions are probable.
Hackers or unauthorized parties try to engage in fraudulent activity by taking data from diverse sources such as user behavior data, device data, IP addresses, external data sources, etc.
It’ll alert users and businesses and flag that application.
What are the benefits of AI-driven fraud detection in mobile apps?
Let’s discuss a few benefits of inteandgrating AI to detect mobile app frauds –
1. Real-time data analysis
The use of AI in fraud detection is a game changer in mobile app development as it can detect fraudulent activities on the go.
As the AI is trained on vast data sets, it can detect which transactions are suspicious before it becomes a serious concern for users and businesses.
Unlike traditional fraud detection systems, AI-powered systems don’t work on predefined rules, rather it does the real-time analysis of data.
These systems are dynamic, meaning they can adapt to learning patterns to detect potential fraud based on login location, device changes, or any abnormal activity. If a potential threat is likely, the system will send real-time alerts to users and businesses.
2. Increased accurate outcomes
AI-driven fraud detection systems use advanced ML algorithms to assess the likelihood of fraud that would otherwise be left unnoticed through manual review.
As AI continuously learns from data, it can learn to distinguish between legitimate and fraudulent transactions based on actions such as unusual behavior within the app or slightly altered IP addresses.
3. Scalability
As the business grows, the number of users and volume of transactions also increases.
While traditional fraud detection systems focus on employing large teams to oversee rising concerns such as growing payment fraud, identity theft, or app installation fraud.
With AI fraud detection systems, businesses can scale their requirements, deal with complex datasets, and reduce such financial losses without incurring additional costs.
4. Creates personalized user profiles
AI-based fraud detection systems analyze user behavior, preferences, transaction history, location, etc. If the app sees that the user makes a specific transaction from one country, while this time user makes it from a different country.
Then the system flags the user as it can tell the difference between real and fake transactions.
What types of fraud can AI fraud detection systems detect?
Let’s discuss some of the common types of fraud that AI fraud detection systems can assess-
1. Account takeover fraud
Such frauds occur when the fraudster steals the user’s account information and tries to make unauthorized transactions.
AI systems can detect such anomalies based on unusual user behavior, login times, or login from different locations.
Thus, AI can adapt to learn and detect unusual patterns and find out whether a legitimate person made the transaction or not.
2. In-app purchase fraud
In-app purchase fraud occurs when hackers use fake payment methods to purchase digital goods/services.
The AI-based fraud detection system can detect such abnormal behavior when users make purchases repeatedly or do refunds within the app.
3. Install Fraud
Research study states that Android users suffer with 6x higher fraud rates which is significantly higher than iOS devices.
The reason might be Apple follows strict guidelines for app developers who want to publish their apps on the Apple store.
App install fraud means when the fraudsters create a malicious, fake app by pretending to be users and advertisers that it generates a huge number of app downloads and installs.
A study from Statista states that mobile app fraud makes up most of the fraud on Android devices.
During 2022, the number of Android app installs frauds increased by 46% and has significantly risen by 61% in 2023.
The latest innovation that Google introduced for fraud apps
Recently, Google brought AI capabilities for apps introduced on the Play Store to protect users against malware detection, and threat protection along with a few security tools.
As per Google, around 3 billion users are protected from malware every day. The AI-powered live threat detection feature uses machine learning algorithms to protect users by disabling the app if it permits malicious attempts.
In the future, it’s expected that Google will provide more tools to developers to protect users from such attacks. It’ll alert users when any app attempts suspicious behavior or plays with the sensitive data of users.
Wrapping up
In this digital landscape, mobile app frauds have been increasing at a rapid pace. AI stands at the front in spotting errors, analyzing leaps and bounds of data, analyzing patterns, and safeguarding users from malicious attacks.
As you know, digital applications take supremacy in the current world, and that’s why mobile app developers and app development companies need to implement AI-driven fraud detection strategies for apps.
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