Beyond fraud: turning policy abuse into business value

Fraud is often associated with stolen cards or fake identities – but lately, policy abuse is gaining attention. How do you define it, and why is it becoming such a hot topic?

You are absolutely right. Traditionally, fraud has centred on stolen cards, fake identities, and account takeovers. These remain critically important and continue to receive significant attention. However, policy abuse is quite different and has grown rapidly in recent years, especially in Europe, where regulations such as PSD2 have drastically reduced fraud at the point of payment.

Policy abuse involves real customers exploiting legitimate rules such as return policies, promotional offers, referral programmes, or refund processes in ways businesses never intended. For example, a customer might order clothes to wear once and then return them – or create multiple accounts to repeatedly claim new customer discounts.

What makes policy abuse particularly challenging is that the people involved are often genuine customers with some real value. They are not outright criminals but opportunistic or unaware of the broader negative impact. Since they use valid identities and payment methods, traditional fraud detection tools often miss this behaviour. And with the rise of online shopping, free trial models, and tighter household budgets, the scale of the issue is larger than ever.

What’s the true impact of policy abuse on digital businesses? Is it really worth treating as a strategic priority?

Absolutely. At first glance, policy abuse might be perceived as a minor cost of doing business, but in reality, it may represent 1 to 3% of gross merchandise value. To put that in perspective, this can equal or even exceed what many businesses spend on marketing. In certain sectors, especially those heavy on promotions or generous return policies, losses can be much higher. For merchants with tight margins, it can be a serious threat.

Beyond direct financial loss, policy abuse also affects key business metrics. It skews data on acquisition costs, lifetime value, and retention, which leads to poor strategic decisions. For example, if lifetime value calculations include repeat abusers who generate low or negative margins, a company might overspend on acquiring new customers with similar profiles.

Operationally, it adds cost and complexity. High refund volumes increase logistics expenses and customer service demands. Chargebacks rise, bringing additional fees and friction with payment processors. Support teams are burdened by disputes linked to abuse, draining resources – I explored this challenge further in a previous article about chargebacks and friendly fraud.

The good news is that companies that start tracking and addressing policy abuse systematically often find they can reduce losses significantly with relatively small changes. Improvements in policy design and user segmentation frequently deliver better returns than traditional fraud prevention or even new customer acquisition. In other words, tackling abuse is not just defensive, it can really become a source of competitive advantage.

How can companies manage policy abuse without damaging customer experience or brand perception?

This is the critical challenge. The worst approach is to impose blunt restrictions or blanket policies that add friction for all users. That alienates the best customers and risks harming the brand.

The most effective approach is based on precision and personalisation:

• Design policies by trust and risk profiles. Tailor return windows or promotional access according to each customer’s behaviour and history. Loyal and low-risk customers should enjoy a smooth and generous experience, while riskier profiles face stricter but fair rules.
• Use real-time detection. Device fingerprinting, behavioural analytics, and abuse scoring models can flag suspicious patterns dynamically while minimising false positives. This allows businesses to react quickly without slowing down genuine customers.
• Apply friction selectively. Extra steps, such as identity verification or purchase limits, should be reserved for higher-risk users. Trusted customers should pass through without unnecessary barriers.
• Communicate clearly and engage. Sometimes it is better to educate or re-engage customers who may be unintentionally misusing a policy, rather than block them outright. Offering a reset or warning can preserve value without losing them. This approach turns what could be a negative interaction into a chance to strengthen trust.

Ultimately, preventing abuse should be integrated into the customer journey, not treated as an afterthought or compliance issue. When done well, it becomes part of a seamless experience where trusted customers feel valued while risks are quietly managed in the background.

Can you share any concrete examples where turning policy abuse into a value lever worked?

Certainly. One digital subscription platform struggled with high refund abuse from users exploiting free trials. Instead of shutting down trials or frustrating everyone with tougher rules, the company introduced soft identity checks and velocity limits based on device and IP address. They also tested offering a more flexible refund policy to trusted users. The result was a 30% drop in abuse, higher conversion and retention, and increased customer satisfaction.

Another example comes from a premium fashion brand. They replaced their flat return policy with a dynamic model that adjusted return conditions according to purchase history and return behaviour. Profiles identified as likely abusers were shown stricter terms or denied returns, while loyal customers continued to enjoy a generous policy. This targeted approach reduced abuse by over 35% and improved margins, without compromising the experience for high-value clients.

Both cases show that addressing policy abuse does not have to mean more friction for everyone. With the right segmentation, companies can cut losses while actually improving the customer experience.

What advice would you give to merchants or platforms that are just starting to look seriously at policy abuse?

First, name the problem. Many companies still categorise it under customer service issues or promotional losses, without recognising it as a form of behavioural fraud. Giving it a clear label makes it easier to measure, monitor, and prioritise.

Next, quantify it. Track refund rates by segment, analyse promotional usage patterns, and review chargeback trends tied to repeat users. Metrics such as abuse loss rate, abuse to lifetime value ratio, or refund claim velocity will give a clearer picture. Even a simple baseline can reveal just how much hidden value is being lost.

Then, bring the right teams together. Fraud, payments, marketing, and customer experience should all be aligned. This is not only about risk management but also about smarter segmentation, better targeting, and protecting long-term value. Policy abuse sits at the intersection of these functions, so silos make it harder to solve.

Finally, start small but think big. Pilot changes with a subset of customers, measure the results closely, and iterate. Over time, refine policies and detection tools to create a balanced system that minimises abuse while maximising customer satisfaction and growth. Quick wins will build momentum, and over time the organisation can move from patching problems to building a more resilient growth model.