Best Fraud Detection and Real-Time Transaction Monitoring Solutions for Digital Banks and Fintechs in USA in 2025
Published: December 5, 2025 | Verified by: Ted Scheiman & Rob Watts
Executive Summary
We analyzed 4 solutions. Top Recommendation: Enterprise Risk Management Platform by FraudNet scored highest due to Unified orchestration across payments lifecycle with a no-code rules engine and enhanced detection of deepfake and synthetic identity fraud, providing broad risk visibility across digital payments and BaaS onboarding..
Content Verification
Side-by-Side Comparison
| Feature | #1 Enterprise Risk Management Platform (FraudNet) | #2 RiskOps (Feedzai) | #3 OrboAnywhere Platform (Featurespace) | #4 Alessa Transaction Monitoring Platform (Alessa) |
|---|---|---|---|---|
| Best For | Unified orchestration across payments lifecycle with a no-code rules engine and enhanced detection of deepfake and synthetic identity fraud, providing broad risk visibility across digital payments and BaaS onboarding. | Integration of fraud and AML detection in a single platform enabling comprehensive risk management with built-in compliance reporting and customer profiling. | Uses advanced AI technologies including image forensics and behavioral analytics to reduce fraud losses by over 90% and decrease false alerts by 35%, enabling more efficient fraud capture. | API-first architecture enabling continuous risk updates and real-time party screening across multiple transaction types for immediate interdiction of suspicious activities. |
| Detection Accuracy & False Positives | Accuracy: “Unmatched accuracy” claimed; no numeric accuracy disclosed. False positives: up to 98% reduction for acquirers; multiple pages cite 97% fewer false positives; AWS reports customers see ~92% average reduction. (fraud.net) (fraud.net) (fraud.net) (aws.amazon.com) | Reported results: 62% more fraud detected and 73% fewer false positives vs a previous solution (Tier 1 bank), according to Feedzai’s RiskOps page. (feedzai.com) | Reports up to 95%+ detection for counterfeit, forgery and alteration; typical ~90% with v5.1, and Sherlock 5.3 targeting ~95%. Vendor notes reduced false positives via 5.0 negotiability-test improvements and a Featurespace integration; no published false‑positive rate. (businesswire.com) (globenewswire.com) | Alessa reports fewer false positives from its transaction monitoring. (alessa.com) Claims include: up to 50% reduction in sanctions/PEP screening false positives via its PEP Scoring Model, plus 70% fewer alerts and an 80% increase in alert accuracy (with 60% efficiency gains) reported by users. (alessa.com) |
| Real-time Latency & Throughput | Latency: Real-time transaction scoring evaluates payments in under 300 ms. (fraud.net) Throughput: Platform processes thousands of transactions per second (via AWS serverless scale). (aws.amazon.com) | Real-time latency: ~3 ms per transaction; throughput: >3, 000 payments/events per second. (feedzai.com) | Turbo 6.0: recognition latency cut up to 70%, with sub‑100ms real‑time API responses. (orbograph.com) Throughput: nearly 10, 000 documents/minute on a single NVIDIA A100 GPU; most modules achieve 2, 4× speedups vs v5.3. (orbograph.com) Designed for low‑latency real‑time fraud scoring (Anywhere Fraud). (orbograph.com) | Real-time transaction monitoring and screening with instant results at payment time; enables immediate interdiction. (alessa.com) Scales to higher transaction volumes across payment rails. (alessa.com) |
| Integration, APIs & Reporting | Low‑code, RESTful APIs and webhooks deliver millisecond scoring, unified data fusion, and integration in hours with 99.99% uptime. (fraud.net) Unified dashboards/case management centralize alerts, rules, and workflows; reporting includes one‑click/instant exports, audit trails, and PCI/PSD2/AML/Reg E files. (fraud.net) | Integrates via REST/ISO 20022; unified data connectors support API, bulk file, and streaming ingestion; real-time standardized REST endpoints for production APIs; data-agnostic connectivity to watchlists (Acuris, Dow Jones, LSEG, Kharon, SWIFT) via Neterium; full audit trails; intelligent dashboards and reporting tools. (feedzai.com) | Web-services APIs (async/sync) enable multi-workflow, real-time or batch processing; scalable on-prem, virtual or cloud. Integrates via C#, .NET, Java and secure FTP. (orbograph.com) Outputs include validation results and fraud risk scores (incl. consortium data) returned to fraud platforms; IQA/classification support downstream processing and reporting; new releases add low-latency real-time API calls and rules/profile tools. (orbograph.com) | - Integration: Integrates with existing/legacy systems and best‑in‑class partners (sanctions, PEPs, crypto, IDV). (alessa.com) - APIs: APIs enable real‑time identity verification and watchlist screening during onboarding. (alessa.com) - Reporting: Auto‑populates, validates, and e‑files SAR/CTR/STR/LCTR across jurisdictions with dashboards/audit trails; automates 70, 100% of reports. (alessa.com) |
Enterprise Risk Management Platform
FraudNetCompany Information
"Best-in-Class AI Solutions for Fraud, Risk and Compliance"
Description
Fraud.net is an enterprise fraud and risk platform that delivers cutting-edge AI-driven solutions for detecting and preventing fraud across various sectors.
