AI-Powered Fraud Detection for FinTech: Secure Transactions, Stop Financial Crime
Move beyond outdated rules. We build and deploy intelligent, self-learning AI systems that detect and prevent sophisticated fraud in real-time—protecting your revenue and reputation.
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The Silent Threat Costing You Millions
In the fast-paced world of FinTech, fraud isn't just a nuisance; it's an existential threat. Sophisticated criminals are constantly evolving, exploiting weaknesses in traditional, rule-based systems. These outdated methods lead to mounting financial losses, damage your hard-won customer trust, and bury your team in a sea of false positives. You're not just losing money to fraud; you're losing legitimate customers frustrated by blocked transactions and wasting valuable operational resources on manual reviews. It's time to shift from a reactive defense to a proactive, intelligent offense.
Why Partner with Errna for AI Fraud Detection?
We don't just provide algorithms; we deliver business outcomes. Our expertise sits at the intersection of advanced AI, financial services, and enterprise-grade software engineering, ensuring your fraud detection system is not only intelligent but also compliant, scalable, and seamlessly integrated.
Explainable AI (XAI)
Our models aren't "black boxes." We build transparent AI systems using frameworks like SHAP and LIME, providing clear, human-readable justifications for every decision. This ensures you can meet strict regulatory requirements and build internal trust with your compliance teams.
Custom Model Development
Off-the-shelf solutions don't account for your unique data and business logic. We build bespoke machine learning models tailored to your specific transaction patterns, customer behaviors, and risk appetite, maximizing accuracy and minimizing false positives.
Rapid, Scalable Deployment
Time is critical. We leverage a mature, AI-augmented delivery process and robust MLOps practices to deploy your custom fraud detection engine quickly and efficiently. Our solutions are built on scalable cloud architecture to handle millions of transactions without breaking a sweat.
End-to-End Security Focus
With CMMI Level 5, ISO 27001, and SOC2 compliance, security is in our DNA. We implement security-by-design, including data anonymization and privacy-preserving techniques, to protect your most sensitive customer data throughout the AI lifecycle.
Deep FinTech Expertise
We speak your language. Our team includes experts with deep domain knowledge in payment processing, lending, AML regulations, and core banking systems. We understand the nuances of financial data and the regulatory landscape you operate in.
Proven ROI and Business Value
Our goal is to directly impact your bottom line. We work with you to establish clear KPIs and build a business case, demonstrating how our AI solutions reduce fraud losses, lower operational costs from manual reviews, and improve customer retention.
Seamless System Integration
A powerful model is useless if it doesn't integrate with your existing stack. Our experts design and build robust APIs for seamless integration with your core banking platforms, payment gateways, and case management systems for a frictionless workflow.
Continuous Model Improvement
Fraudsters never stop evolving, and neither should your defenses. We provide ongoing model monitoring, maintenance, and retraining services to ensure your AI system adapts to new threats and maintains peak performance over time.
Flexible Partnership Models
Whether you need to augment your existing data science team, require a dedicated AI development pod, or want a fully managed, project-based solution, we offer flexible engagement models that align with your budget, timeline, and strategic goals.
Our AI-Powered Fraud Detection Services
We offer a comprehensive suite of services to build and deploy a multi-layered defense against financial crime, tailored to the specific needs of the FinTech ecosystem.
Real-Time Transaction Monitoring
Analyze transactions as they happen to block fraudulent activity before funds are lost. Our high-performance models score millions of events in milliseconds.
- Detect anomalies in transaction amount, frequency, and location instantly.
- Utilize graph-based analysis to uncover hidden relationships between accounts.
- Scale to handle peak processing loads without compromising on speed or accuracy.
Account Takeover (ATO) Prevention
Protect your customers from unauthorized access. We use behavioral analytics and device intelligence to detect suspicious login attempts and account changes.
- Analyze login patterns, device fingerprints, and IP reputation to flag risks.
- Implement multi-factor authentication triggers based on real-time risk scores.
- Identify and block credential stuffing and brute-force attacks automatically.
Behavioral Biometrics Analysis
Go beyond passwords. Our AI analyzes how users interact with your platform—typing speed, mouse movements, and navigation patterns—to create a unique biometric profile and detect imposters.
- Provide continuous, passive authentication throughout a user's session.
- Detect remote access trojans and bot-driven activity with high precision.
- Add a powerful, frictionless layer of security without impacting user experience.
Payment Fraud Detection
Secure all major payment rails, including credit cards, ACH, and wire transfers. Our models are trained on vast datasets to identify even the most subtle indicators of payment fraud.
- Reduce chargebacks and false declines for card-not-present (CNP) transactions.
