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From friction to trust

Historically, fraud prevention has been viewed as a trade-off between robust security and a seamless customer journey, with security often prevailing. However, all too often this ends up impairing business functionality or, worse, complicating the customers’ journey with multiple logins and additional authentication steps.

Harold van Graan.

As fraud tactics evolved over the years, so too did prevention and detection strategies, making security integral to the transaction and enhancing the customer experience, rather than being a hurdle. This evolution allowed business and security to coexist. But is that in fact the case?

Recent technology advances on both sides of this coin have shifted this narrative. The real questions are:

● Is it still possible for increased security and low-friction customer experiences to complement each other in the age of artificial intelligence (AI) and deepfakes?

● In today’s interconnected digital economy, does fraud prevention still equate to intrusive verifications, login frustrations, and multi-factor authentication (MFA1), resulting in MFA fatigue?

The following details how modern identity tools and intentional strategies can help businesses build trust and foster loyalty, while reducing financial losses and protecting customers from identity theft.

The cost of fraud

Let us kick off with the staggering cost implications of fraud. The stakes are high. In South Africa, digital banking crime continued to surge throughout 2023, with fraudulent incidents escalating in 2024. Statistics revealed an 86% increase in reported incidents from the banking sector and a 74% increase in associated losses of just under R1,9 billion, with retail showing corresponding increases.

SA data analysed from 20242 revealed a 337% surge in identity fraud, as criminals opened new accounts or took over existing ones through a range of methods. This marks a significant increase compared to prior years and underscores the urgent need for more advanced fraud prevention measures.

Account takeover3 (ATO) and payment fraud incidents surged by 354% and 92%, respectively, highlighting the growing sophistication of fraudsters. These trends make it imperative for organisations to adopt dynamic fraud prevention strategies that mitigate risk, while ensuring a seamless customer experience.

Busting myths - security versus experience

Equating ‘secure’ with ‘friction’ is a misconception and is outdated. Modern fraud prevention solutions use real-time risk assessment, behavioural biometrics, and machine learning algorithms to identify potential fraud without burdening customers. Let us explore how businesses can strike this balance effectively.

You can start by implementing invisible security through passive fraud detection. Passive fraud checks run in the background, monitoring behaviours such as typing speed, mouse movements, and device reputation. These technologies enable seamless detection of potential threats, enhancing both security and user satisfaction. For instance, a leading international financial institution implemented such strategies to reduce customer friction and detect fraud in real time.

These included:

● Behavioural biometrics that identify user behavioural anomalies such as typing cadence or swipe patterns.

● Device telemetry that detects risky devices or users engaging in suspicious activities.

● Geo-velocity analysis that flags inconsistencies in user location.

These methods allow businesses to extend session lengths without frequent re-authentication, creating a seamless customer experience.

Constructive friction for high-risk scenarios

While most users enjoy frictionless experiences, constructive friction during critical moments can enhance both security and trust. This approach involves techniques such as:

● Liveness detection that ensures the individual performing an action is a live human rather than a deepfake or static image. This technology provides reassurance in high-stakes interactions such as payment processing.

● Step-up authentication adds verification steps, such as MFA or biometrics, for high-risk activities, including large financial transfers or profile updates. These measures ensure user authenticity, while maintaining trust and safety.

Such measures not only protect users, but also do so without unnecessary disruption to the customer journey. For instance, step-up authentication is triggered for high-risk actions, such as large financial transfers or sensitive profile updates, while more streamlined authentication methods are used for low-risk users and activities. This approach ensures customers feel protected without being overburdened, as consumers prefer varying levels of friction with visible security measures during critical moments, which further enhances their trust and satisfaction.

A recent study4 revealed that 38% of consumers want more visible security when accessing bank accounts from a new device, and 37% prefer it during large online transactions.

These targeted strategies serve to instil confidence and ensure a smooth experience for legitimate users.

Fraud prevention strategies for enhanced customer experience

Of course, not all users pose the same fraud risk. Adaptive security models leverage machine learning to assign risk scores dynamically, enabling businesses to:

● Allow seamless access for low-risk users.

● Apply stricter measures, such as identity verification or CAPTCHA (Completely Automated Public Turing test to tell Computers and Humans Apart), to detect suspicious activity.

● Reduce false positives that frustrate legitimate customers.

Continuous monitoring across the customer journey

Fraud detection should not be limited to the point of transaction; it should be continuous monitoring that tracks user behaviour from account registration through checkout, identifying anomalies at every stage. For example:

● Account takeover prevention (ATO) flags unauthorised logins or suspicious profile changes.

● Session hijacking detection terminates sessions with signs of unauthorised access.

Seamless account creation

Lengthy or complex account creation processes put customers off. Implementing passive verification tools, such as device reputation checks, ensures security without introducing excessive friction. This approach reduces abandonment rates, while preventing new account fraud (NAF).

AI plays a major role in fraud detection. Machine learning algorithms can analyse vast amounts of data to detect subtle patterns that are indicative of fraud. For example, these algorithms can differentiate between legitimate users and bots by identifying anomalies in behavioural data. By integrating AI into fraud prevention, businesses can:

● Identify bot-driven attacks, such as credential stuffing and brute-force login attempts.

● Detect emerging fraud techniques in real-time, keeping pace with evolving threats.

Real-world impact

A major bank⁵ in the United Kingdom leveraged advanced identity and access management (IAM) functionalities to balance enhanced security with smooth customer experiences. By implementing risk-based customer authentication, the bank achieved compliance with modern payment services regulations, which aim to enhance payment security and protect users while minimising disruptions. This allowed customers to access banking, credit card, and insurance services seamlessly and securely, improving customer satisfaction.

By leveraging advanced identity verification tools, orchestration platforms, and AI-powered analytics, while educating both customers and internal teams, businesses can effectively combat fraud without compromising convenience. The following provides practical steps you can take to set your organisation on the path to seamless fraud prevention:

● Invest in identity verification tools by implementing technologies that authenticate customers during high-risk actions.

● Orchestrate the journey by using platforms that provide fraud detection, authentication, and CX tools across the user journey.

● Educate customers and teams. Empower users to recognise phishing attempts and train teams on balancing security with usability.

● Leverage the power of AI and behavioural analytics that continuously analyse user behaviour to refine fraud detection models.

In conclusion, fraud prevention need not come at the expense of customer satisfaction. By integrating modern solutions such as orchestration platforms, advanced risk scoring, and seamless identity verification, businesses can deliver a safer, smoother customer experience. Additionally, adaptive, AI-driven strategies and a balanced authentication approach can mitigate fraud risk, while fostering trust and loyalty.

In a nutshell, it is time to bust the myth: secure experiences can also be great.

For more information, visit www.solid8.co.za.

References

¹ www.pingidentity.com/en/capability/multi-factor-authentication.html

²dfa.co.za/south-africa/2025-12-09-unlocking-the-threat-how-sim-card-fraud-undermines-digital-security-in-south-africa/

³ https://www.pingidentity.com/en/resources/blog/post/account-takeover-ato-fraud.html

⁴ https://www.pymnts.com/authentication/2023/more-than-half-of-bank-consumers-want-better-transaction-security/#:~:text=Banks%20can%20bolster%20consumer%20trust,boomers%20and%20seniors%20the%20exception

⁵ Tesco Bank Enhances Experience with Ping Identity Partnership

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