Fraud DetectionOutlining Key Components of a Good Strategy, Plus the Top 10 Service Providers of the Year

February 28, 2023 | 24 min read

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Fraud Detection

In a Nutshell

Reviewing orders to try and detect fraud is a necessity for any eCommerce operation. But what does an effective fraud detection solution look like, and how can you tailor it to suit your individual needs? Most importantly, how do you go about finding the right tools and services to fit your specific needs? Let’s find out.

What is the Best Fraud Detection Solution? What Should it Do & How Do You Gauge Its Effectiveness?

Here’s a startling statistic: card-not-present channels now account for roughly 80% of all fraudulent transactions in the US.

Investing in resources to detect fraud is an absolute necessity for any business that accepts and processes card-not-present transactions. But, to meet this challenge, you need to craft a comprehensive game plan.

What kind of fraud detection strategy is right for your business? What exactly should it entail? And, should you build your own in-house solution or hire a fraud detection service to handle the heavy lifting? We’ll cover all that and more below. First, though, let’s outline what exactly we’re talking about.

What is Fraud Detection?

Fraud detection is a series of manual and automated processes aimed at identifying and responding to fraudulent activity. It entails a lot more than just deploying a couple of fraud filters at checkout:

Fraud detection operations may be executed through automated frameworks like machine learning software, or through a series of manual practices. In most cases, you’ll require some combination of the two. 

The aim here is to go beyond simply spotting fraudulent transactions before it’s too late. A good approach will also help you identify trends, patterns, and flaws in your current fraud prevention strategy. You need to be able to compare suspicious transactions to other incoming data and verify trends and potential patterns to prevent them from reoccurring later on. 

What Should Your Fraud Detection Strategy Help You Accomplish?

Your strategy should help you spot and resolve current attacks, fix weaknesses in your internal practices and systems, and prevent future offenses. With the right strategy in place, you should see:

Accurate Risk Scoring

In order to resolve flawed systems and address incoming attacks, you need to know when, where, and how they’re happening. Fraud scoring is intended to sort transactions according to predetermined triggers, such as location, transaction history, and user authentication. 

Richer Data

Fraud detection relies on accurate data analysis to paint a clear picture of each individual transaction. Managers should be able to look up users based on historical transactions, email, or other identifying characteristics to evaluate the trustworthiness of that user based on previous data. 

Better Customer Relationships

A fraud detection strategy isn’t just about identifying potential bad actors. It’s also about protecting your relationship with legitimate customers. Everyone appreciates knowing their data is in good hands when they shop.

Closer Social Media Integration

Not every type of fraud is easily detectable. First-party fraud, for example, is a post-transactional threat that doesn’t happen until well after the transaction has been finalized. With social media lookup features, merchants can confirm user identities, ascertain compliance, or determine if their products are being used illicitly. 

A User-Friendly Interface

Fraud detection systems are often complex and difficult to navigate. That’s especially true for patchwork systems that are compiled without a good strategic rationale. Your UX interface should include improved visual data analysis and should be customizable and easy to follow.

Scalability

Scaling your fraud detection solutions to suit your budget is a wise move. Paying per API can limit overzealous fraud scoring efforts that often lead to false declines and other headaches by limiting triggers and scoring fields. 

Fewer Chargebacks

An effective fraud detection solution should help you avoid chargebacks, too. While you may not be able to completely stop disputes from rolling in, a smart fraud detection strategy can help you eliminate a large number of potentially fraudulent transactions that could lead to chargebacks later on.

Fraud detection is one investment you can’t afford to skip.REQUEST A DEMO

What Does a Fraud Detection Strategy Entail?

Most fraud detection strategies include some form of data gathering and analysis. Specifically, these break down into two separate techniques: statistical analysis and artificial intelligence-based analysis through machine learning. 

Let’s go over both techniques in greater detail. 

Statistical Analysis

This can be performed either through a series of system-based operations (through a POS terminal or CRM management system), or it can be done manually. The function here is to detect and gather potentially fraudulent data, compare it against any historical data, and then confirm if the data appears fraudulent or not. 

