Fighting fraud can feel like a juggling act. It's a constant effort to stop bad actors from trying to take your money, while not spending too much on your defenses — plus making sure shopping stays fast and easy for real customers.

To pull this off, many companies are using technology to do more with less. Instead of hiring huge teams of people to check every single order by hand, they are switching to smart digital tools that let artificial intelligence do much of the heavy lifting. It's like having a team of super-fast detectives who can scan millions of purchases instantly to catch the bad guys without slowing down the stream of genuine shoppers who are delivering those all-important profits.

Yet the best defense also looks at the big picture, not just the checkout button. Successful businesses watch for warning signs during the entire customer journey, from the moment someone creates an account all the way to when they return an item. By watching every step, it is much easier to spot fraud early and take action — with less of the friction that frustrates genuine customers and hurts profits.

What is fraud management?

Fraud management is like having a high-tech security team for your money. Its main job is to catch bad actors trying to steal cash or data, while making sure your real customers can shop without problems. This is happening everywhere: online when someone buys a product on their phone and offline when they tap a card at the store.

And you can be sure Visa is the top team — it was ranked number one by Juniper Research in its eCommerce Fraud Prevention 2025–2030 Leaderboard.¹

Businesses must try to prevent fraud, as well as detect and intercept it whether that is financial or non-financial; the best method is using a mix of automated AI tools and rules. The first step is to use AI, which is like a detective that is able to scan billions of transactions in milliseconds. Fraud scoring systems look for clues that humans might miss — such as changing customer and ecosystem behavior — and give every purchase a risk score from 0 to 99. A low score indicates a low risk; a high score suggests elevated fraud risk. Rules then apply thresholds or policies to inform what action a business should take, such as allowing a transaction to proceed or triggering extra checks.

Next there is authentication, which is like checking someone’s ID card. Systems such as EMV 3-D Secure ask the bank, “Is this really your customer?” They might use a one-time code sent to a phone or even a fingerprint to be sure. Finally, there’s case management. If a purchase looks suspicious then experts — or advanced software — take a closer look to decide if it should be blocked.

The goal here is simple: to spot fraud as early as possible. By moving away from checking orders by hand and using these smart digital tools instead, businesses can reduce crime faster and keep shopping easy and safe for everyone.

How does fraud management work?

Fighting fraud is changing: Imagine walking into your favorite store to buy a pair of jeans. You try them on, then head to the counter and pay. It’s simple, right? But behind the scenes of every purchase — especially online — there is an invisible battle going on between businesses trying to keep money safe and cybercriminals trying to steal it. To win this fight, financial institutions and businesses are changing their strategies. They’re moving away from checking things by hand to using smart technology to watch for the danger signs — and learning exactly how customers behave so they don't mistake them for a fraudster.

From human eyes to AI: In the past, if a purchase looked suspicious, then a human might step in and take a look at it, otherwise known as a manual review. They would check the customer’s address details, look at the order, and decide if it was safe to proceed. The problem? This process is really slow and expensive. Today, businesses are switching to digital screening, using advanced computer software to check orders instantly. In fact, merchants now check more than twice as many orders using digital tools as they do by hand.² This shift allows stores to do more with less, approving your order in milliseconds so you don’t have to wait while still keeping bad actors out.

Guarding the whole journey: For a long time, security teams only focused on the moment people clicked on the buy button. But criminals are smart: they don't just attack at the shop, they will try to pick your pocket before you even get there, so they can make a purchase anytime, anywhere. They may also try to return a fake item for money back later. Now businesses are using fraud tools throughout the entire customer journey. This means they look for risk signals when you log in (to stop hackers from taking over an account) and even when someone requests a refund. By watching the front door (login) and the exit (returns), businesses can stop bad actors who try to sneak in undetected.

Being smart about saying no: Have you ever had a card declined? It can be embarrassing and frustrating. Sometimes, banks reject a card because they think it is being used by a thief when actually it’s the legitimate cardholder who has been flagged by mistake. Blocking good customers like this, called a false decline, is a huge problem that is expected to cost the global economy more than $264 billion a year by 2027.³ To fix this, financial institutions are refining their rules. They are learning to tell the difference between high-risk fraud signals (like multiple failed transaction attempts) and low-risk situations, like insufficient funds or an old, closed account. The goal is to stop the bad guys without annoying the good guys.

