Peter Cholnoky, Founder & CEO
Today, organizations are heavily investing in applications that drive traffic and attract leads into an online community. However, they are often inundated with problems caused by phishers, bots, spammers, and fraudsters. As these cybercriminals have become more erudite and insidious, even robust security programs such as CAPTCHAs are breached swiftly and ingeniously. With identity fraud and cyber crimes on the rise, organizations are on the lookout for ways to analyze and filter out fake leads and fraudsters that are getting into the system and abusing it. The need of the hour is an advanced API solution that can analyze the sign-ups or webpage visitors to filter out genuine users and prevent the wrongdoers from abusing the organization’s resources. Enter E-HAWK.
As an ace in the enterprise security space, E-HAWK comes to the fore with their world-class cloud API solution to help organizations combat against fraudulent registrations, bogus leads, hackers, and organized cyber crimes. “Through E-HAWK’s solution, our main goal is to detect the fake profiles in account registrations and leads by providing rapid identification tests,” explains Peter Cholnoky, founder and CEO of E-HAWK. Integrated with big data, machine learning, and advanced analytics, E-HAWK’s real-time API runs close to 400 tests on the lead data and generates reports based on the information obtained. The analysis is done mainly in areas like IP, email, phone, name, location, domain, activity, geolocation, device, and fingerprints in real time and these tests can be scored according to the client’s risk profile.
How does it work? When a user submits a web form or signs up for a service, the back end of the client’s system sends an API call to E-HAWK with the data collected of the person. E-HAWK’s solution then runs several subtests and cross analyzes the linked data and returns the test scores found in a JSON response.
Our main goal is to identify the fake profiles in account registrations and leads by providing rapid identification tests
This consists of a Risk Score to understand the performance of the leads and information, and reason behind the given scores. E-HAWK’s alert system notifies the client for blacklisted users and they can infer whether the IP came from an anonymous proxy, spam or fake users and take actions from the API call based on the scores and risk hit details.
The highlights of E-HAWK’s API solution include their ease of implementation and integration capability into the client’s functional system and customization according to their requirements. Clients can develop their own background script to call E-HAWK’s standard base API, which begins to work the moment a user joins their system or submits a form. E-HAWK provides support in the onboarding process through web meetings and walks the client through the configuration and scoring settings.
The effectiveness of E-HAWK’s solutions can be best described with a client success story. Cholnoky narrates the case of a large affiliate program company who faced the challenge of fraudulent people signing up for the affiliate feature using stolen credit cards. They approached E-HAWK for their cloud API solution to analyze their new affiliate registrations and identify the phishes, bots, spammers, and high-risk users. Soon after implementing E-HAWK’s solution within a week, the company identified almost 25 to 35 percent rejection based on the data obtained. The solution checked for malware, spam email, multiple sign-in from the same device, and determined the legitimacy of the affiliates.
The year ahead looks promising for E-HAWK as the company intends to cross over 400 million transactions with their clients. With offices in New York and Amsterdam, the company’s expanding client base includes Fortune 500 companies to smaller web enterprises from Europe, Brazil, Australia, and other countries across the globe. In an effort to keep up with the constantly evolving challenges over the internet and stay ahead in the market, E-HAWK brings out new releases integrated with AI, learning engines, and other cognitive technology every six weeks.