Cybertonica uses machine learning to analyse consumer behaviour, transactions and reduce friction at point of sales whilst preventing fraud

Country: UKcybertonica

Year: 2016

Concept

  • Aimed at e-commerce and m-commerce merchants, payment service providers (PSPs) and financial institutions, Cybertonica is a cloud risk intelligence hub with SaaS solutions aiming to reduce online fraud, manage risk and revenue recovery as well as increasing transaction volume by reducing friction at the point of sale
  • Artificial intelligence is used to analyse data and transaction behaviour in real time, target fraudsters, map and isolate malware, and update a list of blacklisted cards and users to the client
  • For online retailers, devices and payments can be pre-screened, with Cybertonica removing the dependence on third party security verification such as 3DSecure
  • Over a couple of months, data is gathered from three key areas: biometrics (physical behaviour while browsing), browsing history and transaction history to create a smart risk rating which produces a risk-dependent range of security precautions
  • These precautions can be used to detect and prevent fraud. The company can also intervene for hacking or security breaches
  • Cybertonica will monetise by taking a small commission on transactions and plans to roll out the service in four countries: UK, Germany, Russia and Turkey

Consumer Benefits

  • Boost sales: and recover revenue through a fluid transaction process
  • Financial Assurance: 100% of chargebacks are covered
  • Reduce fraud: gathering evidence on illegal card operations, tracing compromised cards and uncovering fraudsters’ behaviour
  • Plug and play: SaaS solutions which are compliant with client companies’ existing payment architecture

How To Use

  • Currently unavailable on Cybertonica’s site, interested users can contact the company for a demo and pricing
  • Cybertonica has been testing its solutions with a large Russian bank

Illustration

Cybertonica CEO talks to Finextra about open API, data privacy and market expectations