What Are The Best Tools To Stop Fake Supplier Invoices?

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When weighing up the best tools to stop fake supplier invoices, it’s important to consider a number of factors. Success rate, how quickly the AI powered fraud detection systems work, and geographical coverage are three things to compare, alongside integration methods and security measures

Whether you’ve experienced the financial losses, reputational damage and strain on supplier relationships as a direct result of paying fake invoices, or are looking to proactively fight fraud, you’re in the right place. Solutions like Trustpair are powerful automated verification tools, built with artificial intelligence to scale across thousands of vendors and payments per month. 

Key Takeaways: Choosing Software to Prevent Fake Supplier Invoice Fraud

  • Leverage AI-Driven Protection: The most effective fraud detection solutions utilize Machine Learning (ML) to identify complex fraudulent patterns and proactively defend against evolving cyber attacks.
  • Context-Specific Solutions: Selection should be based on your specific business model, such as whether you are a regulated entity, the nature of your target audience (B2B vs. B2C), and the types of products or services offered.
  • Eliminate Payment Risks with Trustpair: Platforms like Trustpair offer specialized vendor account ownership verification, ensuring that supplier payments are only ever sent to legitimate, verified accounts.
  • Prevent Invoice Fraud Automatically: Modern software reduces manual oversight by automating the validation process, effectively blocking “fake supplier” schemes before a transaction occurs.

Best tools to stop fake supplier invoices: our comparison table

SoftwareTool descriptionAI applicationSuitable for
TrustpairA B2B payment security tool focused on vendor managementVerifies vendor bank account ownership by cross-referencing global payment data, and automates account controls based on the outcomes of those checksEnterprise Treasury and finance teams looking to prevent payment fraud, Business Email Compromise (BEC) and vendor fraud
SiftA digital trust platform using AI technology to monitor the entire customer journeyWorks with user behaviour analytics and vast amounts of data network to predict intent based on how users interact with a siteB2C companies looking to prevent account takeover fraud without impacting their customer experience
FeedzaiA RiskOps platform using AI algorithms to protect against financial crimeReal time transaction monitoring with explainable AI, it provides clear reasoning for alerts to meet banking audit and compliance standardsBanks, fintechs and regulated financial services industry managing fraud, AML, and compliance in one place
BioCatchBehavioural and device biometrics for bankingAnalyses physical interactions (typing speed, mouse tremors) to detect potential fraud and social engineering scamsFor institutions concerned with authorised push payment scams, such as banks and payment provider tools
SEONAPI-first AI tools to stop fraudulent activities Digital footprinting, AI analyzes social media and web presence linked to an email or phone number in real-timeiGaming and casino websites aiming to protect their accounts against abuse and mitigate fraud risks

Why is Trustpair the best solution against fake supplier invoices?

Trustpair offers a market-leading solution for those fighting fake invoices or supplier impersonation, such as CEO fraud. It delivers real-time account validation and ongoing monitoring for every single payment. As an automated solution, it requires no direct repetitive or manual input from finance or procurement teams, and has a history of a 100% success rate

Benefits of Trustpair

Key benefits of Trustpair’s AI in fraud detection systems include: 

  • Three way matching of invoice data against verified external databases to protect payments while avoiding human error
  • Instant verification and real time monitoring of vendor bank details to ensure new vendors are legitimate and power fraud investigations 
  • Continuous monitoring to defend against fraudulent ‘change of payment details’ requests and supplier account takeover
  • Global coverage (190+ countries) ensuring that both domestic and international payments are protected
  • Full regulatory compliance with anti-money laundering (AML) and Know Your Business (KYB) legislation 

The best fit for?

The types of businesses that would benefit most from working with Trustpair include: 

  • Enterprise-level organizations processing hundreds or thousands of payments per month, requiring automated fraud detection tactics
  • Companies with global supply chains, including business partners in jurisdictions where data is less transparent or regulations less strict 
  • Finance and treasury departments with complex supply chain and payment procedures

Sift: behavioural analytics

Sift is a fraud prevention solution for direct-to-customer businesses. It works by using behavioural analytics factors to ‘risk score’ each customer, tracking digital journeys to combat fraud like account takeovers.

Behavioural biometrics improve fraud detection accuracy by detecting anomalies in user actions, such as mouse movement or typing patterns.