Statistical analysis techniques include:

  • Establishing Parameters: Statistical parameters will be established based on averages, performance metrics, and probability ranges for accurate data capturing.
  • Data Matching: Comparing data points to eliminate duplicate records and establish links between data sets.
  • Variable Analysis: Analyzing the potential relationship between two or more variables and comparing incoming data and historical data to establish patterns.
  • Probability Factoring: Mapping the probability of fraudulent activities based on data captures and analysis to determine the likelihood of fraud.

Machine Learning

Many merchants have switched the majority of their fraud detection efforts to AI-based machine learning software. AI is able to effectively observe, identify, and isolate incoming data much faster than a human being. It can also swiftly filter that data according to predetermined rulesets.

Some of the techniques that AI-based fraud detection systems utilize include:

  • Data Mining: Machine learning systems can collect and filter data in real-time. Data can be mined from a preselected group of characteristics, then associations can be made that signify fraud patterns.
  • Neural Classification: AI fraud software utilizes neural network functionality to classify incoming data and identify associations. Flagged data will proceed through a series of interconnected rulesets.
  • Pattern Recognition: After the neural net, data can be scanned for fraudulent patterns. For example, if a transaction meets preset fraud parameters, it will be sorted for more screening or flagged for manual review.

As the name implies, machine learning software is capable of “learning” appropriate actions based on the amount and quality of data it is fed. Machine learning can, therefore, become more accurate over time. But, although this system is incredibly advanced and innovative, it must be guided by human oversight to function properly. 

A machine isn’t capable of making complex, logical decisions based on conflicting data points. The machine can only sort and flag that information according to predetermined rules. This is why we encourage most merchants to try a blended approach (more on this later).

Learn more about machine learning

Identifying the Right Fraud Detection Tools

The specific fraud detection tools you deploy will be a key point of your strategy. 

You can’t simply deploy one or two disparate tools, with no strategy for how to coordinate them, and expect to see results. Rising to meet a dynamic challenge like third-party fraud means having multiple tools in place, all working in tandem.

Think about it like a net: the finer the mesh, the more you’ll catch. Criminals targeting your business will have their work cut out for them if you adopt the right fraud detection software, hardware, and monitoring tools, then deploy them in a strategic manner.

Some key fraud detection tools we recommend include:

Learn more about fraud detection tools

Fraud Detection Systems: “Built-in” vs. “In-House”

Each of the fraud detection techniques listed above can be used through a variety of merchant-facing systems, including self-managed approaches and third-party service providers. To fully understand your options, let’s take a closer look at the pros and cons of each:

Built-In Fraud Detection

In many cases, your payment processor will provide built-in options for fraud prevention. These generally consist of pre-loaded software that runs checks on a per-transaction basis, and reports are usually accessible through your eCommerce portal.

Some processors offer select fraud solutions standard to all customers, while more making more comprehensive fraud protection an “opt-in” service. Shopify’s Fraud Protect, for example, must be enabled by the merchant.

The main benefit to this process is data sharing. Many cards will have been run on that particular processing platform more than once; even when this isn’t the case, often the users can be identified through historical records. There are some downsides to consider, though.

Pros:

  • Simplest option. Many of these built-in tools are effectively a “plug and play” option for fraud detection.
  • Most cost effective, as they’re typically offered for free as a component of service.
  • Open data gives you the benefit of a much larger body of data for more informed risk analysis.

Cons:

  • Payment processors tend to “play it safe” when rejecting transactions. Could lead to false negatives and lost customers.
  • You will have little control over setting parameters to reject or accept transactions.
  • Lack the ability to take a closer look at each transaction for gray areas like suspected friendly fraud.
Save time. Recover revenue. Prevent more chargebacks.REQUEST A DEMO

In-House Fraud Detection

In-house fraud detection systems offer full control over your fraud review processes and also allow full control over data protection and integrations. Autonomy is an attractive prospect, which makes many merchants happy to deploy staffing resources to keep their fraud prevention in-house.

