Loyalty programme fraud is the deliberate exploitation of reward systems through external hacking, customer abuse of programme loopholes, or employees misusing privileged access to manipulate rewards for personal gain.
Loyalty programme fraud is the deliberate exploitation of reward systems by external hackers, internal staff, or customers abusing loopholes. It costs businesses up to $3 billion globally each year and affects programmes across every sector. This guide covers the main fraud types, how to spot the warning signs early, and six proven strategies to protect your programme and your customers.
In this guide, we’ll expose the risks facing loyalty programmes and give you actionable steps to protect your customers against loyalty programme fraud. Whether you’re dealing with account takeovers, points hacking, or redemption fraud, here you’ll find proven methods to detect suspicious activity early — before the damage is done.
Loyalty programme fraud is the deliberate exploitation of reward systems for financial gain. It can originate from outside your organisation, from within it, or from your own customer base — and each source requires a different defensive response.
The three primary sources are external threats, internal threats, and customer-driven fraud (also called friendly fraud). Understanding where an attack originates is the first step toward building an effective defence.
Loyalty fraud is rising because the gap between attacker sophistication and programme security is widening. In our opinion, it comes down to two core problems.
First, many businesses still protect their loyalty programmes with basic authentication methods, while fraudsters employ increasingly sophisticated tactics to exploit those vulnerabilities. Second, low awareness compounds the problem, and this is despite the dramatic rise in loyalty and rewards fraud over the past decade.
The scale of the problem is significant. Loyalty and rewards fraud now has an estimated global cost of up to $3 billion per year. And despite being widespread across all businesses, just over a quarter of all documented online frauds in 2021 targeted loyalty schemes specifically.
In-house loyalty programmes are disproportionately vulnerable because they often operate on legacy security infrastructure that was not designed with modern fraud in mind. Purpose-built loyalty platforms like Propello Cloud are fortified to the same standard as banking security infrastructure. That security depth is one of the most compelling arguments in the build versus buy question.
Our own research supports this. According to Propello Cloud’s 2025 Customer Loyalty Report — based on conversations with 100 enterprise brands — 78% of businesses cite data privacy and compliance as a critical challenge, and 80% report difficulties with churn management. Both are direct consequences of programmes that were not built with security as a foundation.
Loyalty programme fraud takes many forms. The source of the fraud (external, internal, or customer-driven) tells you where to look. The type of fraud tells you what to look for. Here are the most common attack patterns we see across enterprise programmes.
External fraud involves cybercriminals targeting your loyalty infrastructure from outside the organisation. Every loyalty account contains a goldmine of personal data from email addresses to credit card details. When breached, this sensitive information often ends up sold on dark web marketplaces.
Cybercriminals use multiple attack vectors simultaneously. Through sophisticated phishing schemes, they manipulate customers into revealing login credentials. Once inside, they harvest data, drain points, and can use compromised accounts for money laundering through points conversion.
What is particularly concerning is the rise in identity theft. Fraudsters targeting loyalty programmes exploit the fact that many still rely on basic authentication. They use stolen credentials to create fake accounts and drain reward points before detection systems can respond.
Friendly fraud is fraudulent behaviour carried out by existing customers. Some bad actors in your customer base will deliberately violate terms and conditions, gaming the reward system to their advantage. Some estimates claim up to 86% of chargebacks are intentionally fraudulent.
These are not external hackers. They are customers exploiting reward programme vulnerabilities, often in ways that appear legitimate at first glance. Common tactics include manipulating referral programmes with fake leads and exploiting multi-factor authentication gaps for double-dipping points across channels.
Internal fraud is perhaps the most dangerous category. Company insiders commit over half the total amount of fraud and cost businesses over $1 billion annually. They understand the security protocols and know how to exploit them without triggering alerts.
You can often identify a consistent pattern: internal fraud often starts small. An employee checking their own reward point balance, or making minor adjustments. Over time, this escalates to siphoning reward points from dormant accounts or generating and redeeming points through fake accounts. Proper account monitoring and robust access controls are essential to catching this early.
A data breach is far more than just stolen points. In 2022, the average cost of a data breach reached $4.35 million. The reputational damage adds to the initial financial blow. Bad press around privacy deters customers from purchasing from the affected brand.
Many in-house built programmes still operate with legacy security measures that cannot keep pace with modern threats. Without adequate network security, hackers gain unfettered access to loyalty accounts and extract everything from customer data to transaction histories.
