Identity Verification

Identity verification is the process of confirming the identity of someone. Sometimes called “identity proofing” or “vetting an identity,” it is a method that authenticates the personal information provided by a consumer.

Early Forms of ID Verification

Traces of identity verification date back as early as 100,000 years ago. Before the written word became a way to document identities, physical identifiers were used, such as jewelry or tattoos. These symbols were used to indicate characteristics such as an individual’s wealth, familial or clan ties, and even personal identity. In 3800 BC Babylonians established a consistent practice of recordkeeping. Every 6-7 years the Babylonian empire conducted what would now be called a census, collecting detailed counts of both citizens and resources. In later years the Roman Empire refined their data collection techniques and introduced revolutionary concepts such as birth certificates, land title deeds, and thorough citizenship records.

In 1414 King Henry V of England created passports as a means for English citizens to prove their identities while visiting other countries. In 1829 the British Parliament, prompted by the reforms of Prime Minister Robert Peel, called attention to the importance of printed police records. This probe into more effective documentation led to a more modern way of documenting identities, where a personal document file could be linked back to individuals using a unique numerical value. This advancement paved the way for government databases that link to ID cards.
Approximately ten years later, a Personal Number (PN) system was created in the Netherlands and by the early 1900’s Americans had established the Social Security Administration. Personal identification methods advanced through an international effort as countries around the world developed ways to identify individuals via inked fingerprints, numerical systems, and photo ID’s.

In the late 1970’s the United States established a computerized records system, which presented the ability to cross-reference or compare records between various governmental and banking organizations.

Two Factor Authentication

The arrival of the Internet and subsequently e-commerce, led to the advent of Two Factor Authentication (TFA), also known as two-step verification. This is a method of identity confirmation that requires an additional piece of information beyond just a password. This second factor varies, but can be anything from a personalized security question to a text message with a unique code, even a phone call to corroborate that you are who you say you are.


By the early 2000’s biometric data was revolutionizing identity verification. Biometric verification is the collection of physical or behavioral data in order to uniquely identify a person. These metrics are categorized into morphological (fingerprints, hand and earlobe geometry, vein pattern, shape of face, iris and retina pattern), biological (DNA, blood, saliva, and urine), and behavioral measurements (voice recognition, gestures, speed of movement, etc.). Biometric data has been proposed as the verification of the future and has already been successfully implemented in identification security measures. Biometrics are currently used to authenticate one’s identity in several governmental fields, specifically border control, voter registration, law enforcement, and healthcare.

Apple Inc. began using biometrics, mainly Touch ID and Face ID as a verification tool in unlocking one’s iPhone, making purchases, and authenticating Apple Pay or various other online apps. Touch ID refers to a fingerprint verification and the Face ID feature is a facial recognition system, both are predicted to increase in popularity within the consumer tech world.

Identity management experts hypothesize that although biometrics is trending and clearly on the rise, it will not completely replace passwords. Rather its place in the immediate future will be in providing an extra layer of security, fortifying verification as part of a multi-factor authentication model.

Know Your Customer

Know your customer (KYC) is a process used by businesses to verify the identity of their clients either before or during the time that they start doing business with them. KYC also references the bank and anti-money laundering regulations that are similarly used for purposes of verification. KYC methods are implemented by companies of all shapes and sizes for the purpose of vetting a client, to be sure they are clear of any involvement in corruption, bribery, or money laundering. In addition to confirming non-bribery compliance, KYC procedures are used by businesses to better understand their customers and their corresponding financial dealings.

KYC systems are usually initiated through electronic identity verification, by collecting basic data and information pertaining to their customer. This includes personal information such as name, address, SSN, etc. The aggregating of these personal data components is often referred to as a “Customer Identification Program” and upon completion it is compared to a list of individuals that are known for corruption. If this test is passed, the bank continues the verification process by assessing how much of a risk their client appears to be and how likely they are to be involved in illegal activity. In accordance with the anti-bribery due diligence the business will formulate a general outline of what the client’s account should look like so that in the future, it can be monitored for anything that appears to be out of place or suspect. **Machine Learning**

Machine learning is an application of artificial intelligence (AI) that allows systems to learn automatically without human intervention or assistance. Machine learning focuses on the development of programs that can progressively improve from experience without being explicitly programmed to do so. These machines “learn” through observations of data including examples, experiences, instructions, or pattern analysis. Due to the ever-increasing statistics involving identity fraud, machine learning is actively being used to aid in identity verification.

Each consumer has a digital footprint that is studied by AI in order to recognize patterns and subsequently accurately assign these patterns to an individual’s digital ID. Identities are being stolen at a high rate per day. In order to combat these tragic numbers, we must be develop defensive technology that specializes in protecting our identities.

Identity Verification and Credit Reports

Personal information is directly tied to the credit report profile and its data. It is crucial to ensure your personal information is updated and accurate. Protecting your data and monitoring your SSN, address, and other important information is standard common sense within the current technology climate.