This system can work well. However, success — or failure — hinges on whether you have the staff, technical know-how, and resources available. For all but the smallest operations, it may be necessary to maintain a dedicated fraud management department.

Pros:

  • Total autonomy. You can control exactly how fraud is handled, what standards are used, what indicators are considered, etc.
  • Costs are more transparent; in-house management can give you more insight into how resources and time get allocated.
  • If you identify new trends in fraud activity, you can respond by altering your strategy in real time.

Cons:

  • Limited data insight. The body of data you generate is your only indicator;  you could miss broader trends and developing threats.
  • Hiring additional or part-time seasonal staff (during the holidays, for example) will mean costs are uncertain and hard to plan.
  • Not cost-effective; you’ll have to allocate resources that could be used more effectively in other areas of the company.

In-house systems seem great for the control they give you, but ultimately, it can become an uncertain drain on your expenses. As we’ll see below, it might be wise to consider another option.

Fraud Detection Systems: API-Based vs. Cloud-Based

Of course, another option is to simply offload the burden of fraud detection onto a third party.

Third-party service providers offer a full catalog of varying fraud detection solutions that cater to every merchant type and budget. Although some fraud detection services offer staffing and other manual review benefits as a premium perk, most utilize one (or both) of the integration models below:

API-Based Integrations

Advanced Programming Interfaces, or APIs, allow users to program to a pre-constructed interface, instead of individually programming a device or piece of software. The use of APIs in fraud prevention allows your provider to tailor products to your specific needs. This means that the service provider will offer you a menu of features and let you choose what works for your business.

Essential features for this integration include:

  • Affordability
  • Scalability
  • Real-Time Data Enrichment
  • Functional UX
  • Projected Return on Investment

Keep in mind that API-driven providers may also involve hidden costs. Licensing issues can arise if you require more than one provider, which can impact costs. Additionally, you may require additional platform integrations that can increase your front-end investment, development, and maintenance costs. 

Cloud-Based Integrations

Cloud-based integrations are a next step up from API-centric integrations because they are faster, more comprehensive, and require fewer maintenance resources. If costs are a concern, cloud-based options can have a positive impact on your bottom line. Perks include:

  • Faster Data Retrieval
  • Real-Time Data Analysis
  • High-Limit (or Unlimited) Data Storage
  • Upgrades & Bug Fixes Come Standard

Same as the API model, though, there are some downsides to cloud-based integrations to consider. There could be a higher user learning curve, as well as additional costs like hardware, integration, and support fees.

Blended Fraud Detection Strategies are Best

Developing a fraud detection strategy doesn’t have to be a question of “build” or “buy.” A hybrid strategy, based on a close working relationship between your internal team and a third-party service provider, offers you the best of both worlds.

You have intimate operational knowledge offered by your internal team. At the same time, you have access to the expansive data and expertise that a professional online fraud detection service brings to the table.

Remember, though: an off-the-rack, “cookie-cutter” solution is not what you need. No two businesses have the same risk, so a “one-size-fits-all,” automated solution will ultimately be ineffective. With that in mind, here are a few points to consider when looking for the right service provider for your needs:

  • What are the guarantees? And what are those guarantees based on?
  • If the price is based on transaction volume, can you analyze future growth potential well enough to budget accordingly?
  • Are there client testimonials? Are you able to speak with current customers?
  • Is the vendor adaptable and agile enough to support future technology and fraud developments? Can they grow with your company?
  • Do they have prior experience with merchants in your vertical? Partners who understand merchant experiences will be more effective at minimizing risk without compromising growth.
  • Do they specialize in certain product verticals or risk profiles? If so, do those specialties align with the contours of your business?

Now that we’ve gone over what fraud detection is, how it works, and which methods you might deploy — let’s talk about the best fraud detection service providers available today. 

Top 10 Fraud Detection Service Providers

The provider you should turn to for fraud solutions depends on the specific areas where you need help. This list is in no way exhaustive. However, it does showcase a few of the most reputable vendors and their specialties.

Also, note that these are objective recommendations. We took a detailed look at the highest-rated fraud prevention companies in operation today, and developed a rundown of the leading service providers.

