About Ravelin Enterprise
Ravelin Enterprise is a fraud detection software from Ravelin Technology that helps businesses mitigate risks associated with online transactions. It combines machine learning, advanced analytics, and customizable rules so organizations can identify and prevent fraudulent activities effectively. The software provides real-time insights and detailed reporting to inform decision-making and improve overall security posture. Additionally, it supports multiple payment methods and integrates with existing systems for better functionality. Key capabilities: machine learning algorithms real-time transaction monitoring customizable fraud rules detailed reporting integration with payment gateways Best for: e-commerce businesses that need to secure online transactions and reduce fraud losses.
Ravelin is an AI-native fraud and abuse prevention platform for online merchants, securing the entire customer journey against payment fraud, refund abuse, ATO, and promo abuse. Its core strength lies in its sophisticated technology: custom machine learning models, 100% optimized to client KPIs, and the Graph Network (Connect). This network uses consortium data from over nine billion identity elements to visually identify complex fraud rings and multi-accounting in real-time, delivering superior accuracy and multi-layered defense against evolving threats. The platform is deployed as a Cloud, SaaS, and Web-Based solution, integrating via API to ensure high performance and low latency. It executes real-time risk decisions in milliseconds, crucial for a seamless customer experience. The user interface is highly intuitive, featuring automated consoles and powerful tools for analysts. Support is robust, described as a "Proactive Partnership" with dedicated Data Science, Integration, and Product Support teams, offering continuous optimization and strategic guidance. Ravelin primarily serves high-volume e-commerce, travel, and delivery sectors. Pricing is a premium, subscription-based model with no free version, though initial reports suggest costs start around $1,300 per feature monthly.
Pros & Cons
- +Tailored ML models increase accuracy and reduce false positives for each merchant’s unique fraud profile.
- +Consortium data enables detection of repeat fraud across merchants, improving prevention effectiveness.
- +Graph network link analysis uncovers sophisticated fraud patterns that traditional systems may miss.
- +Coverage of multiple abuse vectors (payments, refunds, promo, marketplace) means a broader defence solution.
- +PSP‑agnostic 3D Secure and transaction optimization helps balance security with higher conversion rates.
- −Custom ML and tailored setups may require ongoing adjustment and may not suit businesses with minimal fraud data.
- −May be over‑engineered for simple use‑cases or smaller merchants with low fraud risk, leading to under‑utilisation.
- −The complexity of features may require dedicated fraud/risk teams to get full benefit, raising staffing burden.
- −For markets or regions with weaker local data representation the effectiveness of consortium intelligence may be less optimal.
- −Multi‑vector coverage means the vendor must support many modules; if one module under‑performs it could affect overall trust.
Features
Key features
- Custom machine learning models
- Merchant‑specific AI models tuned to each business’s fraud challenges and KPIs.
- Consortium data database
- A network database of over 9 billion identity elements enabling cross‑merchant fraud intelligence and repeat‑fraud detection.
- Graph network link analysis
- Real‑time visual graph analysis to uncover hidden connections between customers, accounts, devices and transactions.
- PSP‑agnostic 3D Secure & SCA optimization
- A unified authentication and routing strategy for 3D Secure, strong customer authentication (SCA) and transaction optimization regardless of payment service provider.
- Online payment fraud prevention
- Automated risk decisioning across payment methods designed to block emerging fraud, reduce chargebacks and increase acceptance rates.
- Refund/returns abuse protection
- Tools to accurately separate legitimate returns from abuse, enabling returns for good customers while blocking fraudsters and opportunists.
- Account security & account take‑over (ATO) protection
- Purpose‑built ML to stop account takeovers, prevent multi‑accounting and secure login + checkout journeys.
- Promo, policy & voucher abuse control
- Ability to monitor and limit promotional offer redemption, detect abuse of vouchers or marketing investments and protect acquisition cost.
- Supplier, partner & marketplace fraud detection
- Detection and prevention of fraud originating via suppliers, partners or marketplace participants to safeguard the bottom line.
- Dashboard, rules engine, analytics & reporting
- Comprehensive tooling for fraud teams including rule configuration, analytics, reporting and actionable insights.
Additional features
- Online payment fraud prevention and chargeback reduction
- Automated risk decisioning for all payment methods to accept more payments securely.
- Refund/returns abuse protection
- Differentiating acceptable returns from abuse and enabling smart refund decisions.
- Account security & ATO protection
- Preventing account take‑overs, multi‑accounting and safeguarding user journeys at login and checkout.
- Promo, policy & voucher abuse control
- Monitoring and limiting abuse of sales, vouchers, offers and marketing investments.
- Supplier/partner/marketplace fraud detection
- Identifying fraud in marketplace or supplier‑partner contexts to protect business ecosystems.
- 3D Secure, SCA & transaction optimization
- Managing authentication strategy, dynamic routing and issuer intelligence to maximise approvals.
- Custom machine learning models
- Tailored AI/ML models optimized for each merchant’s fraud profile and KPIs.
- Consortium data of identity elements
- Access to large anonymised identity network for cross‑merchant fraud intelligence.
- Graph network link analysis
- Real‑time link‑analysis generating insights into relationships between entities (accounts, devices, identities).
- Rule engine, dashboard, analytics and reporting
- Full suite of tools for configuring fraud logic, monitoring performance, extracting insights and operational decision‑making.
Pricing
Countries & Languages
Interface languages
Billing currencies
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About Ravelin Enterprise
Ravelin Enterprise is a fraud detection software from Ravelin Technology that helps businesses mitigate risks associated with online transactions. It combines machine learning, advanced analytics, and customizable rules so organizations can identify and prevent fraudulent activities effectively. The software provides real-time insights and detailed reporting to inform decision-making and improve overall security posture. Additionally, it supports multiple payment methods and integrates with existing systems for better functionality. Key capabilities: machine learning algorithms real-time transaction monitoring customizable fraud rules detailed reporting integration with payment gateways Best for: e-commerce businesses that need to secure online transactions and reduce fraud losses.
Ravelin Enterprise Details
Ravelin Enterprise's In-App Market Place
Does Ravelin Enterprise have an in-app market place?
Yes
How many Mini-Apps in the marketplace?
1
Mini Apps
N/A
Pricing Options
Accepted Payment Currencies
USD ($), EUR (€), GBP (£), AUD ($), CAD ($), JPY (¥), CNY (¥), INR (₹), RUB (₽)
Pros & Cons
- Tailored ML models increase accuracy and reduce false positives for each merchant’s unique fraud profile.
- Consortium data enables detection of repeat fraud across merchants, improving prevention effectiveness.
- Graph network link analysis uncovers sophisticated fraud patterns that traditional systems may miss.
- Coverage of multiple abuse vectors (payments, refunds, promo, marketplace) means a broader defence solution.
- PSP‑agnostic 3D Secure and transaction optimization helps balance security with higher conversion rates.
- Custom ML and tailored setups may require ongoing adjustment and may not suit businesses with minimal fraud data.
- May be over‑engineered for simple use‑cases or smaller merchants with low fraud risk, leading to under‑utilisation.
- The complexity of features may require dedicated fraud/risk teams to get full benefit, raising staffing burden.
- For markets or regions with weaker local data representation the effectiveness of consortium intelligence may be less optimal.
- Multi‑vector coverage means the vendor must support many modules; if one module under‑performs it could affect overall trust.
Ravelin Enterprise's Support Options
Email Address
eu.representative@ravelin.comDocumentation
https://developer.ravelin.com/psp/Ravelin Enterprise's Alternatives
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