An account takeover (ATO) is when a fraudster gains control of a legitimate customer’s loyalty account and locks out the real owner. In 2021 alone, over 24 million US households fell victim to loyalty-related ATOs.
These attacks are subtle. Rather than immediately draining points, fraudsters typically play the long game, starting with minimal changes to personal information, gradually expanding their control until they can modify authentication methods entirely.
Spoofing is an old-school tactic that continues to work. Modern spoofers build convincing front ends of reward programmes that perfectly mirror legitimate brands, complete with professional design and convincing user interfaces.
The 7.3% increase in email-based phishing attacks seen in 2021 only tells part of the story. Today’s spoofing operations target multiple vulnerabilities simultaneously, manipulating both technology and human psychology. They are particularly effective against loyalty schemes because customers are naturally receptive to messages about their rewards.
Points hacking has evolved from opportunistic theft into a systematic attack on reward point ecosystems. Hackers now target entire point storage infrastructures rather than individual accounts, aiming to break into dormant accounts that collectively hold millions in monetary value.
A complete loyalty profile — including login credentials and reward card numbers — can be sold for significant sums on dark web marketplaces. Buyers then execute rapid-fire points redemptions before detection systems can respond.
Redemption fraud operates in the grey areas of legitimate programme usage. Whether they are employees with backend access or customers testing system boundaries, these fraudsters exploit normal points redemptions in ways that can be genuinely difficult to detect.
The most effective redemption fraud schemes combine multiple techniques. Internal actors might manipulate loyalty accounts while simultaneously creating plausible customer service scenarios to justify their actions. Meanwhile, some customers systematically probe for gaps in redemption rules, attempting to claim benefits from expired promotions or through unauthorised channels.
No industry with a loyalty programme is immune to fraud. However, certain sectors present more attractive targets based on their reward structures and redemption flexibility. Here are the patterns we have observed across industries.
The travel sector is one of the most targeted industries, with fraud costing an estimated $1 billion annually. Fraudsters approach travel programmes differently from other sectors. Rather than immediate point drainage, they play the long game. Compromised frequent flyer accounts are often left dormant for months while cybercriminals gradually test control limits and prepare for larger-scale theft.
What makes travel programmes particularly vulnerable is their high-value redemption options and transferability features. Our analysis shows that fraudsters specifically target accounts during peak booking seasons, when large-scale point redemptions appear more natural and are therefore harder to flag as suspicious activity.
In retail, the most alarming pattern connects directly to account takeover attacks. Once fraudsters gain control of loyalty accounts, they systematically purchase gift cards with stolen points. These untraceable gift cards are then resold through dark web marketplaces and hidden Telegram channels for 25-60% of their face value.
This resale ecosystem has become so sophisticated that some fraudsters specialise solely in converting stolen loyalty points into gift cards, while others focus exclusively on the resale network. The clean transaction trail this creates makes it harder to flag than direct point theft.
While banks typically maintain robust security for their core services, their loyalty programmes often operate with less stringent protection creating what’s often called a “side door” vulnerability. According to the 2023 FICO Trends Report, there has been a 53% increase in loyalty fraud attempts in the financial services sector.
Fraudsters exploit the grey area between legitimate and fraudulent activity. They convert stolen points into legitimate purchases, transfer them across multiple accounts, and create plausible customer service scenarios to justify suspicious transactions, making the trail increasingly difficult to track.
Detecting fraud early is crucial for preventing it. Each type of fraud leaves its own distinctive fingerprint. The good news is that these patterns often emerge well before any actual fraud takes place. Fraudsters typically test the waters first, probing for vulnerabilities and experimenting with small-scale attacks before launching full-scale operations.
Understanding these patterns is your first line of defence in protecting both your customer accounts and your brand’s reputation.
