CX Fraud Prevention: Balancing Risk and Customer Experience

What is CX fraud prevention? 

CX fraud prevention refers to the strategies merchants use to protect themselves from fraud and abuse while ensuring that their good customers’ experiences are not diminished in the process. CX fraud prevention is the concept of improving the customer journey while providing security. 

The more accurate and efficient fraud prevention is, the better the customer experience will be. Effective CX fraud protection typically involves advanced machine learning (ML), capable of efficiently weighing more signals than manual review or rules-based fraud prevention. 

Types of CX fraud

Fraudsters’ strategies for targeting ecommerce merchants are varied and often sophisticated. The three CX fraud strategies below are some of the most common: 

Account takeovers

The fraudster gains control of a legitimate account, though social engineering (the victim is tricked into revealing sensitive information), credential phishing (a form of social engineering in which login credentials are retrieved through targeted communication), credential stuffing (automation tools are used to deploy previously breached data to gain access to accounts), or other methods. 

Once the fraudster has control, they’re free to make purchases under the cardholder’s name, defrauding the merchant in the process.

Identity theft

New accounts are created with stolen identities and credentials or existing accounts are compromised with an automated trial-and-error system known as brute force. 

Payment fraud

Legitimate credit card information is typically obtained via an online company data breach or purchased on the dark web or through underground forums. This information is then used to place online orders. 

Why is CX fraud important in ecommerce? 

Abandonment rates thanks to friction are high. (According to Resolve, seven out of 10 customers abandon their carts without placing an order.) Equally, customers are unlikely to be forgiving if their security is breached. Safe to say, consumer standards are high.

Failing to account for CX in fraud prevention — not to mention failing to prevent a security breach — leads to wide-ranging challenges for ecommerce merchants: 

Financial implications of CX fraud

CX fraud is expensive.  A fraudulent order means the loss of a sale and the product. Moreover, the defrauded customer is likely to remember your brand — and avoid it—meaning their lifetime value evaporates. 

With growth in the number of high-profile data breaches, online shoppers are more concerned than ever about their personal information being misused for fraudulent activity. According to research from SOTI, 76% of consumers worry about data security when shopping online. Brands that fail to meet customer security expectations or fall prey to fraud schemes get a bad reputation. 

Customer trust erosion

Rebuilding trust after a customer sees fraudulent orders on their statement or is falsely turned down for fear of fraud is almost impossible. On the other hand, brands that build trust over time increase the lifetime value of their customers. 

CX Fraud Prevention Strategies 

Many merchants use rules-based systems, manual review or a combination of both to prevent fraud. But these are rarely the best solutions for seamless CX. 

Rules-based systems can become overloaded with rules (known as ruleset bloat), leading to processing delays. Often, these rules are inflexible, which can lead to false declines. 

However, machine learning and more advanced security methods protect the consumer and enhance the customer journey. 

Learn more about rules-based vs. machine learning in fraud prevention.

1. Implementing advanced authentication methods 

KBA (knowledge-based authentication, such as entering your mother’s maiden name to verify your account) is often easily overridden by fraudsters. Instead, replace it with intelligent, multip-factor authentication. But carefully consider whether and in what circumstances enhanced authentication is required. Any extra verification adds friction to the shopping experience and diminishes customer experience.

• Multi-factor authentication: Requires double verification after the customer has logged into their account, typically using a third-party app or SMS
• Biometric verification: Requires physical indicators such as device fingerprints or face recognition to verify identity.

2. Levearging AI and machine learning

AI and machine learning protect against CX fraud in sophisticated ways that can’t be replicated by rules-based or manual review. 

• Real-time monitoring: Fraudsters’ techniques constantly evolve, making it almost impossible for rules-based systems to keep up. Real-time ML monitors every stage of the customer transaction, adapting to account for new anomalies and suspicious patterns to protect against the latest attack methods. 
• Predictive analysis: By weighing historical data, behavior monitoring and applying advanced statistical models, machine learning is capable of preventing fraud without creating a CX problem. 

3. Data encryption and security measures

Fraud rings know ecommerce merchants are collecting more customer data than ever before. While this data provides valuable insights for merchants to help improve the CX, it also leaves customers vulnerable to targeted attacks. 

With end-to-end encryption and secure payment gateways, data is protected against data breaches through a sophisticated process of data scrambling. This adds an extra layer of security if that data is ever intercepted. 

What are the benefits of customer experience fraud prevention?

At its core, CX fraud prevention is about distinguishing between fraudulent and legitimate orders while providing a memorable customer experience. But a customer-centric fraud prevention system also brings significant benefits for ecommerce merchants. 

Conversion rates

With CX fraud prevention and machine learning, false declines are reduced and friction is eliminated from the checkout process. This leads to much higher customer conversion rates over time. 

Customer satisfaction 

With fewer false declines and processing delays to contend with, customers enjoy a frictionless shopping experience, which inspires loyalty and increases their lifetime value. Positive reviews and recommendations from satisfied customers help build a positive brand reputation. 

Chargeback reduction

With advanced algorithms and ML as the driving force, it’s easy to determine which chargebacks are legitimate and which should be challenged. 

Chargeback win rates increase, and merchants can confidently approve more orders. With higher win rates and accuracy, merchants can build trust with banks and financial institutions. 

Operational efficiency 

Advanced machine learning algorithms make immediate, accurate decisions on whether a transaction is legitimate. Quicker and more accurate decisions during fraud review reduce calls to call centers, freeing up customer service representatives for more complex inquiries, and call wait times go down. 

Instead of fraud prevention and damage control, energy is redirected to the customer experience and revenue optimization. 

How data intelligence and automation can transform CX

From watertight security to customer empowerment, making ML the driving force of your fraud prevention strategy can have a transformative impact on customer experience. 

Customer experience automation

Automated ML recognizes complex patterns that signify return abuse or other types of fraud, stopping fraud attempts in real-time and making  CX more efficient for genuine customers — from moving through the checkout process, to receiving a refund after making a return. 

Fraud detection technology

Advanced fraud detection identifies the relationships among complex signals and behavioral biometrics that rules-based systems can’t, including IP addresses, transaction histories, browsing behavior, keystrokes and the like. Fraudulent transactions are prevented, while legitimate ones pass through seamlessly. 

Identity resolution solutions

Incorporating secure login systems makes it clear to customers that their security is a priority. When used judiciously, advanced security solutions like multi-factor authentication can increase customer trust and inspire brand loyalty. 

Risk assessment in CX

ML eliminates the guesswork and human error that come with manual review and rules-based systems. While rules-based systems often work with siloed data, machine learning algorithms instantly weigh a vast number of data points and signals for highly accurate risk assessment. 

How to leverage AI machine learning 

Fraud prevention works best for businesses when it works harmoniously with every step of the customer journey — not against it. And when it comes to CX, nothing is more important than ensuring a seamless shopping journey. 

Signifyd is a commerce protection platform that protects ecommerce merchants while ensuring their customers have a shopping experience that keeps them coming back. With Guaranteed Fraud Protection, Complete Chargeback Protection and more, Signifyd provides advanced CX fraud protection solutions, streamlining every step of the customer journey. 

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