Know Your Users to prevent fraud | User behavior analytics | Nethone

Gain more loyal customers, reject only fraudsters

Nethone has developed a proprietary fraud prevention solution based on a Know Your Users™ approach, which enables comprehensive, indepth, multidimensional profiling of all online users. From knowing customers to understanding their real motives it’s an essential tool for the new era of customercentric services.

Thanks to the rise of the Internet, the world is said to have become a global village. But has it, really? In a village everyone knows everybody; on the Internet, things are different. People are in a “shadow” behind their screens, more anonymous.
Of course, it’s just an illusion, because every action on the Internet leaves a digital trace. But even though vast amounts of data is at our fingertips, many organisations still refrain from leveraging this additional understanding in customer-facing processes.
Nethone’s Know Your Users™ approach
is an answer to this challenge

We’ve built Nethone Profiler, a solution that allows us to collect unique first-hand data about online users.

Thanks to a proprietary use of machine learning techniques, we are able to profile gathered information, segment traffic and block fraud attempts.

We deeply believe that the future of eCommerce will mean less and less online friction for users. Years of experience in online business allowed us to understand how much of the userside friction is caused by imprecise risk management processes. Nethone was created to enable the further dynamic growth of the eCommerce channel, thanks to radically reducing the risk management related friction manual verification and passive authentication.

From knowing to understanding

What’s the difference between Know Your Customer (KYC) and Know Your Users™ (KYU)?
KYC tries to recognise who’s on the other side of the screen verifying the
identity of a customer. But why not use this data for other purposes also?

What if we could:


enrich and augment the process, and make much more use of it?


move from just protecting the bottom line of an organization to proactively boosting its top line?


broaden our perspective to take a super close look at all users, not just those who have already proceeded to the checkout or filled out the sign-up form?


reach beyond “knowing” to actually “understanding?”

These questions have led the Nethone team to where we are today.


Know Your Users™ is a step forward compared to KYC. It’s all about understanding what’s nondeclarative and unravelling what’s hidden. Nethone Profiler, the technology standing at the heart of the KYU approach, allows merchants to get an exhaustive picture.


It extracts over 5,000 attributes about the device itself, its software and network characteristics, and most importantly about users’ behaviour to get a holistic understanding of the customer the merchant is dealing with.


The outcome of this analysis fuels the machine learning engine responsible for spotting both typical and unusual patterns and correlations, and allows to train the models to industryspecific needs.


As a result, the solution is able to provide realtime recommendations about customers with very high accuracy, all to limit fraud risk and increase income by identifying recurring users and unleash sales potential.

How to shift from KYC to KYU?

To build on top of Know Your Customer towards Know Your Users™ and benefit from that upgrade, it is crucial to understand a few things. First of all, being customercentric it’s the users who need to be satisfied with their online experience to become loyal clients. Secondly, machine learning models are a key factor to this change.

ML models

ML models developed for years

We have been working on our solutions to bring an added value of increased conversion rates since 2016. It required not only a good infrastructure, but also Data Science expertise. All to train machine learning models dedicated to fulfil the specific needs of each of our clients.

Self improving system

Self-improving system

And it’s important to understand that these models can actually reinforce each other by leveraging the outcomes of analyses conducted in the past or at the very same time, but in different contexts for new analyses.

More accurate predictions

More accurate predictions

Just to illustrate the idea; a model identifying prospective frequent shoppers can generate predictions to be used as an additional source of data for a new model, responsible for, say, detection of users likely to churn within 3 months to make their predictions more accurate, and so on and so forth.

Expert on board

Experts onboard

Creating an ecosystem of models is quite a challenge and requires the involvement of some of the brightest minds — people who understand all of the business nuances as well as technical requirements. Our dedicated teams take care of this challenge to address even the most complex needs.

Curious about Know Your Users™ analytics?

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