Cross-reference account activity with customer lifecycle stages. New accounts showing behaviours typical of long-term customers — like high-volume transactions or multiple device usage — often indicate synthetic identity fraud. Similarly, established accounts suddenly deviating from years of consistent behaviour warrant immediate investigation.
| Warning Sign | What to Watch For | Why It Matters |
| Device Patterns | Multiple accounts accessing from identical device IDs | Sudden spikes in multi-account access from one device warrant investigation |
| Unknown Devices | High number of logins from unidentifiable devices | Often indicates device spoofing attempts to mask fraudulent access |
| Geographic Anomalies | Multiple logins from different countries in short timeframes | Legitimate users rarely access accounts from various global locations within hours |
| Bot Activity | Rapid-fire login attempts across multiple accounts | Signals potential credential stuffing attacks |
| Mass Account Changes | Sudden surge in detail modifications across multiple accounts | Often occurs after security alerts, as fraudsters rush to maintain control |
| Points Activity | Unexpected activation of dormant loyalty points | Fraudsters frequently target unused points for quick monetisation |
Focus particularly on combinations of patterns. Unusual earning patterns combined with immediate redemptions often signals organised fraud rather than opportunistic abuse.
| Warning Sign | What to Look For | Risk Level |
| Unusual Earning Patterns | Sudden spikes in points accumulation; points earned from atypical channels; multiple accounts earning from the same source | High |
| Redemption Anomalies | Instant redemption of newly earned points; points redeemed across multiple locations simultaneously; large redemptions from dormant accounts | Critical |
| Account Behaviour | New accounts with excessive point activity; multiple accounts transferring points in a chain; points being moved across geographical regions | High |
| Transaction Patterns | Small transactions designed to stay under fraud thresholds; multiple failed redemption attempts followed by success | Medium |
| System Interactions | Automated point checking activities; multiple accounts accessing points balance simultaneously | Medium |
Authentication failures often precede larger fraud attempts. Quick response to these patterns can prevent more serious breaches.
| Warning Sign | What to Look For | Risk Level |
| Login Attempts | Multiple failed logins followed by success; failed attempts from various IP addresses; rapid-fire login attempts suggesting bot activity | Critical |
| MFA Challenges | Repeated MFA code requests; MFA attempts from multiple devices; failed MFA validations followed by device changes | High |
| Password Resets | Multiple password reset requests; password changes from unfamiliar locations; reset attempts outside normal business hours | High |
| Session Behaviour | Unusual session lengths; multiple concurrent sessions; session jumps between different regions | Medium |
| API Interactions | Failed API authentication spikes; unusual patterns in API calls; authentication bypass attempts | Critical |
Compare redemption patterns against each customer’s historical behaviour. Significant deviations from established patterns often indicate potential fraud.
| Warning Sign | What to Look For | Risk Level |
| Timing Patterns | Off-hours redemption activity; rapid successive redemptions; seasonal pattern deviations | High |
| Value Patterns | Multiple small-value redemptions; points redeemed just below threshold limits; unusually large redemptions from seasoned accounts | Critical |
| Channel Usage | Redemptions across multiple channels simultaneously; switch from preferred to new redemption methods | Medium |
| Product Selection | Sudden preference for high-value rewards; focus on easily convertible items; gift card heavy redemption patterns | High |
| Account Activity | Redemptions immediately after point earnings; points transferred then quickly redeemed; multiple accounts with similar redemption patterns | Critical |
Loyalty fraud creates a devastating ripple effect that impacts multiple stakeholders. A single breach can undo years of carefully built customer relationships, affecting not just the compromised accounts but also the friends and family members of those customers who lose confidence in the programme entirely.
| Stakeholder | Impact Type | Consequences |
| Legitimate Customers | Account Impact | Loss of hard-earned points and rewards; compromised personal and financial data |
| Legitimate Customers | Experience Impact | Reduced programme value from tighter security; service disruptions; eroded trust in brand relationships |
| Brands | Direct Financial | Costs of reimbursing compromised accounts; inventory losses from fraudulent redemptions; regulatory fines and penalties; emergency security investments |
| Brands | Business Reputation | Wavering customer trust and loyalty; decreased programme participation; negative press and social media coverage; market share loss to more secure competitors |
This is why at Propello Cloud, we emphasise that fraud prevention is not just a security function. It is about preserving the entire ecosystem of trust between brands and their loyal customers. According to our 2025 Customer Loyalty Report, 83% of enterprise brands already cite customer engagement as their number one challenge. Fraud makes that challenge significantly harder.
These real-world cases illustrate the devastating impact of loyalty fraud. These examples come from major brands that, despite having substantial resources, still fell victim to fraud attacks. Their experiences offer valuable lessons for protecting loyalty programmes.
The 2020 Marriott International breach perfectly illustrates how compromised employee credentials can lead to catastrophic data breaches. What started as unauthorised access through just two employee logins turned into a massive security incident that affected 5.2 million guest accounts.