What They Do
Fraud.net provides a unified fraud detection and risk management platform powered by AI, supporting clients in handling fraud across multiple industries and transaction types.
Who They Serve
They serve a wide range of industries including payments, financial services, fintechs, and commerce.
Key Value Propositions
Target Customers
Industries Served
Contact Information
Navigation Links
Summary
FraudNet's Enterprise Risk Management Platform offers real-time, adaptive solutions for fraud detection, risk management, and compliance. Built for the unique needs of financial institutions and global commerce, it leverages advanced AI, machine learning, and a global anti-fraud network to deliver clarity and control over risk operations.
Best For
Financial institutions, Global commerce brands, Payments processors & PSPs, P2P, B2B, Cross Border payment providers, Acquirers and issuers, Banks (global, regional, community), Credit unions, Neo banks, Banking-as-a-Service (BaaS) providers, Fintechs (BNPL, Embedded Finance, Digital Payments, Lending), E-commerce, Retail, Travel, Marketplaces, Gaming
Key Features
- AI & Machine Learning (custom models, supervised learning, anomaly detection, graph neural networks, generative AI)
- Data Orchestration and Enrichment
- Global Anti-Fraud Network (collaborative insights across industries)
- Entity Screening (onboarding risk assessment)
- Entity Monitoring (ongoing, automated risk detection)
- Transaction Monitoring (real-time, AI-powered protection)
- Intelligent Risk Decisioning (robust rules, transparent scoring)
- Case Management & Reporting (modernized investigations)
- Advanced Analytics (real-time, data-driven insights)
- Learning Loop (continuous improvement of detection models)
Key Benefits
- Minimize risks and fraud losses
- Reduce false positives (proven 92% reduction in case study)
- Improve operational efficiency (30% cut in review times)
- Automate tasks and enable faster resolutions
- Boost revenue growth by isolating fraud and increasing approvals
- Streamline compliance and audits
- Protect customer trust and brand reputation
- Adapt to evolving regulations and business needs
Who Is It For
- Financial institutions
- Global commerce brands
- Payments processors & PSPs
- P2P, B2B, Cross Border payment providers
- Acquirers and issuers
- Banks (global, regional, community)
- Credit unions
- Neo banks
- Banking-as-a-Service (BaaS) providers
- Fintechs (BNPL, Embedded Finance, Digital Payments, Lending)
- E-commerce
- Retail
- Travel
- Marketplaces
- Gaming
Use Cases
- Regulatory compliance (AML, KYC, KYB, compliance reporting)
- Fraud detection and prevention (account takeovers, identity theft, payment fraud, chargebacks)
- Operational efficiency (resource allocation, process simplification, cost reduction)
- Reputation and trust (consumer privacy, data protection, brand integrity)
Geographic Availability
Resources
Supporting Resources
Detailed Comparison
Detection Accuracy & False Positives
Real-time Latency & Throughput
Integration, APIs & Reporting
FeedzaiCompany Information
"The AI Fraud and Financial Crime Prevention Platform You Can Trust"
Description
Feedzai gives banks the intelligence to block fraud, scams, mules, and money laundering in real time without adding friction for customers. The end-to-end platform covers the entire financial crime lifecycle, from account opening to fraud prevention to AML compliance.