Ratings and reviews were averaged based on real customer reviews from sources including G2, TrustRadius, Software Suggest, and Gartner. The “pros” and “cons” we mention are also paraphrased directly from real, firsthand customer reviews.

Signifyd

#1 | Signifyd

G2 ranks Signifyd as the #1 eCommerce fraud protection service available.

Signifyd provides an end‑to‑end Commerce Protection Platform. This platform leverages their Commerce Network to maximize conversion, automate customer experience, and eliminate fraud and customer abuse for retailers.

Signifyd uses big data and machine learning to provide a 100% financial guarantee against fraud and chargebacks on approved orders. This effectively shifts the liability for fraud away from eCommerce merchants, allowing them to increase sales and open new markets while reducing risk.

Major Clients:

Pros:

  • Integrates seamlessly and is easy to use
  • The Payments Optimization module works with strong customer authentication (SCA), which helps with compliance for EU-based payments
  • Transactions are generally approved in seconds

Cons:

  • It can be very costly for an enterprise-type customer
  • No real-time data
  • Sometimes the human (non-automated) review process can take longer to complete in cases where additional verifying information is needed from the customer

Pricing: Call for a free quote.

Extra Perks:


Fraud Detection

#2 | Arkose Labs

Arkose Labs’s fraud deterrence platform eliminates sophisticated bots, frustrates fraudsters, and delivers user-centric account security. Combining real-time risk classification with dynamic challenges, the AI-powered platform uses enterprise-grade CAPTCHAs to defeat persistent bot and fraud farm attacks and protect platforms from account takeovers, fake account creation, spam, scraping, and more.

Major Clients:

Pros:

  • Easy to integrate with existing websites and workflows
  • Constantly improving their product, adding new challenges, monitoring traffic, and suggesting additional integration strategies
  • Tailors enforcement mechanisms to specific needs

Cons:

  • Lacks an API endpoint that provides real-time monitoring and the capability to configure alerts
  • Pricey; not ideal for start up companies seeking immediate ROI
  • Requires front-end integration

Pricing: Call for a free quote.

Extra Perks:

  • Free Demo

Fraud Detection

#3 | NoFraud

NoFraud is an eCommerce fraud prevention and checkout solution that protects businesses from fraudsters, eliminates chargeback losses, and provides smoother, more frictionless checkout experiences for trusted shoppers.

NoFraud integrates directly with eCommerce platforms to scan every order for signs of fraud in real-time. They use a combination of powerful algorithms and proactive human review to provide simple pass-or-fail decisions for every transaction. Their aim is to eliminate the need to manually review orders or monitor fraud scores, and provide a 100% financial guarantee for chargebacks.

NoFraud Checkout also dynamically adapts the number of input fields based on customer risk factors. More trustworthy shoppers are sped through, while riskier shoppers must provide more information.

Major Clients:

Pros:

  • Seamless integration; easy to use and navigate
  • Excellent customer service and tech support
  • Decreases chargebacks

Cons:

  • Software is extremely sensitive; flags some orders needlessly
  • The integration ranks at the higher end of the pricing scale
  • They only cover purchases up to $2,000, but will increase the limit (for an additional fee)

Pricing: Call for a free quote

Extra Perks:

  • APIs
  • Free Demo

Fraud Detection

#4 | DataDome

DataDome protects mobile apps, websites and APIs from online fraud, including scraping, scalping, credential stuffing, and account takeover.

They also protect against layer 7 DDoS attacks and carding fraud. Their AI-powered bot detection engine processes more than one trillion pieces of data every day, from 25 worldwide points of presence. This helps protect some of the world’s largest global eCommerce businesses in real time.

DataDome is easily deployed and is compatible with 100% of web infrastructure technologies, thanks to strong technical and business partnerships with market leaders. It runs anywhere, in any cloud, and is compatible with multi-cloud and multi-CDN setups.

