In the past, theft meant someone breaking into your house or stealing your wallet. But in today’s digital world, thieves don’t break locks, they break into accounts, systems, and transactions online and this is termed as online fraud.
The problem with online fraud is that it keeps changing. As security gets better, cybercriminals find smarter ways to break through it. They create fake accounts, steal identities, or make fraudulent payments. These activities are often hard to spot until it’s too late.
Fraud detection APIs are powerful tools that help businesses catch and stop fraud before it happens.
In this blog, we’ll explore what fraud detection APIs are, how they work, and why they’re crucial for businesses in safeguarding their operations. Let’s explore it further:
What are fraud detection APIs?
Fraud detection APIs are essential tools for businesses that can help them stop and prevent fraud from happening. These APIs analyze data, like login details, payment information, or user activity, to spot anything unusual or suspicious. As soon as it spots any unusual activity it flags them and notifies the users in real time.
Fraud detection platforms are widely used across various industries to safeguard against financial and security threats that range from e-commerce and retail to social media platforms to the banking and financial sectors.
The need is real because fraudulent activities have increased exponentially in recent years. Let us check some statistics below:
- A 2021 report by Juniper Research says online payment fraud could cost the world $206 billion by 2025.
- A 2022 report by Juniper predicts businesses may lose over $343 billion to online payment fraud between 2023 and 2027.
- Online payment fraud is expected to rise sharply, from $130 billion in 2020 to $206 billion by 2025.
The above statistics depict the pressing need for businesses to consider implementing fraud detection solutions.
How Fraud Detection APIs Work
Fraud detection APIs involve 4 major steps that are:
- Data Collection
The API collects important information during key activities, such as:
- When a new user signs up (onboarding), their email and IP address are recorded.
- During login, the device, location, and time of access are noted.
- While making a purchase, transaction details like the card used and shipping address are captured.
- Data Processing
This data is sent to the fraud detection system for analysis. The system uses preset rules or machine learning technology to identify anything unusual or suspicious.
Example: A user logging in from two different countries within minutes might be flagged as suspicious.
- Risk Scoring
The system assigns a risk score to each action based on the analysis.
Example: A score of 90 (out of 100) for a login attempt might indicate a high chance of fraud because it came from an untrusted device.
- Action Triggering
Based on the risk score, the API decides the next step. Some of the examples are listed below:
- A low-risk transaction might be approved automatically.
- A high-risk login might prompt a two-factor authentication (2FA) request such as asking the user to enter an OTP sent on their mobile phone or email.
- A suspicious activity could be flagged for manual review by a security team.
This process ensures user safety while minimizing disruptions for genuine customers.
Examples of Risky User Behaviors
1. Different Billing and Shipping Addresses
Fraud detection systems flag transactions where the billing and shipping addresses don’t match, as this can indicate stolen payment details.
Example: A purchase billed to New York but shipped to an unknown address in California.
2. Disposable Email Usage
Using temporary email addresses raises red flags, as fraudsters often use them to avoid detection.
Example: A user signs up with “[email protected]” to bypass verification.
3. Unusual Login Locations
Logins from unexpected or far-apart locations within a short timeframe may signal account compromise.
Example: A user logs in from London and Tokyo within an hour.
4. Multiple Registrations Using the Same Device
Repeated signups from one device can indicate fraudulent activity, like creating fake accounts.
Example: A single phone is used to register 10 different accounts on an e-commerce site.
5. Bruteforce Attacks
Hackers repeatedly guess login credentials to gain unauthorized access to accounts.
Example: An account receives hundreds of failed login attempts within minutes.
Detection Methods
All fraud detection APIs have detection methods that help with detecting different types of fraudulent activities. Some of them are listed below:
- IP Address Tracking: Fraud detection APIs check the IP addresses of users to spot unusual activity. If a user’s IP behaves differently than expected, it might indicate fraud.
- Device Fingerprinting: These systems look at the unique details of the device used, like the operating system, browser, and hardware. If a new or very different device is detected, it could be flagged as suspicious.
- Behavioral Analysis: Machine learning tracks regular user habits, like login times, locations, and actions. If a user behaves differently than usual, it might signal a fraud attempt.
- Geo-Velocity Tracking: APIs measure how quickly a user’s location changes. If someone appears to move between far-off places too quickly, it may suggest fraudulent activity.
- Scrapper/Crawler: Fraud detection APIs identify and block bots by tracking unusual patterns like rapid requests or fake user agents. This helps prevent data scraping and unauthorized activities.
- Email: Fraud prevention APIs are also equipped with detection methods for emails that look suspicious or have some gibberish data for the sake of creating an email ID.
