Fraud.net provides an AI-native platform for real-time fraud detection, anti-money laundering (AML), and risk management tailored for digital enterprises and fintechs. The platform enhances transaction security and customer trust by reducing fraud losses by up to 68% and lowering false positives by 78%, ensuring a seamless customer experience.
Funding
$5M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Digital enterprises and fintechs face increasing challenges in combating sophisticated fraud schemes, managing anti-money laundering (AML) compliance, and mitigating various financial risks. Traditional fraud detection systems often struggle to keep pace with evolving threats, resulting in significant financial losses and increased operational overhead. Furthermore, high false positive rates can lead to customer friction and lost revenue opportunities.
Solution
Fraud.net offers an AI-powered platform designed to provide end-to-end fraud detection, AML, and risk management solutions tailored for the real-time economy. The platform leverages machine learning and a global anti-fraud network to identify and prevent a wide range of fraudulent activities, including application fraud, transaction fraud, and account takeovers. By unifying fraud detection, compliance, and risk management into a single, customizable solution, Fraud.net enables businesses to streamline operations, reduce fraud losses, and improve customer experience. The platform's intelligent risk decisioning capabilities and advanced analytics provide real-time insights, allowing businesses to make faster, smarter decisions and adapt to evolving threats.
Target Audience
The primary target audience includes payments processors, financial institutions (global, regional, and community banks), fintech companies (BNPL, embedded finance, digital payments, lending), and e-commerce businesses.
Features
- AI & Machine Learning: Employs supervised machine learning, anomaly detection, graph neural networks, and generative AI for smart threat detection.
- Intelligent Risk Decisioning: Provides robust rules and transparent scoring for informed decision-making.
- Global Anti-Fraud Network: Leverages collaborative insights across industries to identify potential fraudsters.
- Data Hub: Offers seamless integrations and limitless options for data enrichment and orchestration.
- Case Management & Reporting: Modernizes and streamlines investigations with a unified view of relevant data.
- Data Orchestration: Unifies, enriches, and automates data flows for comprehensive risk management.
- Advanced Analytics: Delivers data-driven insights and real-time clarity through comprehensive reporting and analytics.
- Customizable and Scalable: No-code rules engine, flexible dashboards, and tailor-made machine learning models adapt to business needs.
- Entity Screening and Monitoring: Screens and monitors entities to proactively identify new risks.