- Identify and flag suspicious patterns indicative of business email compromise (BEC).
- Protect against synthetic identity fraud in payment and credit applications.
Loan & Credit Application Fraud Analysis
Automate and enhance your underwriting process. Our AI scans applications in real-time to detect falsified information, synthetic identities, and other signs of credit fraud.
- Verify income, employment, and identity documents using OCR and data analysis.
- Cross-reference data points to identify inconsistencies and potential misrepresentation.
- Reduce default rates and manual review times for your underwriting team.
Insurance Claim Fraud Detection
Move from manual review to intelligent automation. Our AI analyzes claim data, adjuster notes, and third-party information to flag suspicious claims for further investigation.
- Identify organized fraud rings and collusive activities using network analysis.
- Use natural language processing (NLP) to extract insights from unstructured text.
- Prioritize high-risk claims, enabling your team to focus their efforts effectively.
AML Transaction Pattern Analysis
Enhance your Anti-Money Laundering program with AI. Our models detect complex money laundering typologies like structuring, smurfing, and layering that rule-based systems often miss.
- Reduce false positives, allowing your compliance team to focus on genuine threats.
- Generate automated narratives for Suspicious Activity Reports (SARs).
- Adapt to new and emerging money laundering techniques without manual rule updates.
AI-Powered KYC & Identity Verification
Streamline and secure your customer onboarding process. We use AI to automate document verification, perform biometric checks, and screen against sanctions lists with greater speed and accuracy.
- Extract and validate data from IDs, passports, and utility bills using OCR.
- Perform facial recognition and liveness checks to prevent spoofing.
- Reduce customer friction and abandonment rates during onboarding.
Regulatory Compliance Consulting
Navigate the complex regulatory landscape of using AI in finance. Our experts provide guidance on model governance, validation, and documentation to ensure you meet standards set by regulators.
- Develop comprehensive model risk management (MRM) frameworks.
- Prepare documentation for internal audits and regulatory inquiries.
- Ensure fairness and mitigate bias in your AI models.
Custom Machine Learning Model Development
Leverage our team of data scientists to build fraud detection models from the ground up, specifically designed for your business context and data ecosystem.
- Utilize a wide range of algorithms, from gradient boosting to deep neural networks.
- Incorporate both structured and unstructured data sources for a holistic view of risk.
- Own the intellectual property for the models we develop for you.
Explainable AI (XAI) & Model Auditing
Gain full transparency into your AI's decisions. We implement XAI techniques and conduct independent model audits to ensure fairness, accuracy, and regulatory compliance.
- Generate feature importance and reason codes for every prediction.
- Test for and mitigate algorithmic bias related to protected characteristics.
- Validate model performance against established benchmarks and business goals.
Fraud Analytics & Reporting Dashboards
Turn data into actionable intelligence. We build intuitive, real-time dashboards that provide a comprehensive view of fraud trends, model performance, and key risk indicators.
- Visualize fraud patterns geographically and over time.
- Track key metrics like false positive rates, detection rates, and ROI.
- Enable your team to drill down into specific alerts and investigations.
Data Anonymization & Privacy-Preserving AI
Protect sensitive customer data while still leveraging its predictive power. We implement advanced techniques like tokenization, differential privacy, and federated learning.
- Comply with data privacy regulations like GDPR and CCPA.
- Train models on decentralized data without exposing raw personal information.
- Minimize the risk associated with data breaches and unauthorized access.
System Integration & API Development
Ensure your AI fraud detection engine works seamlessly within your existing infrastructure. We develop robust, high-availability APIs for easy integration.
- Connect with core banking systems, payment gateways, and CRMs.
- Provide comprehensive documentation and developer support.
- Build for scalability and low latency to support real-time decisioning.
Model Maintenance & Retraining
Fraud patterns are constantly changing. We provide ongoing MLOps support to monitor for model drift and performance degradation, with automated retraining pipelines to keep your defenses sharp.
- Implement A/B testing and champion-challenger frameworks for new models.
- Ensure your models learn from the latest fraud trends and patterns.
- Maintain optimal performance and extend the lifecycle of your AI investment.
Our Proven 4-Step Delivery Process
We follow a structured, collaborative approach to ensure your AI fraud detection solution is delivered on time, on budget, and perfectly aligned with your business objectives.
Discovery & Strategy
We immerse ourselves in your business, identifying key fraud challenges, data sources, and technical requirements to define a clear project roadmap and success metrics.
Data Preparation & Feature Engineering
Our data scientists clean, aggregate, and transform your raw data into powerful predictive features, laying the foundation for a high-performing machine learning model.