Benefits of Using Fraud Detection APIs
- Automation
Fraud detection APIs handle the entire process automatically, running 24/7 without needing extra staff or systems. They send alerts and notifications whenever suspicious activity is detected.
- Efficiency Over Manual Methods
Fraud prevention APIs work faster and more accurately than manual processes, offering real-time detection and instant responses to potential threats.
- Scalability
Fraud detection APIs and tools can easily handle growing data and user volumes, adapting to the size of your business without losing effectiveness.
- Customization Options
Businesses can tailor fraud detection APIs to their specific needs by adjusting settings like alert triggers and thresholds.
- Cost-Effectiveness
Flexible pricing models, such as pay-per-use, let businesses manage fraud detection affordably while scaling their operations as needed.
Real-World Applications of Fraud Detection APIs
- Transaction Screening
Fraud detection APIs check every transaction in real-time to identify and block suspicious ones. This prevents issues like unauthorized payments. For example, A fraud detection API on an e-commerce site can spot unusual activity, like a high number of expensive orders that don’t match the account’s usual behavior. It can also block payments from flagged IP addresses to stop stolen credit cards from being used.
- User Authentication and Verification
Fraud prevention APIs ensure users are who they claim to be by using methods like OTPs or biometric checks. This stops unauthorized access. For example: An e-commerce app uses an API to verify a user’s fingerprint when logging in. If an unknown device tries to log in, the API blocks access and sends an alert or in some cases, it will send a challenge to the user where they will need to verify their identity by entering an OTP sent through email or their mobile phone.
- Behavioral Analysis
Fraud detection APIs track user behavior patterns to spot unusual activities that might indicate fraud. This helps detect threats early. For example, a video streaming platform notices a user suddenly streaming from two countries within minutes. The API flags this as suspicious and can either raise an alert or suspend the account temporarily.
Why Choose REST APIs for Fraud Detection
REST APIs are lightweight and compatible with several tech stacks making it easy for businesses to make it a part of their infrastructure. Below are some of the reasons why REST APIs should be your choice:
1. Ease of Integration
REST APIs are cross-platform and use standard HTTP protocols, making it easy to integrate fraud detection systems into various applications (e.g., web apps, mobile apps, and backend systems) without requiring proprietary libraries or tools.
2. Scalability
RESTful architecture is stateless, meaning each request is independent. This simplifies scaling fraud detection systems to handle large volumes of transactions, which is essential in environments like e-commerce or banking.
3. Wide Adoption
REST APIs are widely used and understood, meaning developers can implement fraud detection solutions more quickly without learning a new communication protocol.
4. Real-Time Decision-Making
Fraud prevention APIs often need to assess transactions in real time. REST APIs can provide low-latency responses, enabling businesses to approve, challenge, or reject transactions almost instantaneously.
5. Standardized Data Exchange
REST APIs typically use JSON or XML, which are easy to parse and widely supported. This allows seamless communication between different systems and easy integration with third-party fraud detection services.
REST APIs are better suited for:
- Projects requiring platform-agnostic integration.
- Businesses need scalability, flexibility, or cross-platform functionality.
- Environments where advanced features, central control, or robust security are priorities.
Implementing Fraud Detection APIs
There are various fraud prevention APIs in the market that businesses can easily integrate into their system. Here is the step-by-step process to get started with the process of integrating fraud detection APIs:
- Clearly define your objectives. For example, if you’re an e-commerce platform, your goal might be to prevent fraudulent transactions during checkout or identify high-risk users during registration.
- Explore fraud detection providers like Sensfrx, Seon, Sift, FraudLabs Pro, or MaxMind. Compare their features, such as risk scoring, transaction monitoring, device fingerprinting, and machine learning capabilities, and see if they match your goals.
- Study the API documentation to know how the API works. Look for examples of requests and responses, error handling, and sample codes.
- Verify that the API supports the programming languages and frameworks your team uses. Most APIs support common stacks like Python, JavaScript, or PHP.
- Sign up with the provider to get API keys. Use these keys to authenticate your requests securely.
- Adjust risk scores, thresholds, and rules based on your specific fraud detection requirements. This customization ensures the API aligns with your operational context.
Expert Consultation
It might be daunting to find the right fraud prevention API that is affordable and suits your requirements. So, seeking expert consultation will be super helpful. Sensfrx is a fraud detection tool that is easy to integrate and a comprehensive fraud detection tool built for businesses of all sizes. We offer REST APIs as well as readymade SDKs supporting multiple programming languages. Sensfrx also offers a free trial that you can check right here or contact us if you have any queries.
