The value that a fraud protection team (and by proxy, the fraud manager) delivers is far different from any other team in the company because it’s perceived differently.

A typical fraud team operates in a fairly gray and very tricky area. While they are measured by their impact on preventing and reducing overall fraud, they are not measured by the amount of revenue they contribute, and their impact on the bottom line.

Essentially, their role is reduced to mere gatekeepers, overlooking their true value.

It doesn’t help that every fraud decision has the potential to upset someone. Whether declining transactions or approving them, there is a looming decision that impacts bottom lines both directly (preventing loss) and indirectly (via the user experience of not declining a legit transaction, and reducing friction where needed).

Alas, there is no award for good behavior here. If a fraud manager does everything well and does their job, there’s no applause.

But if something goes wrong, they get reprimanded for subpar work. Their ongoing work to minimize fraud is rarely recognized the way it should be.

The entire perception of the fraud team’s effect and role needs to be modified and measured accordingly.

So, we’ve come up with a new KPI - one we hope will make everyone more effective and impactful in the fight against fraud.

Why a Fraud Manager Should Be Glorified

Here is the simple truth that often gets ignored:

The diligent work of the fraud team translates to extra money for the company.

As it happens, businesses care far more about what they’re losing as opposed to what they’re gaining.

This is only natural. In psychology and behavioral economics, there is a name for this - loss aversion.

Fraud managers are pressured to take extra precautions to keep fraud at bay, resulting in rejection of genuine customers, harming user experience, and leaving a lot of money on the table.

Our point is this:

Instead of the fraud manager being conceptually responsible for decreasing the amount of chargeback and fraud in general, they should just as much be held responsible for getting people in, so to speak.

In other words: it’s about time we give them the credit for actually increasing the bottom line.

Here’s what we have in mind.

Introducing a New KPI: The Revenue of New Fraud Suspect Shoppers Gained

For every business, one of the most important metrics is customer acquisition cost (CAC) because it helps calculate the overall value of a customer and the resulting ROI of an acquisition.

Stating the obvious, right?

What isn’t obvious is measuring the acceptance rate of new shoppers in spite fraud. By all accounts, it should be.

For example, a digital goods merchant can have a cushy 0.2% chargeback rate and a decline rate of 15%, which is roughly the average decline rate in this segment.

But when talking about the decline rate for new customers, the average is around 25%.

That’s simply what happens. The tendency to decline new consumers is always higher than it is to decline their long-term peers - ones you have an LTV on, know transaction history of, and other data.

So, imagine all the first-time buyers who recently snagged up a gift card, discounted coupon, and such, beyond the holiday season. Each and every one of them can become a loyal customer and even a brand advocate.

Too many are getting declined.

It’s time to invert the pyramid and measure this from the bottom up, calculating the impact of fraud manager’s performance on the bottom line through a “hidden” KPI:

the revenue of new fraud suspect shoppers gained.

How?

We suggest the following formula:

% of new visitors that were onboarded instead of rejected within a specific time frame * their lifetime value.

Let’s say that just 5% of new customers are added on a monthly basis through the deeper discovery of the root causes of fraud: poor customer experience, inadequate fraud protection tools, inefficient merchant operations, or any other issue.

Multiply that 5% with the customers’ lifetime value and voila - the narrative changes.

It’s about how much money the company could have lost but didn't due to the aforementioned action.

The fraud manager is actually impacting the company’s top line through a certain amount. Add the gross margin to the mix and you also get an understanding of how the bottom line is impacted.

They literally bring money that is otherwise lost for absolutely no good reason.

Where Is the Catch?

There isn’t any.

What we’re saying is an observation of industry peers who are privy to the inner workings of mid/large companies and their fight against payment fraud.

A simple change can make a huge difference.

Think about the way this shift in approach could improve the way employed fraud professionals perceive themselves. It would do wonders for their motivation and heighten their sense of belonging to a company that fully values their expertise.

Too many businesses operate under the misconception that their anti-fraud initiatives are designed for one function alone: loss prevention.

Cybersecurity is a team sport where everyone has to work together to keep up and stay afloat.

Successful fraud management can’t happen without everyone - the fraud team, technology - playing a role in properly responding to fraud, not just detecting and preventing.

We say this because the fraud team can’t do it alone. They need the right set of tools to improve their efficiency, something that will detect fraud quickly and accurately in real time.

Artificial intelligence, in other words.

It can reduce the time usually spent investigating each case and improve the accuracy by providing actionable insights to make a decision where it’s needed. This not only translates to less fraud but also to less customer friction.

Now, this is a sensitive area due to technology’s power to be a game-changer - and a job changer too.

While adequately trained AI models are effective at preventing fraudulent activity, the human touch is always going to be needed. There’s always going to be a need to still view the alerts and perform analysis to understand why a customer or transaction was flagged.

Plus, someone needs to take care of training data availability and accuracy, as well as make sure that the right processes are adopted so that AI models can improve over time.

By understanding this, the fraud team will have a clearer idea of how the AI model learns and works, and ultimately - helps diminish fraud.

The reality is that a fraud manager is expected to act a certain way because they operate within the confines of fraud losses. They need to realize their true position within the system - as heroes who can save the day over and over again simply by thinking bigger.

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