It would be nice to have a strong indicator to assess whether users are legitimately doing their activities or not. This is one of the reasons why device risk indicators are made and being implemented in businesses.
These days, fraud has been more sophisticated. Fraudsters can easily commit online frauds without being detected. Sadly, it takes a long time for them to be caught after the damage that had been done to the victims.
In order to combat fraud techniques like this, better fraud prevention solutions are needed. One of them involves using the device used by every user as a way to indicate whether a fraud has been attempted.
What Is Device Risk Indicators?
Device risk indicators are metrics or indicators to assess a risk based on the devices. They are meant to identify risks that users have by investigating the devices they use for the services.
Another reason behind these indicators is also to prevent fraud as early as possible, before the damage is done. This makes them a solid digital fraud prevention against emerging threats surrounding online activities.
By using indicators, businesses can generate a device risk score on each user. They then can decide whether to enforce more verifications on the users with higher risk scores, or simply deny users from accessing their services.
Are Device Risk Indicators and Key Risk Indicators Same?
When looking at online searches, there is another term called key risk indicators (KRIs). While it seems similar to device risk indicators, there are some differences between them:
- KRIs are metrics used to identify risks from various areas of the businesses. Meanwhile, device risks only indicate risks from the devices being used by users.
- Risks involved with KRIs include operational, financial, strategy, and compliance-related risks. Meanwhile, device risks specifically revolve around devices, such as computers, tablets, and smartphones.
- KRIs are meant to detect early warnings from events that harm businesses and companies. Meanwhile, device risks are meant to prevent fraud and security-related incidents.
Common Device Risk Indicators
In order to identify security risks and potential frauds, these indicators detect anomalies and bad signs from devices. Here are several types of device risk indicators that can be used:
- Unauthorized access attempts. This system can detect repeated unusual access without having to authenticate.
- Suspicious login behavior. Ranging from multiple failed login attempts to logging in at an unusual time or location.
- Malware detection. Compromised devices with malware could be detected, ensuring access to the account using that device is denied.
- Device compliance. Businesses can enforce users to obey security measures, such as having up-to-date software and deactivating VPNs.
Real-World Applications of Device Risk Indicators
Nowadays, there are many ways to implement online fraud detection like this in digital services. Let’s take a look at several examples of how it’s done:
Gaming: Terminating Video Game Bots
Botting has been notorious for its unfair advantage towards the gameplay. Some players could use bots to repeat specific in-game activities automatically or assist players to win against opponents.
To combat botting, game publishers need to implement indicators that can detect bot programs that exist on the player’s device. This is to ensure fair gameplay for all players, keeping only real humans playing the game.
Ride-hailing: Preventing GPS Spoofing
Ride-hailing services can be manipulated by drivers to gain extra income and meet the required quota. By spoofing the GPS, they can appear to be closer to the ride-hailing users who are currently searching for a ride.
This fraud has been known to be prohibited, but prohibiting the activities wasn’t enough. An indicator is needed to ensure drivers can’t fake GPS, preventing upset passengers who have to wait longer due to GPS spoofing.
e-Wallet: Detecting App Tampering
It is possible for hackers to modify an app, bypassing the security system and gaining unauthorized access. This can be easily seen with e-wallet apps, where hackers could find vulnerabilities within the app’s source code.
Worse, they can also inject malware into the modified version and then trick unsuspecting users into downloading it. They then can easily steal important data from the victim’s device and use it to steal money from the account.
In order to prevent this, companies need to have indicators that can detect if the app has been modified or tampered with. This is to make sure users only download the app from the official sites, updated to the latest version.
Also Read: 5 Key Strategies for Payment Fraud Prevention in Financial Services
Strengthening Fraud Detection with Device Risk Indicators
Now that it’s clear what types of device risk indicators there are and how they can be applied, what are the solutions now? For the best fraud prevention solutions, businesses need to have these key factors on their risk indicators:
Risk-based Decision-making
Businesses need to ensure the system can maximize their efforts on the most dangerous risks. To do this, these indicators need to be able to make a decision based on the risk level.
For instance, risks can be assessed based on several factors, like which one is likely to occur or which one has the most impact on users. This allows businesses to allocate resources more effectively to prevent fraud.
Automatic Fraud Detection
A real-time automatic fraud detection is a great system to identify fraud before it causes a heavy toll. This detector may rely on machine learning to detect potential fraud by:
- Detecting unusual login patterns, including sudden logins using a new device or location.
- Creates a personalized user fingerprint based on device, location, and user behavior.
- Detecting unusual activities like botting, prompting users for additional verification.
Industry-related Adaptation
Like those examples shown above, businesses need good risk indicators that can adapt to the services they have. Whether they have an online shop, live service games, or even mobile banking to transfer balance.
Since each industry provides different activities, these indicators must be able to be customized to suit businesses needs. This is to minimize false positives from risk indicators that don’t match with the services.
Proactive vs. Reactive Security
Lastly, risk indicators should have proactive or reactive risk management. Proactive refers to preventing the risks from occurring, whereas reactive refers to mitigating the risks that already happened or are currently happening.
While proactive seems better, there’s a chance a fraud could still bypass indicators. So in reality, businesses need to do their best at preventing fraud, and also be able to mitigate it from worsening the damage.
In conclusion, device risk indicators can be the best businesses’ online fraud detection and solution if implemented well. Truly a good companion to help businesses secure their services and their customers.