Major Clients:

Pros:

  • Seamless, instinctual interface without a lot of noise
  • Customizable rulesets with excellent onboarding
  • Provides SDK (software development kit) integrations that simplify coding obfuscations and coupling challenges

Cons:

  • No ‘out of box’ API augmentation (manages internal systems only)
  • Software is sensitive; can lead to false negatives
  • No APIs with intro platform

Pricing: Entry level price of $2,990

Extra Perks:

  • Free Quote

Fraud Detection

#5 | Seon

SEON helps its customers uncover fraud patterns and generate new revenue streams. Intelligent risk scoring with AI and machine learning adapts to your business risk evaluation. This means you get full visibility and complete control over every interaction, order, account, transaction, and opportunity.

Major Clients:

Pros:

  • Seamless integration with a wide range of data points
  • Detailed IP geolocation checks, screening of personal data for fraudulent indicators, checks social media profiles, and the rules management system is quite easy to use without specific knowledge
  • Platform is extremely well organized

Cons:

  • Lacks the means to export a full blacklist or internal scoring data points
  • Loading customers into the system can take a while
  • IP checks could be more precise with mobile IPs

Pricing: Starting at €299

Extra Perks:

  • APIs
  • Free Demo

Fraud Detection

#6 | Riskified

Riskified uses powerful machine-learning algorithms to instantly recognize good customers and weed out bad ones with a 100% chargeback guarantee. Merchants can safely approve more orders, expand internationally, and eliminate the costs of fraud while providing a frictionless customer experience.

Major Clients:

Pros:

  • It's easy to filter through thousands of orders to identify general trends
  • Obtain quick responses and solutions when submitting claims and reimbursements
  • The effectiveness of the product; does not require heavy maintenance

Cons:

  • Sometimes people are flagged for no reason
  • Focusing purely on fraud prevention means merchants in the EU need to handle 3DS/PSD2 on their own
  • There are no mobile SDKs, yet more than 50% of eCommerce is mobile in some countries

Pricing: Call for a free quote

Extra Perks:

  • APIs
  • Chargeback Guarantee
  • Real-Time Monitoring

Fraud Detection

#7 | Sift

Sift, formerly Sift Science, empowers companies of all sizes to unlock revenue without risk. Industry leaders like Twitter, DoorDash, and Twilio rely on Sift to stay competitive and secure.

Sift prevents fraud with industry-leading technology and expertise, an unrivaled global data network, and a commitment to building long-term partnerships with our customers.

Their Digital Trust & Safety Suite prevents fraudulent payments, fake accounts, spam, scams, and account takeover. They reduce false positives and power frictionless experiences in the process.

Major Clients:

Pros:

  • Easy to use and provides excellent visibility about any suspicious behavior
  • Automate workflows are very flexible and easy to understand
  • Straightforward integration

Cons:

  • Route building and initial configuration of workflows could be improved
  • Does not always accurately link accounts
  • Product is priced relatively high

Pricing: Volume based pricing. Call for a free quote

Extra Perks:

  • APIs
  • Free Quote
  • Real-Time Monitoring

Fraud Detection

#8 | Kount

Kount’s AI-driven Identity Trust Platform protects the complete customer journey for more than 9,000 leading brands and payment processors.

Powered by its Identity Trust Global Network ™, Kount, An Equifax Company, links billions of trust and fraud signals to protect every interaction. It provides end-to-end coverage from account creation and login to payments and disputes.

Major Clients:

Pros:

  • Kount RIS API is very clear, concise, and easy to implement
  • The approve/decline model has proven to be a seamless experience
  • Also checks a customer’s chargeback history

Cons:

  • Many different clients and customers are automatically flagged with a low Omniscore
  • Decline rules are very limited
  • Datamart BI reporting tool is not optimized, and limited

Pricing: Two-tier pricing based on small business and mid-market models

Extra Perks:

  • APIs
  • Real-Time Monitoring
  • Payment Verification

Fraud Detection

#9 | ClearSale

ClearSale’s balanced approach to eCommerce fraud protection and prevention yields the highest approval rates and lowest false-positive rates in the industry.

Having been in business for over two decades and running, and with a 99% retention rate, that’s really saying something.

