Every business wants conversion as much as possible. However, there’s a problem with conversion: fraud and user experience. Businesses may have to choose which one between fraud vs user experience that they need the most while sacrificing the other one.
The truth is, businesses can get stronger security against fraudsters but potentially lose the satisfying user experience. On the other hand, businesses can get a smooth authentication to ensure conversion but may be weaker to advanced frauds.
So, is it not possible to have better security without hurting conversions? This article will explain how businesses approach this dilemma of balancing fraud prevention and UX in their authentication systems.
Why Fraud vs User Experience Is a Real Business Challenge
Fraud prevention and user experience are important aspects of the security systems. Over time, businesses have spent their resources on optimizing them, trying to protect sensitive data and keep customers enjoying transacting with them.
However, the problem lies with how to balance them, which is often considered a challenge. Here are several reasons why these two components of authentication systems give businesses a real challenge:
- Difficulty of choosing between fraud prevention and UX. Like the explanation above, if businesses favor security over user experience, businesses lose customers. If businesses favor user experience over security, businesses may not be capable enough to withstand sophisticated fraud attacks.
- Risks from not taking action. Even if businesses leave their current authentication systems as is, businesses will either lose to ever-evolving frauds or lose customer trust from being unable to protect their data.
- Pressures from regulatory entities. Businesses have to keep up with constantly renewed regulation to combat ever-evolving frauds by implementing stronger security systems. However, it could compromise user experience.
How to Balance Fraud vs User Experience Without Losing Millions
Like the question said, how can businesses balance fraud prevention and user experience without losing customers due to overcomplicated verification? There are three known ways:
Risk-Based Authentication
Risk-based authentication (RBA) is a dynamic system that verifies users based on perceived risk. It adjusts login requirements by analyzing several factors (device, behavior, etc.) to determine the risk score. This is how RBA balances fraud and UX:
- If the risk score is low, the user is at low risk. RBA then gives minimal login requirements, optimizing user experience.
- If the risk score is high, the user may be potentially dangerous. RBA then checks users with additional authentication processes, ensuring they are legit and not a fraudster.
Adapted Security Based on User Behavior
The way users behave can also help businesses to check whether they are real customers or fraudsters in disguise. By utilizing behavioral analysis, businesses aren’t just checking their credibility from the login process but also their whole activities.
In short, if they show unusual activity, the security system will require step-up verification. This, in turn, ensures everyone else’s user experience while keeping the services highly secured.
Balanced Solutions Based on Industries
Another angle to see the balance solutions is to implement authentication systems based on which industry the businesses settle with. How can this theory balance fraud prevention with user experience? Let’s look at a few examples:
- For industries known for being the most targeted by fraud, like the fintech industry, businesses may focus on strict fraud prevention (KYC, biometrics) with user-friendly interfaces.
- For industries with less targeted but still maintained security, like e-commerce, businesses may try RBA that determines login requirements based on the user’s risk score, keeping the balance between safety and UX.
- For industries that deliver speed above all else, like social media platforms and streaming services, businesses may use passwordless logins with risk assessment, keeping verification fast but safe.
Designing Fraud Prevention That Protects User Experience
With the fact that security without hurting conversions is possible, how do businesses design conversion-friendly fraud detection?
Using Device Fingerprint and Behavioral Analysis
First, let’s take a look at systems in the verification process that don’t interrupt user experience. Both device fingerprint and behavioral analysis work in the background, which is ideal for keeping user experience high.
These systems analyze user behavior and their device for unusual patterns. For example, device fingerprints check the user’s location and device for possible app tampering or usage of VPNs, while behavioral analysis checks their typing patterns and gestures.
Reducing Unnecessary OTP and MFA Login Requirements
Businesses can increase the user experience by utilizing passwordless authentication, reducing friction in security flows. Users can log in with just one tap, while businesses check their credibility by risk profiling their phone numbers from carrier networks.
Minimizing False Positives in Fraud Detection
False positives often happen in fraud detection with machine learning algorithms. This issue can frustrate legit users who are trying to access their account. To fix this:
- Implement a multi-layered fraud detection system. From KYC to AI authentication, these features help contribute to the security system with less false positives. The more, the better.
- Keep the human touch to check potentially flagged frauds. They can validate transactions flagged as potentially fraudulent by security systems, minimizing potential checking errors.
Measuring the Fraud vs User Experience Impact on Conversions
To design a conversion-friendly fraud detection, businesses must measure the impact of user experience in fraud prevention on conversions as well as the impact of complex fraud prevention systems on UX.
Tracking Conversion Drop-Offs
Find out how many users drop off from services over excessive fraud prevention checks. Businesses can utilize analytic tools, such as Smartlook, to track each conversions.
The drop-off rate then can be calculated by comparing how many total users who failed the verification with the total verification attempts. Investigate the cause of the drop-off rate to find the most optimal solutions.
Comparing Fraud Loss vs User Abandonment
How many losses do businesses have from fraudulent attacks? And how many losses do businesses have from user abandonment? Compare these two to find the solution to the fraud vs user experience problem.
Continuous Testing and Optimization
Once businesses identify the problem in the verification systems, it’s time to perform more testing and optimization. By doing this, businesses can gain immediate feedback on which areas between fraud prevention and user experience they can optimize.
Secure Your Platform Without Friction Using Keypaz
Keypaz helps businesses to strike a balance between fraud prevention and UX without sacrificing one thing for another. As an AI-powered fraud detection and authentication platform, here’s what Keypaz can do:
- Device intelligence checks behavioral data from user devices to detect suspicious activity in the background, keeping user experience high.
- Real-time rule orchestration allows businesses to tailor the fraud detection to suit the industry needs, adapting with user experience.
- Small signal detection detects multiple anomalies and unusual patterns with AI and data analytics. Keypaz operates all of this transparently.
With Keypaz, businesses get a robust and scalable security infrastructure while improving user experience. A perfect balance between fraud vs user experience for all businesses. Start your free trial now.