Because "we got the ratio down" and "we fixed the problem" are not always the same thing.
If your fraud strategy is "add another rule and hope," we should probably talk. Fraud and chargebacks rarely start with one bad rule. They usually start with a pattern nobody fully understands.
Approval rates change. Chargebacks creep up. Fraud losses increase. One affiliate suddenly performs very differently than the others. A new acquisition channel looks great until the disputes arrive six weeks later. Customer-service complaints start sounding suspiciously similar. Transactions that looked profitable at authorization turn into losses after refunds, disputes, fees, and operational costs catch up.
Then everyone starts tuning thresholds. Sometimes that helps. Sometimes it just moves the problem somewhere else.
Our Fraud & Chargeback Reduction work is designed for merchants and SaaS companies that actually want to understand why the problem exists and fix it at the source.
We look across the transaction lifecycle, customer journey, fraud controls, acquisition channels, operational processes, dispute patterns, data quality, and payment behavior to figure out what is really driving the issue.
Because a fraud problem is not always a fraud-tool problem. And a chargeback problem is definitely not always solved by making the chargeback ratio prettier.
Chargeback ratios get everyone's attention because processors, acquiring banks, and card networks pay attention to them. Fair enough.
But the ratio is usually the end of the story, not the beginning.
A dispute may originate with a fraudulent transaction. Or misleading marketing. Or an affiliate promising something your product does not deliver. Or confusing billing descriptors. Or a cancellation process customers cannot navigate. Or recurring billing that technically complies with the terms but consistently surprises the customer. Or poor customer service. Or bad data feeding a fraud model.
By the time the chargeback appears, the actual problem may have happened days, weeks, or even months earlier.
So we work backward.
We look at where the customer came from, what they were shown, how the transaction was presented, what data was collected, how fraud controls evaluated it, what happened after authorization, how fulfillment or service delivery occurred, how support interactions were handled, and what eventually caused the customer or issuer to dispute the transaction.
That is how you solve the problem. Not by staring at the numerator.
Payment fraud is rarely static. Fraudsters adapt. Affiliates adapt. Customers adapt. Your product changes. Marketing changes. Traffic sources change. Fraud rules get tightened. Approval rates move. Then someone loosens the controls because conversion dropped, and suddenly everyone is surprised when losses come back.
Fraud management is a system. Change one part and something else usually moves.
Sometimes the fraud controls are too loose. Sometimes they are too aggressive and good customers are being rejected while the bad traffic finds another way through. Sometimes the fraud platform is doing exactly what it was configured to do — and the configuration is the problem. Sometimes the data feeding the system is incomplete, inconsistent, or simply wrong.
We do not begin by assuming the answer is "buy another fraud tool." There are already plenty of fraud tools. We start by figuring out what is happening.
Affiliate and partner channels can scale quickly. So can the problems hiding inside them.
One affiliate may appear to be your highest-performing source because they generate huge volume and beautiful front-end conversion. Then the refunds arrive. Then the disputes. Then customer-support complaints.
Affiliate fraud can take a lot of forms: misleading claims, fake leads, incentivized traffic, stolen identities, manufactured conversions, unauthorized recurring billing, traffic sources that were never disclosed, or marketing practices that create customers who were destined to dispute from the beginning.
We help connect the front-end acquisition data to the payment outcomes. Which affiliates produce the most disputes? Which produce the highest fraud rates? Which look profitable before downstream costs but become unprofitable after chargebacks, refunds, support, and fees?
Once that data is connected, the conversation changes. You stop arguing about whether an affiliate "seems shady." You can show exactly what the traffic is doing.
Fraud teams often focus heavily on the moment of authorization. That makes sense. It is also only one moment.
We look at the entire lifecycle: acquisition, checkout, authorization, routing, retries, fulfillment, support, refunds, cancellation, recurring billing, descriptor recognition, and eventually the dispute.
Those events are connected. If you only look at the final chargeback record, you are trying to solve a movie by staring at the last frame.
We would rather watch the whole thing.
Good fraud and chargeback analysis depends on connecting data that often lives in different places: payment processor data, fraud-platform results, CRM data, affiliate data, customer-service tickets, refund records, chargeback files, subscription activity, device signals, marketing source information, and order history.
Sometimes the answer becomes obvious only after those datasets are joined together. Maybe a specific campaign produces customers who cancel at three times the normal rate. Maybe chargebacks increase dramatically when a transaction is retried after an initial decline. Maybe customers who contact support but do not receive a refund are overwhelmingly responsible for one dispute reason code.
This is why we spend so much time in the data. Opinions are useful. Patterns are better.
This part matters.
There are companies looking for help because their fraud and chargeback programs are not working. And there are companies looking for help because they want to keep doing something they know is problematic while staying just far enough below a processor or card-network threshold to avoid getting shut down.
We are interested in the first group.
If your goal is to improve your customer experience, reduce fraud losses, fix operational problems, clean up bad acquisition channels, improve data quality, and build a healthier payment program, we can help.
If your goal is essentially "How do we keep doing the same thing without Visa noticing?", we are not your people.
We do not build strategies around hiding bad behavior, manipulating monitoring programs, disguising transaction activity, or making an unhealthy business model look temporarily less unhealthy.
We work with organizations that actually want the problem fixed. Coincidentally, those are also the organizations where we tend to get the best results.
Fraud reduction does not mean declining everything that looks remotely suspicious. Anyone can eliminate fraud by eliminating sales. That is not particularly impressive.
A good fraud program balances loss prevention with approval performance, customer experience, operational cost, and revenue.
If a rule blocks $1 million in fraud but also declines $8 million in legitimate customers, that is not automatically a successful rule. If chargebacks decline only because refunds explode, congratulations — you moved the loss from one spreadsheet column to another.
We look at the total economics. The goal is not a beautiful fraud metric. The goal is a healthier business.
This work is designed primarily for merchants and SaaS companies that have a real fraud or chargeback problem and genuinely want to fix it.
Maybe your chargeback ratio is trending in the wrong direction. Maybe your acquiring bank or processor is starting to ask questions. Maybe fraud losses have increased and nobody can explain why. Maybe an affiliate channel suddenly looks suspicious. Maybe your fraud, finance, operations, and customer-service teams all have different explanations for the same problem.
You do not need to have the answer when you call us. That is what the engagement is for.
You do need to be willing to follow the data wherever it leads.
The best fraud and chargeback programs are built around understanding: which transactions are actually risky, which customers are being incorrectly rejected, which channels create downstream problems, why customers dispute, and which controls improve the economics of the business.
Not a temporary fix. Not a prettier dashboard. Not a strategy for staying just below somebody's monitoring threshold.
A real reduction in the underlying problems causing fraud and chargebacks in the first place.
Because "we got the ratio down" and "we fixed the problem" are not always the same thing.
