GEMS Data Model and Growing Global Business at the Speed of Trust

Innovation
Data Science
Identity Fraud
Data analysis
Paul Fisher & Robert Nendza -- Pipl
Jul 15, 2021
Webinars
This session will provide insight about how leading online commerce businesses are using the “GEMS” data model (Global, Email, Mobile phone, Social media) to create a baseline for engaging, verifying, and assessing the risk of customers in new markets where traditional data sources typically used for these essential tasks fall short.

Some content is hidden, to be able to see it login here Login

Blue-tinted background of a man watching a webinar

Host a Webinar with the MRC

Help the MRC community stay current on relevant fraud, payments, and law enforcement topics.
Submit a Request

Publish Your Document with the MRC

Feature your case studies, surveys, and whitepapers in the MRC Resource Center.
Submit Your Document

Related Resources

Mar 07, 2023
The Hidden Opportunities (and Cost) in Your Existing Payments Stack

There’s a big gap in digital commerce. Merchants have very detailed data on their entire customer journey up until one of the most critical points: the payment. At that point, many are lacking clear visibility and real insight into their approval rates and other business metrics, often resulting in loss of revenue and higher total cost of payments acceptance. This is mainly due to unclear or insufficient payment data—payment data with which they could easily answer questions like Why are 15% of my orders declined and what could/should I do about that? Most merchants don’t have easy access to the answers.

Participants in the ecosystem such as payment gateways, payment service providers (PSPs), third-party fraud tool providers, BIN service providers, acquiring banks, card brands, and issuing banks (and APM schemes) must all come together in some capacity for a single payment to go through successfully.

All these layers between buyers, merchants, and approved transactions have different technology standards, formats, data fields and, most importantly, definitions of data and data fields—both in what is sent out (for approval) and what comes back (in response). It all adds up to a huge challenge for businesses to easily access and turn payments data (whether from one or many PSPs/processors) into actionable insights. How can you improve performance if you don’t know what to tweak or why? How can you monitor any changes over time?

All merchants have some form of blind spots in their payments data that can help them uncover and address costly issues or opportunities to improve. And what could be more relevant today—in an economy where companies, teams, and people are being asked to do more with the same (or less) resources—than finding ways to optimize your existing payment stack?

Mar 07, 2023
From Fraud To Trust: A Better Approach to Digital Identity Verification

The dramatic shift to online shopping means retailers see their customers less than they ever have. Additionally, with daily data breaches and lax password security, account credentials are readily available for purchase.

This is a boon to fraudsters looking to pose as legitimate customers. So good in fact, that from 2019 to 2021, identity theft increased 81.8% globally. For too long, organizations have played defense and responded to suspicions of fraud reactively. It’s time to start establishing digital trust with customers early in the journey, just like retailers would do in the day when they knew their customers personally.

Identity is at the root of all fraud. Merchants that can safely trust their customers' identities will reap the benefits. First, they can greatly reduce the impact of fraud on the business. Second, they have more—and better—data for reducing customer friction, increasing loyalty and targeting sales or marketing efforts more effectively.

So how can merchants know for certain a customer is who they claim to be?

Traditional identity verification (IDV) solutions validate some customer attributes, but these are no longer enough to establish trust. To establish that an identity can truly be trusted, it’s imperative to take a more holistic look and verify the connections between that data and the person claiming to be a customer.

Professional fraudsters can try to impersonate legitimate customers, but they can’t create trusted identities. Even synthetic identities fail when exposed to this scrutiny.

This is why trusted identities offer a safer approach to IDV. By identifying trust, the company focuses less on behaviors and more on the individual making purchases.

X
Cookies help us improve your website experience.
By using our website, you agree to our use of cookies.
Confirm