Pipl, the identity trust company, today introduced Pipl Trust, a new solution designed to democratize trust and redefine the way online organizations and retailers look at risk for the digital consumer. Pipl Trust provides an easy, frictionless way to assess trust in every digital consumer interaction.
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Pipl Trust provides continuous adaptive trust to better identify trustworthy engagements at every digital touchpoint. The Pipl Trust data set includes more than 5 billion identities, over one trillion data connections and the broadest and deepest set of emails and mobile phone data available globally. (Graphic: Business Wire)
“The lack of trust online has significant implications at every consumer touchpoint and leads to increased friction, decreased loyalty and customer churn,” said Matthew Hertz, founder and CEO of Pipl. “We need to democratize trust and keep bad actors out of every digital interaction, not just the payment layer. By assessing the risk of every customer interaction, Pipl provides frictionless trust at every stage of the digital consumer journey and significantly reduces fraud and abuse.”
Evaluating Trust at Every Point of Digital Customer Engagement
Digital acceleration has exacerbated old issues and created new ones for website operators and mobile application providers—from fake registrations and false reviews, to account takeover and promo abuse. It’s important for businesses to be able to quickly and efficiently establish trust to reduce friction for good customers while defending against abuse.
Although many organizations look only at payment fraud, companies lose more business when they create friction for good customers. For example, U.S. merchants lose more than $443 billion annually in false declines. Beyond ecommerce, lack of trust impacts every organization providing any type of online service, from product reviews and reservations to dating, classified ads and streaming services.
Available as an easily integrated software development kit (SDK), Pipl Trust provides continuous adaptive trust to better identify trustworthy engagements at every digital touchpoint. Pipl Trust is easily integrated into every web page and application screen with a snippet of code. It then provides predictive trust scoring to automate trust decisioning at touchpoints such as registration, login, review and purchase. This improves the customer experience by reducing friction for good customers while stopping bad actors. Key features include:
- Industry’s most comprehensive and dynamic data set: Pipl lets businesses know if a digital consumer should be trusted. The Pipl Trust data set includes more than 5 billion identities, over one trillion data connections and the broadest and deepest set of emails and mobile phone data available globally.
- Continuous adaptive trust across the customer lifecycle: Trust and fraud indicators vary across activities. Unlike point solutions, Pipl Trust is purpose-built to examine key attributes associated with account opening, login, account changes, purchase and other customer touchpoints to leverage the right data and AI models at the right time to streamline risk assessments across the decision cycle.
- Ease of implementation: Customers can quickly add an invisible, frictionless trust evaluation to every web page or app screen and define their risk tolerance for automated approval or decline for the most common consumer interactions.
- Automation for faster decisioning: Pipl Trust leverages AI with machine learning to provide a simple score that significantly reduces the need for data and signals orchestration from multiple vendors.
About Pipl
Pipl is the identity trust company. We make sure no one pretends to be you. We use multivariate linking to establish deep connections among more than 100 billion disparate identifiers—email, mobile phone and social media data that spans the globe—and then look at the big picture to derive identity trust. Our solutions allow organizations to provide frictionless customer experiences and approve more transactions with greater confidence and speed. For more information, visit pipl.com
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