Sift leverages AI-powered automation to help companies scale their fraud prevention, relying on AI rule sets to oversee thousands of customer accounts and payments without requiring manual intervention. 

The key benefits associated with Sift are: 

  • Reduced customer chargebacks: customer identity theft verification prevents fraudsters from impersonating consumers and making fraudulent transactions on their behalf
  • Securing customer accounts against takeover fraud: promoting customer retention and growth in lifetime value metrics
  • Reducing friction in ecommerce and marketplace customers

Sift is most suitable for direct to consumer businesses, including marketplaces and eCommerce websites protecting against common and new fraud patterns. 

Feedzai: regulated environments

Feedzai is a platform purpose-built to prevent financial crime in highly-regulated environments, such as in banks, lenders and other financial institutions. It targets anti-money laundering (AML) compliance, achieving higher bank account opening and transfer security.

The RiskOps platform uses AI for fraud detection, tracking real-time behaviour (including device usage) and transaction data to identify abnormal behaviour that signals signs of manipulation.This empowers teams to step in before the fraud actually occurs. 

Benefits of Feedzai’s financial fraud detection include: 

  • Explainable AI audits for regulated institutions bound by the EU’s AI Act, for example
  • Large teams that require visibility over fraud, AML and compliance into a single dashboard
  • Built-in ‘responsibility’ ensures that the algorithm acts fairly and without bias, for fraud detection accuracy

Feedzai is most suitable for fintechs, banks, insurance companies, and any other company bound by financial regulations. It works for fraud risks across the globe.  

BioCatch: protect against social engineering 

BioCatch is aimed at protecting banking customers against social engineering attacks; authorised push payment scams, phishing and coercion that relies on bypassing traditional ‘hard’ defences. 

The proprietary ‘DeviceIQ AI’ validates the integrity of the device environment, including checks for deepfake injection, agentic AI usage, and AI-assisted access vectors. 

BioCatch offers the following benefits to its customers: 

  • Analysing specific behavioural factors, like typing cadence and mouse movements, to detect AI 
  • Automated device access decisions based on these behavioural factors (with a very low risk of false positives)
  • Protection against AI-powered threats in customer account takeover fraud

BioCatch is most suitable for banks and financial institutions that offer log-in portals to their customers, since it protects access to the platform from suspicious patterns and devices. 

SEON: iGaming expertise 

SEON is a fraud management solution with specific use cases for iGaming and online casinos. Since generative AI can generate realistic synthetic data for fraud detection model training, the AI aspect of this protects against bonus abuse and synthetic ID creation (the potential for a single customer to open and profit from multiple fake accounts).

Fraud detection platforms like SEON can leverage network effects, where fraud data from one client helps protect all others, enhancing accuracy. SEON uses AI to perform digital footprinting, accessing over 900 first-party data signals to check factors like domain age, email breach history, emulator use and residential proxy detection. This works in real-time to shut down account access before it’s given. 

SEON offers the following benefits: 

  • Specific understanding and expertise in the iGaming industry
  • Complex checks that feel lightweight to the customer, meaning no added friction
  • The ability to view the audit trail and decision in a single platform (all customer risk signals in a single view)  

SEON would be most suitable for iGaming and online casino companies, or membership-style businesses that offer account bonuses, but want to protect against abuse. 

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FAQ
Frequently asked questions
Browse through our different sections and find the answer to your question.

AI detects fraud by analysing massive datasets in real-time to identify patterns, through anomaly detection and behavioral inconsistencies that deviate from established legitimate user profiles and historical data. It uses machine learning models to score legitimate transactions based on risk factors such as geographical location, device fingerprinting, and velocity.

There is no single ‘best’ tool because the ideal choice depends on whether your priority is e-commerce chargeback protection (Sift) or banking compliance (Feedzai), for example. In B2B payment security, Trustpair is the market leader. Selecting the right software requires matching the specific AI model to your industry’s unique transaction patterns and risk tolerance.

AI systems continuously learn, rules based systems don’t. Adaptive learning systems in fraud detection update automatically to identify new and emerging fraud tactics. Compared to traditional methods like static rules, AI systems improve their accuracy and adaptability by continuing to analyze vast datasets, allowing them to identify emerging threats before they are widely reported. With dynamic rules that evolve over time, AI systems improve their ability to detect anomalies and reduce false positives compared to static rule-based systems.

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