Leveraging AI for Risk Scoring in B2B Payment Companies

Enhance fraud detection, streamline onboarding, and improve credit risk assessments with AI-driven insights for secure B2B payments.

Is Your Business at Risk from Hidden Threats and Regulatory Challenges?

Safeguard your B2B payment operations from fraud and compliance issues, ensuring trust, efficiency, and financial stability.

KYB Onboarding Risk

Front companies slip through manual checks, exposing B2B payment networks to fraud and regulatory fines.

Invoice & Vendor Fraud

Fake invoices and rogue vendor records create unauthorized payouts, draining working capital and damaging trust.

Complex Cross-Border Compliance

Global AML, OFAC, and FATF rules change often, forcing teams to juggle siloed data and costly reviews.

Policy Breaches by Commercial Clients

High-volume customers can exceed chargeback or transaction limits unnoticed, spiking losses and scheme penalties.

FraudNet: Revolutionize Risk Management with Intelligent Solutions

Protect your B2B payments with real-time insights, fraud prevention, and seamless compliance across borders.

AI-Native Fraud Detection

Scores transactions in real time to flag anomalies before funds move.

Dynamic Risk Scoring

Evaluates alternative data for precise, up-to-date business risk.

Automated Invoice Parsing

OCR extracts and verifies fields, blocking tampered or duplicate invoices.

Predictive Client Monitoring

Alerts when customers near policy thresholds, enabling proactive action.

Key Capabilities For Business to Business (B2B) Payment companies

Unified AI Scoring Engine

FraudNet seamlessly integrates payments, KYB, and third-party data to deliver lightning-fast risk scores with less than 1% false positives. Empower your B2B payment network with unparalleled accuracy, minimizing fraud risks while ensuring compliance and enhancing trust across global transactions.

Configurable Workflows

Streamline your entire risk management process with customizable workflows. Design rules, manage queues, and handle approvals all within a single platform. This eliminates the inefficiencies of swivel-chair reviews, accelerates resolutions, and enhances your B2B payment operations.

Global Compliance Coverage

Effortlessly expand your global footprint with our continuous screening against sanctions, PEP, and adverse media. Ensure compliance without the need for additional personnel, allowing your B2B payment company to focus on growth while mitigating risks across diverse markets.
Impact & Results

Delivering Results that Matter

We don’t just promise better fraud control—we deliver tangible improvements that protect your business.

97%

Fewer False Positives

Approve more valid transactions confidently.

88%

Fraud Reduction

Experience double-digit reductions in fraud-related chargebacks

60%

Cost Savings

Save time and resources while securing your revenue.

Why FraudNet

Future-Proof Your Fraud & Risk Program

With an integrated platform designed for precision, agility, and impactful results, enabling your team to make smarter decisions, improve operational efficiency, and fuel your business growth.

Customizable & Scalable

No-code rules engine, flexible dashboards, and tailor-made machine learning models that are designed to adapt seamlessly and scale alongside your business.

End-to-End Platform

Unify fraud detection, compliance, and risk management into one powerful solution, saving valuable time and streamlining your operations.

AI Precision You Can Rely On

Reduce false positives, detect and prevent more fraud, and mitigate risk with highly accurate, real-time risk scoring and anomaly detection you can trust.

Real-Time Fraud Intelligence

Leverage advanced analytics, comprehensive reporting, and our Global Anti-Fraud Network to make faster, smarter decisions on the spot.

Testimonials

Real Success From Real Teams

Fraud.net’s flexibility has helped our AfterPay business grow by allowing us to meet our increasingly complex customer and country requirements. Their platform has enabled Arvato to increase our agility and significantly reduce fraud attacks.

Director Risk & Fraud, Arvato

FraudNet's combination of customized machine learning and flexible rules management has been transformative. We've achieved dramatic efficiency gains while maintaining robust fraud protection - a game-changer as we navigate evolving regulatory requirements.

Head of Financial Crime, Countingup

The great usability of Fraud.net is night and day when comparing it to our prior risk prevention platform. Reporting is also faster, more straightforward, and more impactful. With Fraud.net, we can easily visualize and share findings, providing our leadership with a clear understanding of the return-on-investment for our activities in real-time.

Fraud Manager, Global Financial Institution

Speak with our Solutions Expert Today

Thank you! Your submission has been received!
Oops! Something went wrong while submitting the form.
Recognized by Industry Analysts

Related Resources

FAQs

What is B2B payment AI risk scoring?

B2B payment AI risk scoring is a process that uses artificial intelligence to evaluate the risk associated with business-to-business transactions. It analyzes various data points such as transaction history, buyer and supplier profiles, and payment patterns to assign a risk score. This helps businesses quickly identify potentially fraudulent or risky transactions, enabling them to take preventative measures and ensure secure and efficient payment processes.

How does AI improve the accuracy of risk scoring in B2B payments?

AI enhances the accuracy of risk scoring by leveraging machine learning algorithms that can process vast amounts of data and identify patterns that may not be evident through traditional methods. AI systems continuously learn from new data, allowing them to adapt to emerging fraud tactics and refine their predictions over time. This results in more precise risk assessments, reducing false positives and negatives, and ultimately improving the reliability of risk management in B2B payments.

What data is typically used in AI risk scoring for B2B payments?

AI risk scoring for B2B payments typically uses a variety of data, including transaction amounts, frequency, and velocity, as well as historical payment patterns. It may also consider company size, industry, credit scores, supplier and buyer relationships, and external factors like economic indicators. By integrating these diverse data points, AI models can generate comprehensive risk profiles that provide valuable insights into the potential risks associated with each transaction.

What are the benefits of using AI for risk scoring in B2B payments?

Using AI for risk scoring in B2B payments offers numerous benefits, including enhanced fraud detection, improved efficiency, and reduced operational costs. AI can process large volumes of data faster than manual methods, enabling real-time risk assessment and quicker decision-making. It also reduces human error and bias, leading to more consistent and objective risk evaluations. Additionally, AI-driven insights can help businesses optimize their payment strategies and improve overall financial security.

How can businesses implement AI risk scoring in their payment systems?

Businesses can implement AI risk scoring in their payment systems by integrating AI-powered risk management platforms or solutions into their existing infrastructure. This involves selecting a suitable vendor, setting up data feeds, and configuring the AI model to align with their specific risk parameters and business objectives. It's important to ensure data privacy and compliance with relevant regulations during implementation. Regular monitoring and updates are also crucial to maintain the effectiveness of AI risk scoring over time.

What challenges might businesses face when adopting AI risk scoring for B2B payments?

Businesses may encounter several challenges when adopting AI risk scoring for B2B payments, such as data quality issues, integration complexities, and the need for skilled personnel to manage AI systems. Ensuring data privacy and compliance with legal regulations can also be challenging. Additionally, businesses need to be prepared for initial implementation costs and potential resistance to change from stakeholders. Overcoming these challenges requires careful planning, investment in training, and collaboration with experienced technology partners.