Model Development & Validation
We train, test, and validate multiple custom models, selecting the optimal algorithm that balances accuracy, speed, and explainability for your specific use case.
Deployment & Integration
We deploy the validated model into your production environment via a scalable API and provide ongoing monitoring and support to ensure sustained performance and value.
Real-World Impact in FinTech
We don't just talk about AI; we deliver tangible results. See how we've helped FinTech companies like yours combat fraud, reduce costs, and secure their platforms.
Industry: Payment Processing
Reducing Chargebacks for a High-Growth Payment Gateway
Client Overview: A rapidly growing payment processor was struggling with rising chargeback rates from sophisticated card-not-present (CNP) fraud. Their existing rule-based system was generating too many false positives, frustrating legitimate merchants and customers, while still failing to catch new fraud patterns. They needed an intelligent solution that could adapt in real-time without hindering growth.
"Errna's AI solution was a game-changer. We not only cut our fraud losses significantly but also improved our customer experience by reducing false declines. Their team understood our business and delivered a solution that integrated perfectly with our platform."
- Jace Holloway, Chief Risk Officer, PaySecure Inc.
The Problem
The client's static fraud rules couldn't keep up with dynamic criminal tactics. This led to a vicious cycle: to fight new fraud, they would add more restrictive rules, which in turn increased the rate of falsely declined transactions, impacting revenue and merchant satisfaction. Their fraud team was overwhelmed with manual reviews, creating operational bottlenecks.
Key Challenges:
- High volume of CNP transactions needing real-time scoring.
- Inability of the existing system to detect synthetic identity fraud.
- Excessive manual reviews due to a high false positive rate.
- Negative impact on authorization rates and customer experience.
Our Solution
Errna developed and deployed a custom real-time fraud detection model using a gradient boosting algorithm. The solution was delivered as a low-latency API that integrated directly into the client's payment authorization flow.
- Engineered features based on transaction history, device fingerprinting, and behavioral data.
- Trained the model on the client's historical data, enriched with third-party sources.
- Implemented an XAI dashboard to provide fraud analysts with clear reasons for each risk score.
- Established an automated model retraining pipeline to adapt to evolving fraud patterns.
Industry: Digital Banking (Neobank)
Automating AML Compliance and Preventing Account Takeover
Client Overview: A leading neobank needed to strengthen its defenses against money laundering and account takeover (ATO) attacks to meet regulatory pressure and protect its growing user base. Their compliance team was struggling to keep up with the volume of alerts from their legacy transaction monitoring system, and customers were reporting an increase in unauthorized access.
"The team at Errna provided a level of expertise in both AI and banking regulations that we couldn't find elsewhere. They helped us automate our AML processes and significantly reduce our exposure to account takeover fraud, all while ensuring we remained compliant."
- Sophia Dalton, Head of Compliance, Finova Bank
The Problem
The neobank's existing AML system produced a high number of false positive alerts, consuming significant resources from their compliance team. Simultaneously, their ATO prevention relied on basic rules that were easily bypassed by fraudsters using stolen credentials, leading to financial losses and reputational damage.
Key Challenges:
- Overwhelming volume of false positive AML alerts.
- Difficulty in detecting sophisticated money laundering schemes like smurfing.
- Rising customer losses due to credential stuffing and phishing attacks.
- Need for a solution that could scale with a rapidly expanding customer base.
Our Solution
We implemented a two-pronged AI solution. First, an unsupervised learning model for AML that clustered user behavior to identify anomalous transaction patterns indicative of money laundering. Second, a supervised model for ATO prevention that analyzed login data, device information, and behavioral biometrics.
- Used anomaly detection to flag suspicious activity that deviated from a user's normal financial behavior.
- Developed a real-time risk scoring engine for every login and sensitive account action.
- Integrated the solution with the client's case management system to streamline investigations.
- Provided a full documentation package for model validation and regulatory review.
Industry: Online Lending
Detecting Application Fraud for a P2P Lending Platform
Client Overview: A peer-to-peer lending platform was experiencing increased default rates linked to fraudulent loan applications. Fraudsters were using a mix of stolen and synthetic identities to secure loans with no intention of repayment. The manual underwriting process was slow and unable to effectively vet the high volume of incoming applications.
"Errna built an AI-powered underwriting assistant that has become essential to our operations. It flags high-risk applications with incredible accuracy, allowing our team to focus on legitimate borrowers. Our default rates have dropped, and our approval process is faster than ever."
- Marcus Dyer, CEO, LendRight
The Problem
The platform's growth was being undermined by credit losses from fraudulent applications. The manual review process was not scalable and was inconsistent in its ability to spot the subtle signs of synthetic identity fraud, where criminals combine real and fake information to create a new identity.
