Why Ravelin for payment providers?
Ravelin is a fraud detection company that uses Machine Learning models and other techniques to form a complete picture of a shopper’s risk profile before they check out. Ravelin provides real-time decisions so your merchants can accept payments confidently, protecting their margins while helping you to reduce fraud across your portfolio.
Make excellent fraud detection your USP
As the algorithm consumes more data and gets feedback on previous predictions, it becomes more accurate. Machine Learning techniques allow us to tackle problems that involve large volumes of data, adapting to shifting patterns of fraud. It is therefore ideally suited to managing fraud whilst ensuring that you can safely accept payments across your portfolio. If you operate within Europe, Machine Learning techniques can fulfil the requirements outlined under PSD2 for transaction risk analysis. In addition, this approach enables you to keep fraud rates at merchant and portfolio level below the Reference Fraud Rates. This means you can provide exemptions to SCA for payments, reducing friction for successful payments and the costs associated with challenging a transaction. Give your team the tools they need to effectively manage fraud across your portfolio, without compromising on your margins. Ravelin works with your company to configure the model and set risk thresholds, providing you with a solution appropriate to your business.
A frictionless experience for good users; a frustrating one for fraudsters.
Key benefits of machine learning
Put your data to work
Machine Learning models love large datasets. We extract all the data possible from the customer journey to build a highly accurate score and to comply with PSD2-level Transactional Risk Analysis requirements.
Approvals in real time
Machine Learning models enable you to let merchants know if a payment should be accepted or not, instantly. Our model returns results in milliseconds, supporting merchant conversion rates whilst protecting your margins.
Grow your portfolio
As your merchant profile grows and the volume of data increases, Machine Learning’s innate scalability allow you to avoid increasing operational costs in line with volume.
Get accurate predictions
Machine Learning models give you highly accurate decisions and outperform traditional rules based strategies, helping you to manage fraud across your portfolio effectively. Make the most of transaction risk analysis and reduce friction for legitimate payments.
Machine Learning techniques allow you to set thresholds that take into account required fraud rates, helping you comply with relevant business or legal requirements. This can be balanced with conversion rates for specific merchants and across a merchant portfolio.
A lot can happen in 800 ms
Data is sent to us via an API.
The data runs through our Machine Learning models and returns a score to indicate the probability that a customer is a fraudster.
Ravelin then returns a recommendation to allow, prevent or review the customer via the API.
Suspicious customers can either be challenged or declined automatically.
You can view all the relevant data and decisions in the Ravelin platform.
Read more about machine learning models, neural networks and risk scores here »
How machine learning
works at Ravelin
Tailored to your company’s needs
Providing a highly accurate prediction specific to your portfolio and business needs. This approach gives you a flexible solution, taking into account your acceptance strategy and your portfolio’s unique fraud pattern.
Comprehensive experience in fraud and risk management
This gives us a unique understanding of the challenges faced by payment facilitators and gateways. Our analysts, data scientists and engineers work closely with clients to make sure you get the most out of the integration and our Machine Learning models.
Payment Service Providers have complete oversight of their fraud risk across their entire portfolio via the Ravelin PSP platform.
Real time decision-making Optimise your margins
With real-time scoring and recommendations, you can accept payments confidently, optimise your margins and protect your company from fraudsters.
Analytics and reporting Maintain control
With our analytics dashboards your team can have complete oversight and control over your portfolio, providing crucial insights and facilitating reporting to regulatory bodies. Ravelin reports focus on fraud rate trends as well as performance of our solution.
Portfolio level rules Set boundaries
Effective portfolio rules provide important boundaries for Machine Learning models. Create rules on the Ravelin platform to ensure that relevant regulatory and business policies are taken into account at merchant and portfolio level.
The regulatory landscape for payment facilitators, gateways, and acquirers operating in Europe is shifting. With more emphasis on security and fraud mitigation combined with a shift in liability, PSD2 is changing the payments industry. Is your business ready? Our PSP platform was built with PSD2 requirements in mind.
Ravelin allows PSPs to switch into a merchant view to see more granular data at customer level if required. These merchant level accounts would have the same functionality as our Ravelin for Merchants product.
Read more about the impact of the PSD2 directive and 3D Secure here »
Ravelin analytics provides a comprehensive overview of fraud patterns for each merchant as well as across your entire portfolio. This gives you critical insight and oversight of opportunities and regulatory constraints and facilitates annual reporting to regulators, saving your team time.
With Ravelin’s PSP platform, it is possible to set strict thresholds to ensure that fraud rates for individual merchants as well as across your entire portfolio do not go above the Reference Fraud Rates. This means you can optimise management of exemptions to Strong Customer Authentication as part of your merchant offering.
Ravelin’s product gives PSPs the flexibility to apply rules at individual, group or portfolio level - allowing you to effectively manage a diverse portfolio.