The attackers accessed Marriott’s property management system — the core application used across their franchise network — and harvested extensive customer data including contact details and valuable loyalty account information such as points balances and account numbers.
Despite their loyalty programme passwords remaining secure and their Bonvoy platform staying protected, the breach still resulted in an £18.4M fine. This case shows how even partial account takeovers can have devastating financial and reputational consequences.
The North Face incident of 2022 shows how rapidly modern account takeover attacks can escalate. The attack began weeks before detection, ultimately compromising 200,000 customer accounts.
The attackers targeted specific data points: personal details, purchase histories, and critically, XPLR Pass Rewards information. While The North Face’s decision not to store payment card details prevented direct financial theft, the compromise of their reward programme forced them to wipe tokens on affected accounts and require password resets across their entire system.
The real damage was not financial — it was reputational. Fraud prevention is not just about protecting financial data. The most lasting damage often comes from the compromise of loyalty-specific information and the subsequent loss of customer trust.
Protecting reward programmes is not about choosing between security and user experience — it is about prioritising both without compromising either. Through protecting millions in loyalty points and working with enterprise brands, we have refined six essential strategies that create robust security without friction.
A Breach Detection System (BDS) is non-negotiable for protecting loyalty accounts. By the time a data breach is detected, attackers have typically been in the system for months.
Think of BDS as your loyalty programme’s immune system. It continuously monitors for suspicious activity across your network, flagging potential threats before they can compromise customer data. The power of modern BDS lies in real-time analysis. It can catch hackers mid-attack, forcing them to abandon your platform.
Key warning signs your BDS should track:
Even brands with strong security teams remain vulnerable without automated breach detection. When you are handling sensitive customer data and valuable reward points, you need technology that never sleeps. I have found a great list of the top ten BDS systems currently available. Some of them are even free.
Google reports that multi-factor authentication blocks up to 99% of phishing attacks, making it one of the most impactful single changes you can make to protect loyalty accounts.
An effective MFA should layer security intelligently:
Some customers may initially question additional security steps. That concern subsides quickly when they understand these measures protect their valuable reward points. Resistance will pale in comparison to appreciation. Over half of consumers think positively about businesses that implement strong security measures.
Fraudsters are not just attacking your systems; they are directly targeting your customers through social engineering. Cybercriminals impersonate legitimate communications to harvest login credentials and account information.
Take a page from the banking sector’s playbook. Leading banks build customer trust through proactive education about security measures, and we have seen this work just as effectively in loyalty programmes. Security education does not dampen programme enthusiasm. If anything, it demonstrates value.
According to KPMG’s Consumer Loss Barometer, consumers were asked what actions their banking institutions should take to reduce security breaches. Frequent communications and updates scored 38%, a direct line to the security team scored 13%, and mobile security courses scored 10%.
What successful customer education looks like:
An educated customer base is your first line of defence against fraudulent activity.
Smart workflow design plays an integral role in effective friendly fraud detection. Customised triggers act as an early warning system, helping identify and stop suspicious activity before it escalates.
Triggers that have proven particularly effective:
What makes these workflows powerful is their ability to adapt to your specific loyalty programme. Each trigger can be fine-tuned based on your customer behaviour patterns, making it easier to distinguish between genuine activity and potential fraud.
While Experian’s latest fraud report highlights how smart workflows combat APP and P2P fraud (page 16), we have found they are equally crucial in detecting friendly fraud – a growing concern, with 59% of eCommerce merchants reporting increased attacks (see page 6 in the same report).
The most secure loyalty programmes operate through small, dedicated teams on both sides. At Propello Cloud, we assign focused customer success teams to work with just a select few client representatives, creating clear, traceable points of interaction that quickly contain any potential security risks.
Key considerations for managing backend access:
Modern loyalty software eliminates the need for large teams managing backend operations. When only a handful of people can modify reward points or account settings, unusual activity becomes immediately apparent. In our report, we found that 69% of enterprise brands now prefer outsourced loyalty solutions precisely because the tighter access controls and specialist oversight make internal fraud detection far more straightforward.
Individual security measures are valuable. But the brands that truly protect their programmes are the ones that make all the components work together. Here is how a layered monitoring system functions in practice.
Modern fraud detection requires a layered approach. From AI-powered analytics to behavioural monitoring, these tools work together to spot patterns that might slip past individual security measures. The key is real-time monitoring that adapts to emerging threats, not reactive systems that only flag fraud after it has already occurred.
