Keep up with the digital identity landscape.
Ekata, a global identity verification company, provides APIs and SaaS solutions that allow businesses worldwide to link digital transactions to the human behind the screen and fight fraudulent transactions. The company focuses on five core elements: name, phone, email, address and IP, universal attributes that are used as global identifiers. Their product suite is powered by the Ekata Identity Engine, their proprietary, intellectual property, that uses unique datasets from the Ekata Identity Graph, and the Ekata Identity Network which provides identity verification data.
The company recently announced the release of its latest product for its global identity verification dataset, Network Score.
Network Score is a machine learning prediction that enables businesses to better identify good and bad customers based on a series of insights. The new dataset flags potentially risky digital transactions and fraudulent customers by analyzing the activity patterns of the identity information being used.
The new Network Score service leverages the Ekata Identity Network to reduce the number of false declines and increase the precision of fraud detection. The Identity Network works in conjunction with the Identity Graph, vetted through rigorous acceptance criteria in compliance with global privacy and security standards.
“With over 20 years of sourcing identity data from our global data providers, we know that authoritative data isn’t enough,” said Rob Eleveld, Ekata CEO. “Stolen personally identifiable information (PII) and fake digital identities are becoming increasingly prevalent, which makes verifying identity in the digital and card not present (CNP) world harder than ever. Fraudsters can try to impersonate and act the way legitimate users do but they will never match 100 percent of the time; those activity patterns can be powerful signals of fraud.”
For example, a real consumer typically uses the same primary address and secondary address together. But looking at how that secondary address has been used across the digital interactions in a Network, one might see that the secondary address has been used with tens of different email addresses in the month, which suggests promotion abuse or other fraudulent activity. Ekata built the Identity Network to track these types of activities and leverage transaction-level intelligence to identify when consumer information is being misused.
The Identity Network, along with the Identity Graph, are differentiated datasets that power the Ekata Identity Engine. The Identity Engine helps businesses make accurate risk decisions about their customers by providing predictive data insights on who they are, and how their information is being used online. Using sophisticated data science and machine learning, the Identity Engine transforms the two datasets into unique and valuable data attributes, such as Ekata’s new Network Score. These attributes are made available through Ekata’s APIs and SaaS-based tool, to vastly improve business’s confidence in their risk analysis.
The Identity Network offers dynamic decision making, as the model continues to learn with new transactions in order to better determine fraud potential. Moreover, the Identity Network provides businesses insight into cross-border and cross-industry fraud patterns outside of their own data set. The Identity Network does not rely on blacklisting and does not use previous customer decisions to influence its data.
Network Score is also one of the attributes that is surfaced in the APIs, which sits in key products like Identity Track API and Transaction Risk API. The company selects those features based on performance, precision and finding fraud, so Network Score is centered on the innovation that Ekata is doing from a machine learning and data science perspective.
“The engine is essentially our core technology that powers all of these data insights. We have two data sets that we use to power that engine, and so the network is one of those components, and Network Score is derived directly from that,” said Stacey Chen, Senior Product Marketing Manager at Ekata. “And the way that we think about it is, we have a graph, and we have a network, so the graph is focused on validating digital identity elements and how they’re linked, and then the network really tells us about how those elements are being used.”
The company is already looking toward the horizon after the rollout. The aggregate score is currently generated from 147 features in Ekata’s machine learning model, opening the door for evaluation for which five key elements the company is hoping to expand upon from a network perspective. However, according to Chen, it all comes down to what the market demands.
“Five years ago, we probably wouldn’t have cared as much about the phone if it weren’t for [mobile-first companies like] Postmates or Uber. So, we’ll continue to see what the market needs are and build our features around that. I think Network Score is just the start of that, and there’s a lot of features that get input into the model for the Network Score prediction, so there’s room to explore how we can look at those individually or pull those apart and make those available to our customers.”
Currently, Ekata works with a variety of notable customers across different sectors, including Stripe, Square, American Express, Postmates, Airbnb and several other marketplaces pertaining to travel, e-commerce and online lending. However, with the COVID-19 pandemic in place, the organization is looking toward other potential spaces. But when it comes down to who they provide their services to, the goal is to provide a secondary layer of additional verification and customer data to fight costly fraud schemes.
Keep up with the digital identity landscape.
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