Battle of the bots: The scariest part of this battle is that criminals are using new technology, too. They use AI to create deepfakes — fake videos that look real — or write believable phishing emails to trick people. Such criminal innovation moves very fast. To keep up, financial institutions are using their own AI and something called behavioral analytics. This is like a digital fingerprint: the system learns your habits, such as how you type, where you shop and what you usually buy. If a transaction fits your profile, it goes through. If it looks odd — like you suddenly start buying expensive jewelry in a country you’ve never visited — the AI flags it. This helps spot unusual patterns that a human might miss on their own.

Looking at the big picture: Security experts have realized that building a profile means looking at all the ways account holders interact with their bank. For example, if they were to only watch credit cards, they could miss a thief using a debit card. Looking at the big picture means everything from sending and receiving bank transfers to getting cash from an ATM, loan applications and more. All of these actions, including payment and non-payment, help tell a story about that person’s behavior. And because fraud is not segmented and looked at in isolation, blind spots are removed and fraudsters are less able to get a foothold in the system.

What can businesses do to improve fraud prevention?

The invisible shield: Imagine you are about to download the latest accounting software for your business. You click buy and within a blink of an eye, the download starts. It feels like magic, but behind that button press a massive, invisible battle is taking place. It is a battle between businesses wanting to sell you the latest software and cybercriminals trying to take money. To keep the internet safe, companies are using some incredible technology. They are not just hiring more security guards, they are building really smart digital defense systems. These systems work faster than a human ever could, learn from mistakes and look at the big picture to stop bad actors without slowing you down.

Automated decisions in a flash: Until recently, if a purchase looked suspicious, a human might have to check the address, look at the credit card number, and decide if it was safe. But the manual review process is time, money and labor-intensive. Today, businesses use automated decisioning tools that can screen a transaction in milliseconds, so human experts don’t have to waste time on those tasks. This reduces the amount of manual reviews for security teams by more than 25%.⁴

Reducing the false alarms: Have you ever tried to buy something — maybe something low value like a snack or a drink — and your card got declined even though you had enough money? That false positive, or false decline, happens when the security system blocks a good customer because it erroneously thinks they are a fraudster. This is embarrassing and frustrating, but it’s also a very costly problem. To fix this, businesses are adopting AI-driven scoring. Instead of just saying yes or no, the system gives every purchase a risk score from 0 to 99. A score of 0 means the purchase is safe, while 99 indicates a high probability of fraud. Because the AI is so smart, it can tell the difference between a criminal and a genuine customer buying something while traveling in a new city.

Layering the defense: Most people who lock their front door when they leave the house also check the windows are shut too. In the same way, protecting payments requires more than just one lock, called “layering”. Businesses use different AI models to protect every step of the customer journey. They don't just check when you click the buy button; they’re watching when you create an account, when you log in, and even when you ask for a refund. They use tools like Visa Account Takeover Protection to help make sure a hacker hasn't stolen your password and Verification Services to help ensure you are who you say you are. By layering these tools, they cover all the points of vulnerability. If a fraudster manages to sneak past the login screen, the next layer of defense at the checkout will catch them. It is like an obstacle course that is easy for you but much harder for a thief.

The 360-degree view: If financial institutions want to be better at fraud management, they need to see everything at once. Managing fraud effectively requires a 360-degree view to monitor the entire payments landscape in real time. This means looking at the customer’s whole financial behavior. The system learns what is normal for them: for example, do they usually shop for affordably priced items in a particular city? If suddenly their account tries to buy ten expensive watches in a country they have never visited, the system spots the difference quickly. By understanding the whole picture — real-time behavior, location and past history — financial institutions can spot and intercept instances of fraud no matter what trick the criminal tries to use.

What does Visa offer?

Visa Risk Manager (VRM) is like a bouncer who enforces the venue’s own rulebook. Instead of checking every guest by hand and slowing down the line, VRM provides financial institutions with a real-time decisioning platform where they define the rules. Using transaction risk scores and other parameters, VRM consistently applies those financial institution-configured rules at the door, helping issuers focus on the highest-risk transactions while allowing legitimate customers to move through smoothly. As a comprehensive software-as-a-service risk management platform, issuers can monitor accounts, set dynamic risk rules and automate responses to suspicious behavior.

Decision Manager has studied billions of past shopping trips and transactions to learn what a legitimate transaction looks like versus what a fraudulent transaction looks like. It uses machine learning, which means it gets smarter with every single purchase. It automates the work too: instead of a human having to look at every order to see if it looks suspicious, this system helps spot genuine customers and lets them make purchases instantly. And it helps block the bad actors automatically, to help prevent the store from losing money, and real customers won't get stuck waiting in line.

Visa Managed Services provides access to experienced fraud risk professionals who can support a company’s existing fraud operations. Depending on the organization’s needs, this support may include developing elements of a fraud risk strategy, assisting with rule development for risk tools, or helping manage day to day activities during periods of limited staffing. The model is flexible and can range from advisory support to more hands on operational assistance. 