Beyond monitoring, you need clear protocols for responding to suspicious activity. This means putting specific processes in place for investigating alerts, validating suspicious activity, and taking action on compromised loyalty accounts before the damage compounds.
Effective alert systems balance sensitivity with accuracy. We have found success with tiered alert systems that escalate based on threat level from automated warnings for minor anomalies to immediate action triggers for serious security risks.
Comprehensive tracking goes beyond monitoring individual transactions. It means fully understanding patterns across your entire loyalty programme from point accumulation to redemption behaviours. That broader view is what allows you to identify potential fraudulent activity before it scales.
The landscape of loyalty programme security is evolving rapidly, driven by technological advancements and changing fraud patterns. Here is where we see things heading.
The future of fraud detection lies in AI-powered solutions. Through our work with major brands, we are seeing how machine learning models identify both known and emerging fraud patterns in real-time. AI’s ability to analyse vast datasets, spotting suspicious patterns that legacy systems miss, without creating friction for legitimate customers, is transforming what is possible.
According to Propello Cloud’s 2025 Customer Loyalty Report, 62% of enterprise brands are already investing in AI and machine learning capabilities for their loyalty programmes. The brands that move early on this will have a significant detection advantage.
Data sharing is becoming crucial in the fight against fraud. Modern fraudsters do not operate in silos, so neither should our defence strategies. 81% of industry leaders believe cross-sector collaboration is essential. Secure data consortiums and improved intelligence sharing help identify fraud patterns across multiple programmes and stop attacks before they spread.
Physical biometrics like fingerprints remain important, but the future lies in multi-layered authentication. Based on the research we have conducted, we can expect a combination of behavioural biometrics, device intelligence, and advanced analytics to become the standard for loyalty programme access.
The future of fraud detection is shifting from reactive to proactive. This transformation is backed by significant investment. A recent worldwide study showed a substantial increase in fraud prevention budgets across selected countries, with an overwhelming focus on real-time monitoring and AI. This investment reflects a fundamental shift in how organisations approach loyalty programme security.
After exploring the complex landscape of loyalty programme fraud, one thing is clear: protecting your loyalty programme is not just a security decision — it is a customer retention decision.
Through our experience at Propello Cloud, we have seen how a comprehensive technology platform transforms vulnerable programmes into robust engagement engines. But choosing the right partner who understands both the technical and human elements of loyalty security is crucial.
Whether you already have a loyalty programme in place, are planning to build one, or are considering partnering with loyalty specialists, here is your starting point:
Implementation checklist:
Essential resources to deploy:
Ongoing protection:
Ready to build a more secure and engaging loyalty programme? Download our Customer Loyalty Report 2025 to discover how leading brands are combining robust security measures with seamless customer experiences to drive sustainable growth.
Loyalty programme fraud is the deliberate exploitation of reward systems through external hacking, customer abuse of programme loopholes, or employees misusing privileged access to manipulate rewards for personal gain.
Watch for multiple failed login attempts, unexpected changes to account details, and suspicious redemption activity. Key indicators include logins from unusual locations, sudden changes in redemption patterns, and multiple accounts linked to a single device.
Most vulnerabilities come from outdated authentication methods, legacy systems that cannot keep pace with modern threats, and the high value of the data and points stored in accounts. This combination makes loyalty programmes an attractive target.
Implement strict access controls, limit backend access to essential personnel, maintain detailed audit trails, and use real-time monitoring. Regular security audits and clear accountability chains reduce the risk of internal exploitation.
AI systems analyse large volumes of transaction data to detect suspicious patterns in real time. Machine learning models identify both known and emerging fraud patterns while maintaining seamless experiences for legitimate customers.
According to Google, MFA blocks up to 99% of phishing attacks. Combining multiple security layers, including biometrics and device verification, reduces the risk of unauthorised access to accounts.
Brands need dedicated reporting channels, immediate account freeze capabilities, and trained security teams ready to investigate. Clear escalation procedures and secure communication methods keep customers informed throughout the process.
Travel, retail, and financial services face the highest exposure due to high-value rewards and flexible redemption options, but no industry with a loyalty programme is immune.
Highly important. Social engineering attacks target programme members directly, so regular security communications and clear guidance about official contact methods are a practical first line of defence.
Essential features include multi-factor authentication, real-time monitoring, fraud detection algorithms, secure data encryption, and regular security audits. Biometric verification adds an extra layer for high-value programmes.
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