Key Challenges:
- High credit losses due to first-party and third-party application fraud.
- Slow and labor-intensive manual underwriting process.
- Inability to detect patterns of organized fraud across multiple applications.
- Need to maintain a fast, frictionless experience for legitimate borrowers.
Our Solution
We developed a comprehensive application fraud solution that combined machine learning with data from alternative sources. The system analyzed application data, device information, digital footprints, and credit bureau data to generate a real-time fraud risk score for each applicant.
- Used NLP to analyze unstructured data and verify submitted documents.
- Implemented network analysis to identify links between seemingly unrelated applications.
- Created a "confidence score" for applicant identities to flag synthetic profiles.
- Delivered the solution as an API that integrated directly into their loan origination system.
Our Technology Stack & Tools
We leverage a modern, best-in-class technology stack to build high-performance, scalable, and reliable AI solutions for the FinTech industry.
What Our Clients Say
Our success is measured by the success of our clients. We are proud to be a trusted partner to FinTech innovators worldwide.
"The AI fraud detection system Errna built for us is years ahead of what we had. It adapts to new threats on its own, and the reduction in manual reviews has freed up my team to focus on more strategic initiatives."
"As a startup, we needed a partner who could move fast without compromising on quality or security. Errna delivered a robust, scalable solution that gives our investors and customers confidence in our platform."
"The explainability of the AI models was crucial for our regulatory reporting. Errna's team not only built a highly accurate system but also provided the transparency we needed to satisfy our auditors."
Meet Our FinTech AI Experts
Our team combines deep expertise in data science, cloud engineering, and financial services to deliver solutions that solve real-world problems.
Vishal N.
Manager, Certified Hyper Personalization Expert, Senior Data Scientist (AI/ML)
Prachi D.
Manager, Certified Cloud & IOT Solutions Expert, Expert in Artificial Intelligence Solutions
Akeel Q.
Manager, Certified Cloud Solutions Expert, Certified AI & Machine Learning Specialist
Joseph A.
Expert Cybersecurity & Software Engineering
Flexible Engagement Models
We offer a range of engagement models designed to fit your specific needs, whether you're a startup or a large enterprise.
Staff Augmentation
Integrate our expert AI engineers, data scientists, and MLOps specialists directly into your team to accelerate your project and fill critical skill gaps.
Managed AI Pods
Get a dedicated, cross-functional team of experts—including a project manager, data scientists, and engineers—to manage your AI project from end to end.
Project-Based Solutions
Define the scope, and we'll deliver a complete, turnkey AI fraud detection solution for a fixed price, with clearly defined milestones and deliverables.
Frequently Asked Questions
Rule-based systems are static; they can only catch fraud patterns that you explicitly define. They are brittle and quickly become outdated as fraudsters change their tactics. AI, specifically machine learning, learns from your data to identify complex, non-obvious patterns and adapts over time. It can detect novel fraud schemes that have never been seen before, significantly reducing both fraud losses and the number of false positives that frustrate legitimate customers.
This is a critical concern, and we address it head-on with Explainable AI (XAI). We use state-of-the-art techniques and frameworks (like SHAP and LIME) to provide clear, human-understandable reasons for every decision the model makes. For any transaction flagged as fraudulent, we can show exactly which factors contributed to that score. This transparency is essential for satisfying regulators, auditors, and internal compliance teams.
Typically, the most valuable data is your historical transaction data, including labels for which transactions were fraudulent (e.g., from chargeback reports). This includes information like transaction amount, timestamp, user ID, device information, IP address, and any available customer data. The more historical data you have, the more powerful the model will be. During our discovery phase, we work with you to identify and prepare all relevant data sources.
The timeline can vary depending on the complexity of the use case and the state of your data, but a typical project follows a phased approach. A proof-of-concept (POC) can often be completed in 4-6 weeks, demonstrating the potential value on your data. A full production deployment, including integration and testing, usually takes between 3 to 6 months. We prioritize a rapid time-to-value without sacrificing quality.
Security is our top priority. We are a CMMI Level 5, ISO 27001, and SOC2 compliant company. We follow security-by-design principles in all our development. For AI projects, we can implement advanced privacy-preserving techniques such as data anonymization, tokenization, and even federated learning, which allows us to train models without your sensitive raw data ever leaving your environment. All data is handled in secure, encrypted cloud environments.
Ready to Outsmart Fraud?
Stop reacting to financial crime and start preventing it. Schedule a free, no-obligation consultation with our AI experts to discover how a custom fraud detection solution can protect your platform, your customers, and your bottom line.