AI and machine learning models analyze large amounts of payment data to help spot fraud and identify risk. Instead of focusing on just one kind of transaction, they help protect the entire payment journey — from in-store card payments to online purchases, to other non-card payments. By learning from patterns across a wide network level view of transactions, these systems can recognize emerging fraud trends and adapt in order to improve protections more broadly. They also look for early warning signs of suspicious activity so action can be taken sooner and many problems can be stopped before real harm occurs.

The Featurespace Platform offers a suite of AI-powered fraud prevention and detection solutions. It studies customers’ typical habits such as what they shop for and when, and helps build a clearer picture of what good behavior looks like — whether customers are tapping a card or using an app to pay. Because it looks at the big picture of money moving around the world, plus the tiny details of personal habits, it gives businesses a more complete map to spot unusual activity. This means they don't have to rely on guesswork: Featurespace, a Visa solution, provides instant risk scores so you can take immediate action across multiple payment methods, including credit and debit cards, ACH, Faster Payments, wire transfers, checks and person-to-person (P2P) transfers.

Using proprietary Adaptive Behavioral Analytics (ABA), Automated Deep Behavioral Networks powered by machine learning, and Large Transaction Model (LTM), Featurespace helps identify risk, intercept new attacks and spot suspected fraud early — including fake account openings and complex merchant fraud. This all takes place in real time, and while ensuring legitimate payments continue to flow as normal.

Guarding the whole customer journey is key to managing fraud, wherever it strikes — and by using Visa tools powered by AI and machine learning you can see the bigger picture, spot the signs and take swift and decisive action.

How can businesses use Visa fraud management solutions?

Decision Manager

Lighten the load when it comes to fraud management and make checking suspicious orders one by one a thing of the past. By adopting tools like Decision Manager, merchants can reduce the number of orders that need a human review. This is a game-changer for operational costs. Instead of paying experts to watch routine orders, businesses can let AI handle the easy stuff automatically. This allows staff to focus purely on the most tricky, complex cases that really need their attention. The result? A faster checkout for shoppers, better allocation of resources and significantly lower costs for the business.

Optimized decline rules

There is nothing more frustrating for a customer than trying to buy something and having their card declined when they have plenty of money. The false positive is a double-edged sword for businesses: first, you lose the sale; second, you have to spend time and money investigating why the system made a mistake in the first place. Organizations that optimize their decline rules are turning this situation around. By using advanced data to fine tune their systems, they can stop blocking good customers. This reduces the operational headaches and costs associated with digging into false alarms. More importantly, it opens the door for more sales. When you stop saying no to valid purchases, your revenue naturally goes up. It is about finding the sweet spot — keeping the fraud rules tight enough to stop more criminals, but flexible enough to let more legitimate transactions sail through smoothly.

The $54 billion shield

The scale of digital crime might be huge, but the defense system fighting it is even bigger. In 2023 alone, the ecosystem of fraud management solutions of Visa helped block more than $54 billion⁵ in attempted fraud. How does Visa do it? It’s not just one tool, it is a massive, always-on network. Visa analyzes hundreds of signals across roughly 300 billion+ transactions a year to assess risk.⁶ It uses state-of-the-art Cyberfusion Centers that operate 24/7 to watch for attacks. By combining deep industry expertise with billions of dollars in technology investments, Visa acts like a giant, invisible shield. This ecosystem analyzes patterns across the globe instantly. If a new fraud trick pops up in one country, the network learns from it and protects businesses everywhere else. This proactive defense keeps the digital economy safe, ensuring that billions of dollars stay where they belong — in the hands of legitimate businesses and consumers.

Featurespace x Danske Bank

Speed is everything when fighting fraud. In the past, spotting a crime might have taken minutes or even longer — an eternity in the digital world. Featurespace is changing the game by giving financial institutions the ability to respond to threats in real time. Rather than just looking at a transaction after it happens, Featurespace uses pre-emptive technology. The platform uses Adaptive Behavioral Analytics (ABA) to understand what normal looks like for every customer. It doesn't just look for bad transactions, it looks for changes in behavior. If a criminal tries to use a sophisticated trick, the AI can spot the anomaly near-instantly. For example, when Danske Bank integrated Featurespace’s solution, it was able to drive a reduction in its fraud detection time from 10 minutes down to just 24 seconds. When financial institutions can move from reacting to problems to actively preventing them, it means drastically cutting down the time it takes to stop a thief and boosting their overall security.