What They Do
Fraud and financial crime prevention through AI-driven solutions.
Who They Serve
Banks, payment service providers, and government agencies.
Key Value Propositions
Target Customers
Industries Served
Contact Information
Navigation Links
Summary
RiskOps is the world’s first unified risk operations platform, designed to synthesize all available risk signals and data to detect and prevent fraud, identity theft, and financial crime. It leverages advanced AI, machine learning, and behavioral analytics to provide real-time, omnichannel risk analysis and case management, supporting compliance and reducing operational silos.
Best For
Retail Banks, Merchant Acquirers, Payment Service Providers, Corporate Commercial Banks, Core Banking Providers, Government
Key Features
- Behavioral biometrics, device intelligence, and malware detection for identity verification
- Real-time fraud detection using advanced machine learning and behavioral analytics
- Automated risk profiling, watchlist screening, transaction monitoring, and SAR filing for AML
- 360-degree view of customer risk by integrating demographic, behavioral, and transactional data
- AI-native risk decisioning with explainability, fairness, and governance safeguards
- Omnichannel Case Manager for unified alert and case management
- Intelligent dashboards and reporting tools for actionable insights
- Cloud-based platform capable of analyzing over 3000 payments per second
- Collaborative user experience for cross-team workflows
Key Benefits
- Unified platform for fraud, identity, and AML management
- End-to-end protection across the customer lifecycle
- Real-time, omnichannel risk analysis and detection
- Reduces false positives and operational time to resolution
- Accelerates team onboarding with a single system
- Cloud-native scalability and proven performance at scale
- Ensures regulatory compliance and data privacy
- Boosts efficiency and speeds up decision-making
- Enables collaboration across risk, fraud, and compliance teams
Who Is It For
- Retail Banks
- Merchant Acquirers
- Payment Service Providers
- Corporate Commercial Banks
- Core Banking Providers
- Government
Use Cases
- Account opening and onboarding fraud prevention
- New account fraud detection
- Account monitoring for suspicious activity
- Transaction fraud detection
- Scam prevention
- Merchant acquiring risk management
- KYC (Know Your Customer) and CDD (Customer Due Diligence)
- AML transaction monitoring
- Watchlist screening
Geographic Availability
RiskOps Platform
Feedzai’s RiskOps platform delivers a unified approach to fight fraud and financial crime across the entire customer lifecycle.
Achieve End-to-End Protection from Fraud and Financial Crime
RiskOps provides protection across Identity, Fraud, and Anti-Money Laundering, integrating solutions for each area.
- Identity: Securely recognize and verify customers using behavioral biometrics, device intelligence, and malware detection.
- Fraud: Real-time, omnichannel risk analysis using advanced machine learning and behavioral analytics.
- Anti-Money Laundering: Automated risk profiling, watchlist screening, transaction monitoring, and SAR filing.
RiskOps Outperforms Other Approaches
RiskOps delivers significant improvements in fraud detection, reduction of false positives, and speed of model deployment.
- 62% more fraud detected
- 73% fewer false positives
- 25x faster model deployment
A 360 Degree View of Risk
Synthesizes all available data to build a complete risk profile for each customer, integrating demographic, behavioral, and transactional data.
AI Innovation that Improves Performance and Reduces Costs
AI-based approach ensures accuracy, speed, fairness, explainability, and governance, supporting compliance.
A Unified, Collaborative Approach
Single, collaborative user experience for all teams to manage risk across the lifecycle, eliminating silos and enabling real-time sharing of insights.
Omnichannel Case Manager
Unifies risk operations across channels, enhancing detection strategies and investigator effectiveness.
Actionable Insights
Intelligent dashboards and reporting tools provide real customer intelligence to identify threats and business opportunities.
Trusted Performance
Proven scalability and performance, with real-time analysis of over 3000 payments per second and protection of over $6B in transactions annually.
