SWIFT Announces Semi-Finalists for its Global FinTech Innovation Challenge 2015

We’re excited to announce that Jewel Paymentech has been selected as a semi-finalist in this year’s Innotribe Global FinTech Startup Challenge 2015!

This is certainly a recognition of the technology embedded within One Sentry™ – the industry’s first fully automated tool that enables banks and payment facilitators to effectively manage their merchant’s brand, fraud, credit and data security risk.

Click here to read the full press-release

About Innotribe
Launched in 2009, SWIFT Innotribe is about innovation and connecting people, networks and ideas. We bring together global innovators and investors, strategists, and influential decision-makers from leading financial institutions across the globe, providing them early insights into innovations that could disrupt current business models and create new opportunities for new ones. Through the Startup Challenge competition, we bridge the gap between the startup ecosystem and the financial service community.

SWIFT is a member-owned cooperative that provides the communications platform, products and services to connect more than 10,800 banking organisations, securities institutions and corporate customers in more than 200 countries and territories. SWIFT enables its users to exchange automated, standardised financial information securely and reliably, thereby lowering costs, reducing operational risk and eliminating operational inefficiencies. SWIFT also brings the financial community together to work collaboratively to shape market practice, define standards and debate issues of mutual interest.

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19 Mar / 2015

One Sentry’s Predictive Analytics

Our predictive modeling web heuristics research technology is currently used as part of our One Sentry Merchant Risk Monitor product to identify potentially bad merchant websites. This technology allows us to predict possible bad merchants without needing to rely on retroactive knowledge.

Our analytics is based on a propreitary algorithm that uses both Naive Bayes classifier and Random Forest models to derive results. A 5-step methodological approach is employed to analyse any given content in order to predict an outcome.

  • Collection
  • Content Analysis
  • DB Checks
  • Scoring
  • Re-learn

Site Scraping (Web Crawler) tech is completely developed in-house and is built using a dynamic parsing platform allowing distributed collection of information. We also use a self-developed processing engine to combat “anti-bot” mechanisms.

OS - Herustics Engine 1


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02 Mar / 2015