Recently in Customer Identities Category

How to Know Customers Are Who They Say They Are

| No Comments | No TrackBacks

In 2015 alone, 62% of companies were targets of payment fraud. As customers increasingly conduct their financial affairs online and via mobile devices, risk management and fraud prevention become more and more difficult. So, how do you know customers are who they say they are?

Short of reaching through the computer, tablet, or smartphone screen and verifying a customer with your own eyes, there are a plethora of ways that help you better know your customer, manage risk, and even prevent fraudulent transactions.

Age & National ID Verification

The first step to customer authentication is to match a customer's national ID (for example, their social security or driver's license numbers) and date of birth. Better authenticate a customer's ID documents and simplify compliance with any age restrictions or purchase laws, while improving customer service at the same time. Instantly verify that the customer purchasing your age-restricted goods is old enough to legally make that purchase.

Name-Address Matching

The second step is to match name to address to confirm the person buying your product or service isn't giving you false information. Personator leverages a comprehensive dataset containing billions of records to confirm and match current names and addresses with the highest degree of accuracy. Our powerful, real-time tools and services help you achieve entity resolution and compliance, as well as better know your customer and reduce, or even eliminate, the need for manual review.

Address Correction & Formatting

Next, you'll want to add in what's missing from customer data entry, legacy systems, sales input, and anywhere else your records come from. Add missing street suffixes, state/province/administrative area info, and standardize addresses to specific country formats using Advanced Address Correction (AAC) to verify that addresses are accurate and deliverable to real locations.

Contact Data Validation

Validation concerns more than just a name or address - it needs to look at all aspects of people data, from names and addresses to phone numbers, email addresses, geocodes, IP locations, demographics, and more. Determine that the given postal address for every customer is deliverable, the email address exists, the name associated with a mobile device and whether the phone number is active and callable, and the given name is in a valid format. You can even trace customers with geocodes and IP locators to manage risk and ensure compliance.

Melissa's Personator® World Edition can help meet all of these needs. Personator is a customizable web service that fits all your ID verification process and risk management requirements. It can help optimize onboarding and fraud detection in Ecommerce, AML Compliance, Customer Due Diligence, Card Not Present, Know Your Customer (KYC), and FinTech/RegTech arenas.

Try Personator free for 30 days to see how it can transform your business's safety and compliance.

By David Loshin

In the past few entries in this series we have basically been looking at an approach to understanding customer behavior at particular contextual interactions that are informed by information pulled from customer profiles.


But if the focal point is the knowledge from the profile that influences behavior, you must be able to recognize the individual, rapidly access that individual's profile, and then feed the data from the profile into the right analytical models that can help increase value.

The biggest issue is the natural variance in customer data collected at different touch points in different processes for different business functions. A search for the exact representation provided may not always result in a match, and at worse, may lead to the creation of a new record for the same individual, even one or potentially more records already exist.

In the best scenario, the ability to rapidly access the customer's profile is enabled through the combination of smart matching routines that are tolerant to some variance along with the creation of a master index.

That master index contains the right amount of identifying information about customers to be able to link two similar records together when they can be determined to represent the same individual while differentiating records that do not represent the same individual.

Once the right record is found in the index, a pointer can be followed to the data warehouse that contains the customer profile information.

This approach is often called master data management (MDM), and the technology behind it is called identity resolution. Despite the relative newness of MDM, much of the capability has been available for many years in data quality and data cleansing tools, particularly those suited to customer data integration for direct marketing, mergers, acquisitions, data warehousing, and other cross-enterprise consolidation.

In other words, customer profiles and integrated analytics builds on a level of master data competency that is likely to already be established within the organization.


Categories