Frequently Asked Questions
Answers to common questions about how RiskOps works, its key aspects, benefits, and why to choose Feedzai.
Resources
Detailed Comparison
Detection Accuracy & False Positives
Real-time Latency & Throughput
Integration, APIs & Reporting
OrboAnywhere Platform
FeaturespaceCompany Information
"Innovating Payments: Automation and Fraud Detection"
Description
OrboGraph is a leading provider of AI-based fraud detection and check processing automation solutions for the banking and payments industry. With over 30 years of experience, we deliver targeted solutions that enhance the efficiency and accuracy of financial transactions.
What They Do
OrboGraph specializes in AI-driven solutions for fraud detection and check processing automation.
Who They Serve
The banking and payments industry.
Key Value Propositions
Target Customers
Industries Served
Contact Information
Key Pages
Summary
OrboAnywhere Platform modernizes check processing and fraud prevention for financial institutions by utilizing AI, self-learning, and deep learning technologies. It automates check recognition, payment negotiability testing, fraud detection, and compliance, supporting teller, branch, mobile, RDC, archive, lockbox, and ATM image capture.
Best For
Financial institutions, Banks, Vendors serving the banking industry, Organizations processing paper checks
Key Features
- AI and deep learning-based check recognition
- Field detection using neural networks for precise field location
- Text classification for automated data extraction
- Interpretation and normalization of recognition scores using decision-tree models
- Modules for recognition, validation, and compliance
- Support for CAR (Courtesy Amount Recognition), LAR (Legal Amount Recognition), and MICR (Magnetic Ink Character Recognition)
- Integration of OrbNet AI technology
Key Benefits
- Modernizes legacy check systems
- Delivers 99%+ read rates and 99.5%+ accuracy on checks
- Reduces manual entry errors and operational costs
- Mitigates risk of fraud and compliance violations
- Streamlines deposit review and check processing workflows
- Supports omnichannel check image capture
Who Is It For
- Financial institutions
- Banks
- Vendors serving the banking industry
- Organizations processing paper checks
Use Cases
- Automated check recognition and data extraction
- Fraud detection for on-us and deposit checks
- Payment negotiability validation
- Regulatory compliance (OFAC, BSA/AML, UCC, Reg CC, KYC)
- Reducing posting errors and protecting against deposit fraud
Modernization of Legacy Check Systems
Financial institutions are modernizing legacy check systems to improve check processing and fraud prevention. AI, machine learning, and deep learning-based systems provide stronger automation, payment negotiability testing, fraud detection, compliance, and behavioral analysis.
- Improves teller, branch, mobile, RDC, archive, lockbox, and ATM image capture
- Justifies continued investment in check processing
Check Processing Terminology and Components
Explains the basics of check processing: CAR, LAR, and MICR, and their importance in automated check recognition.
- CAR: Automated recognition of the numerical amount on checks
- LAR: Reading the legal line for written amounts
- MICR: Reading bank routing, account, and check serial numbers using magnetic ink
Legacy Check Recognition Limitations
Legacy systems rely on traditional algorithms and OCR/ICR, resulting in lower performance and higher error rates.
- CAR/LAR performance: 75%-85%
- Error rates: 2-4%
- Difficulties with field location and handwritten fields
Check Recognition: AI-based Deep Learning Models
Describes how OrboAnywhere uses deep learning for field detection, text classification, and interpretation to automate and improve check recognition.
- Field detection using object detection neural networks
- Text classification with NLP and deep learning
- Interpretation and normalization of recognition scores
OrboAnywhere Check Automation Modules
Overview of the main modules: Anywhere Recognition, Anywhere Validate, and Anywhere Compliance.
- Anywhere Recognition: High-accuracy check reading
- Anywhere Validate: Payment negotiability validation
- Anywhere Compliance: Risk mitigation for regulatory compliance
Resources
Supporting Resources
Detailed Comparison
Detection Accuracy & False Positives
Real-time Latency & Throughput
Integration, APIs & Reporting
Alessa Transaction Monitoring Platform
AlessaCompany Information
"AML Compliance and Fraud Management Software"
Description
Alessa provides a comprehensive solution for Compliance professionals, focusing on Anti-Money Laundering (AML) compliance and fraud management. Their platform helps organizations reduce risks, streamline compliance processes, and ensure adherence to regulatory requirements while automating reporting functions.
