MarTech360 Interview With Ziv, Co-Founder And CTO At nSure.ai

“We cater specifically to high-risk merchants targeted by professional fraudsters, and we provide them with a dedicated AI/machine learning model that’s built for their business.”

Can you tell us a little bit about your professional background and your current role at in nSure.ai?

Yes, my professional background is in engineering. I graduated from Tel Aviv University with a degree in physics and electrical engineering and computer science in the late 20th century, and since then, I have been working in the high-tech industry as a software developer.

Over the past 10 years, I have been primarily focused on fraud prevention and the sale of digital goods. I previously owned the largest digital gift card marketplace in Europe, where we faced numerous fraud challenges. As a result, we began investing in resolving this issue, which eventually led to the spin-off of our company about four years ago, now known as nSure.ai.

What’s your current role at nSure.ai?

Co-founder and CTO.

Can you tell us a little bit about what nSure.ai does and how it differentiates itself from other companies that are in the same fraud prevention space?

nSureAI is a service provider specializing in fraud prevention for merchants selling digital goods. Our unique focus on the digital products and value transfer space allows us to assist merchants dealing with the inherent risks associated with immediate delivery and lack of physical address.

We cater specifically to high-risk merchants targeted by professional fraudsters, and we provide them with a dedicated AI/machine learning model that’s built for their business. What sets us apart is not only that, but also our screening capabilities for fraudulent transactions and ensuring secure transactions. In addition,  we also offer a comprehensive guarantee. If a fraud incident occurs on a transaction we approved, we take full responsibility and fully reimburse the merchant for any damages incurred.

Can you tell us a little bit more about your personal experience in R&D and software architecture and how that’s shaped your career?

I’ve been programming since the age of eight, starting with my first computer, a Sinclair Spectrum, and later a Commodore 64, where I dabbled in basic programming. What began as a hobby eventually turned into my profession.

I used to enjoy hacking games, manipulating their defenses to make copies before the internet era. Writing code and engineering have always been my passions, which led me to study computer sciences and pursue programming in the late 90s.

I’ve worked at companies like TCI Telecom and Checkpoint, initially in the security space and now in the cybersecurity field. This journey has shaped me into a software engineer, architect, and most recently, as co-founder and chief technology officer here.

What are some effective strategies that businesses can implement to prevent scalable, digital fraud?

The most effective approach to combat fraud is to avoid solely relying on identities. It’s crucial to strike a balance between the risks of allowing fraudulent transactions and the negative impact of declining legitimate ones.

In today’s landscape, identities have become increasingly inaccurate due to two prominent trends. First, there is a rise in the sale of identities on the dark web by individuals who generate real identities or through stolen identities obtained during Know Your Customer (KYC) processes.

Second, there is a growing inclination among legitimate users to conceal their identities for privacy reasons, leading to the widespread adoption of features like VPNs and temporary email addresses. This presents a challenge for fraud prevention, as both fraudsters and genuine users are appearing more similar in terms of identity.

To address this, it is advisable to shift focus towards techniques that unveil the true intentions of buyers, differentiating between bad actors and legitimate ones, rather than relying solely on identities. This approach offers a more effective strategy for individuals and companies in the current landscape.

Can you tell us a little bit about nSure.AI’s advanced AI risk engine and how it leverages machine learning techniques to identify fraudulent transactions?

At nSure.ai, our primary focus is building AI models that aim to uncover the true intent of buyers and distinguish between bad actors and legitimate users. We heavily rely on behavioral analytics, but not limited to the behavior of individual users. Instead, we analyze the broader market behavior in relation to specific transactions. Since the baseline of normal behavior is constantly evolving, we employ machine learning techniques to continually learn and adapt to these changes.

To achieve this, we gather a plethora of data points from merchant applications, web pages, and services. Additionally, we enrich this data with diverse sources to gain different perspectives. By combining and extrapolating hundreds of data points, we create a comprehensive dataset that encompasses tens of thousands of variables. This enables our machine learning models to provide highly accurate differentiations between users.

How do you see the future of fraud prevention and detection evolving? And what role does nSure.ai play in shaping that future.

It seems that fraud prevention needs to evolve by reducing reliance on identities and instead embracing the power of behavioral analytics. This direction allows for modeling complex behaviors that involve numerous metrics and data points, requiring advanced algorithms to handle the vast amount of data involved.

Furthermore, the decreasing effectiveness of identities aligns with the growing need to leverage machine learning for enhanced accuracy. In summary, shifting focus towards behavioral analytics and harnessing the capabilities of machine learning are essential steps in advancing fraud prevention strategies.

There is a growing trend towards digital products and a strong emphasis on delivering seamless digital experiences to consumers. It’s crucial to eliminate delays and reduce friction in the purchasing process to enhance user satisfaction.

At nSure.ai, we provide a solution that caters precisely to these needs. We enable merchants to sell digital goods and values without requiring extensive user identification or worrying about fraud-related damages.

Our unique proposition lies in offering a full guarantee to merchants, ensuring a smooth and secure digital commerce environment. We firmly believe that this is the future of digital experiences, and it aligns perfectly with the core values of nSure.ai.

What advice would you give to other leaders that has helped you personally?

When it comes to creating value, one must prioritize and measure the impact of their actions. As an entrepreneur or business owner, it is crucial to make decisions about what not to do, as there are countless possibilities and limited resources.

Sorting priorities based on the value they bring allows for a focused approach. This is a daily practice that I find to be the most important in my work. By focusing on the most valuable tasks first, one can maximize their impact and drive success in their endeavors.

What’s the biggest challenge you or your team is solving this year?

The biggest challenge we are tackling this year revolves around the emergence of new fraud patterns, particularly social engineering or victim-assisted fraud. In this type of fraud, perpetrators exploit the victims themselves to carry out fraudulent activities.

From a fraud prevention perspective, it becomes incredibly challenging to differentiate between a genuine user and a victim who is unknowingly manipulated by a fraudster. The fraud appears normal, as it originates from the same device, IP address, and location as the legitimate user.

For our customers, this poses a significant threat to their reputation, as they strive to protect their customers from falling victim to such schemes on their platforms. Detecting and preventing this type of fraud is a complex task, as it is highly scalable and evades easy detection.

Addressing this challenge requires innovative approaches and advanced technologies to safeguard against this emerging pattern of fraud.

Tell us about the last book you read?

The book I just finished reading is “Practical Fraud Prevention” by Gillette Supporter and Shoshana Marani. It’s a relatively new book, published either this year or possibly the previous year.

This book offers a comprehensive overview of various types of fraud and methodologies, focusing primarily on traditional fraud rather than the scalable and digital aspects. Nonetheless, it provides valuable insights into the ecosystem and strategies that can be employed. Overall, I find it to be a helpful and informative read.

Thanks, Ziv!