ClearSale does business in over 160 countries. They’ve won several awards for stellar customer service and proven value as a top fraud prevention brand.

Major Clients:

Pros:

  • Completely seamless integration
  • Ease of use and dashboard implementation
  • Extremely high customer service ratings

Cons:

  • Unclear service charges
  • KPI’s and analytics are not always communicated effectively
  • Unclear attribution factors corresponding to the source of the converted sale

Pricing: Two-tiered payment plan, with a free trial period for either.

Extra Perks:

  • Free Trial
  • Plug and Play Service
  • Real-Time Monitoring

Fraud Detection

#10 | Prove

Prove is an emerging star in the fraud detection services game. They offer phone-centric solutions that enable clients to acquire new consumers and engage with their existing consumers.

This is done by removing friction while bolstering security and enhancing consumer privacy & consumer choice. Prove Pre-Fill™ enables companies to drive more signups by auto-filling forms with authenticated identity data, to accelerate revenue while mitigating fraud across mobile, desktop, tablet, contact center, and in-store channels.

Major Clients:

Pros:

  • Seamless integration and swift onboarding
  • Offer a robust series of products, from Payfone Pre-fill to soft authentication like Payfone TrustScore, to even more friction-induced authentication products like Instant Link
  • Offers additional optimization services

Cons:

  • Password-protected documentation is slow-loading and difficult to sort
  • Slight overlap between Trust and Verify products
  • Some of Prove's products rely on third-party data such as Mobile Network Operations (MNOs) and credit bureaus, but their latest mobile-first products do not have this dependency and rely only on data gathered via SDK

Pricing: Call for a free quote

Extra Perks:

  • APIs
  • Real-Time Monitoring

Optimize Your Online Fraud Detection

Fraud detection is complex, and even with the right strategy, there’s no guarantee that you’ll see optimal results. Most conventional fraud tools are very limited in terms of their response to first-party fraud, for instance.

So, why not improve your odds?

Chargebacks911® should be an integral part of any multilayer fraud management system. We work closely with in-house management teams to create a customized integration, along with the most comprehensive, transparent, end-to-end outsourcing option available.

Our solutions increase revenue retention and make fraud detection and chargeback mitigation tasks more efficient. We allow our clients to reallocate resources to revenue-generating departments. And, of course, this is all backed by the industry’s only performance-based ROI guarantee.

Contact us today to learn more about our solutions and how Chargebacks911 can help optimize your online fraud detection efforts.

FAQs

How is fraud usually detected?

Fraud detection is a series of manual and automated processes aimed at identifying and responding to potential acts of fraud. Fraud detection is usually carried out through automated frameworks like machine learning software, a series of manual review practices, or some combination of the two. The process usually involves fraud detection tools like AVS, geolocation, and 3-D Secure.

What are the types of fraud detection?

Most fraud detection strategies include some form of data gathering and analysis. Specifically, these break down into two separate techniques: statistical analysis and artificial intelligence-based analysis through machine learning.

What is the most common fraud detection method?

Often, your merchant services provider or payment processor will provide built-in options for fraud prevention. These generally consist of pre-loaded software that runs checks on a per-transaction basis.

For more comprehensive fraud protection, you may have to opt-in. Shopify’s Fraud Protect, for example, must be enabled by the merchant.

Should I outsource my fraud detection?

It depends on the specifics of your business.

Third-party fraud detection systems are intended to take the burden of fraud prevention and management from your shoulders in a way that still allows you some agency. However, this isn’t to imply that this is the best method for every merchant. If your company has a higher chargeback ratio, for instance, you may need a more multi-layered strategy than merchants with no chargeback issues.

How Do I find the right fraud solution?

A one-size-fits-all, automated solution will ultimately be ineffective. So, you need to weigh candidates against the specifics of your business. But generally speaking, a hybrid strategy, built on a close working relationship between your internal team and a third-party service provider, will offer the best results.

With a hybrid in-house and outsource solution, you have intimate operational knowledge offered by your internal team. At the same time, you have access to the expansive data and expertise that a professional online fraud detection service brings to the table.

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