What They Do
Provide AML compliance and fraud management software solutions to various industries.
Who They Serve
Banks, credit unions, fintech companies, casinos and gaming, lending and financing organizations, money service businesses (MSBs), cryptocurrency firms, insurance companies, payments companies, and non-financial organizations.
Key Value Propositions
Target Customers
Industries Served
Contact Information
Navigation Links
Summary
Transaction monitoring solution offering real-time, periodic, and event-based monitoring with machine-learning and rules-based analytics for financial institutions, fintechs, and MSBs to detect money laundering and fraud.
Key Features
- API-first architecture enabling continuous risk updates and real-time party screening across multiple transaction types for immediate interdiction of suspicious activities.
Detailed Comparison
Detection Accuracy & False Positives
Real-time Latency & Throughput
Integration, APIs & Reporting
Our Ranking Methodology
How we rank these offerings
We ranked these fraud detection and real-time transaction monitoring solutions for digital banks and fintechs in USA based on three key factors: Detection Accuracy & False Positives (40% weight), Real-time Latency & Throughput (35% weight), and Integration, APIs & Reporting (25% weight). The Enterprise Risk Management Platform scored highest due to its claimed unmatched accuracy, significant reduction in false positives, robust real-time capabilities, and comprehensive integration options. RiskOps followed closely with impressive accuracy improvements and state-of-the-art real-time transaction processing. OrboAnywhere Platform led in specific use-cases like check processing with solid detection rates but lagged in overall versatility. Alessa scored well in reducing false positives but showed comparatively lesser performance across other criteria.
Ranking Criteria Weights:
Frequently Asked Questions
- What are the typical costs and pricing models for fraud detection and transaction monitoring solutions in digital banking?
- Pricing models in this space often include tiered offerings based on transaction volume and feature set, with some solutions like FraudNet’s Enterprise Risk Management Platform offering adaptive costs based on real-time usage and analysis needs. Subscription-based models are common, typically including setup fees for integration, which can vary based on the complexity and customization. For instance, OrboAnywhere Platform automates multiple touchpoints such as teller and ATM, often reflecting in customized pricing depending on the institutional scale and specific needs addressed.
- What are the key selection criteria for fraud detection and transaction monitoring platforms?
- Critical selection criteria include the technology's ability to provide real-time analysis, integration capabilities with existing systems, and the breadth of risk data synthesis. Platforms like RiskOps, with its unified risk operations capability and omnichannel analysis, emphasize these features. Additionally, adaptability to regulatory changes, as seen with solutions like Alessa that offers both machine-learning and rules-based analytics to detect money laundering and fraud, is crucial for compliance and operational efficiency.
- What industry standards and compliance requirements must these solutions meet?
- Solutions must adhere to regulatory frameworks such as the Bank Secrecy Act, AML, and Know Your Customer (KYC) requirements in the USA. Platforms like Alessa are built to ensure compliance through real-time and event-based monitoring. Moreover, the global anti-fraud network leveraged by FraudNet's Enterprise Risk Management supports financial institutions in meeting both local and international compliance standards.
- What are some common implementation challenges faced with these solutions, and how can they be mitigated?
- Implementation challenges include integration with legacy systems, data privacy concerns, and user adaptation. Solutions like OrboAnywhere mitigate these issues by offering modular features that can gradually modernize check processing while using AI for seamless integration. Additionally, the self-learning aspect reduces manual intervention, thus easing the transition process for financial institutions.
- How do these platforms deliver ROI and value to digital banks and fintechs?
- These platforms deliver ROI through enhanced fraud detection accuracy, reduced false positives, and improved compliance, which cumulatively lower operational costs. For example, by using advanced AI and machine learning, FraudNet enables institutions to optimize risk management processes, potentially leading to a reduction in fraud-related losses. Platforms like RiskOps integrate risk data across channels, which enhances decision-making speed and reduces the burden of compliance, thereby improving operational efficiency.
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