Celebrating Industry Recognition as a Best in Class ML Vendor Simility
At Simility, we pride ourselves on leading a new era of machine learning-powered anti-fraud solutions. Since beginning this journey in 2014, we’ve come a long way in meeting the growing demands of our global business customers thanks to the tireless work of our dedicated team. So it’s with great delight that we’re able to share the findings of a new industry report from leading market analyst Aite Group, which places Simility as one of just three best-in-class fraud and AML machine learning (ML) vendors.
The Aite Impact Matrix (AIM) rates highly the completeness of our product offering, model performance, and Simility’s overall responsiveness and support capabilities. It’s fantastic to have such a highly regarded independent review of our offering in what is a fast-evolving and extremely competitive market. It sets us up strongly for the next stage of our journey as part of the PayPal family.
As the AIM report recognizes, ML-based fraud prevention has evolved out of a growing need to combat rising levels of cyber-crime. Card not present (CNP) fraud losses in retail alone are predicted to reach $130 billion between 2018 and 2023, according to Juniper Research.1 Fraudsters are leveraging huge troves of readily available breached data to use in attacks, often in combination with automated bots and anonymizing tools. The result for many financial institutions and retailers is a stark choice: absorb more fraud losses or add customer friction to the process.
Fortunately, it doesn’t need to be this way. Our mission over the past four years has been to stay one step ahead of advances in fraud techniques. Technological innovation has enabled faster and more effective predictive analytics, with costs coming down and scalability improving. Regulators are also encouraging financial firms in particular to embrace more advanced detection tools like those offered by Simility.
Market leading ML
Aite Group’s comprehensive analysis recognizes these giant strides we’ve made in keeping our customers insulated from the global rise in fraud. In particular, it highlights the strengths of our:
- Collaborative approach to implementation and support
- Embedded device identity capability
- Data handling
It’s only natural that data sits at the heart of the Simility approach. We combine huge volumes of information from structured and unstructured sources to provide the most accurate real-time results.
Our clear box approach to ML is also key. We automatically generate ML models based on the data and the fraud prevention goal. However, customers are able to view a list of features selected by each model to compare them side-by-side and better understand why a particular model was chosen. This kind of “explainability” empowers fraud teams with deeper insight into fraud decision making and can drive a more optimized approach overall.
We work hard to give in-house risk teams all the tools they need to be as effective as possible, enhancing their expertise with ML rather than replacing it. This includes a turnkey approach for quick deployment of state-of-the-art ML models. But we also recognize that sometimes they need extra support. That’s why our world-class team of data scientists is also on standby 24/7 to provide data-science-as-a-service to help keep customers on the front foot in the fight against fraud.
The next stage
As we come up to five years at Simility, it’s been a fantastic journey so far. Our customers’ success is the ultimate success for all of us here, so it’s a delight to see some of their glowing reviews cited by Aite Group. “Flexibility,” “responsiveness” and a “collaborative approach” all stand out, while one firm described Simility as “a true partner, not just a vendor.”
However, this is just the beginning. As Aite Group reveals, we have plenty to keep us busy including planned ML enhancements such as automated feature generation to speed time-to-deployment for customers. There’s also work to do to keep pace with rapid market changes, including authorized push payment fraud in the UK and Know Your Customer checks. We’ll also be continuing integration work with PayPal and Braintree which will ultimately benefit our collective customer base across the globe.
1. Juniper Research, https://www.juniperresearch.com/researchstore/fintech-payments/online-payment-fraud
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