In any identification system, the process of determining a person’s identity and then using that identity to verify activities and transactions at multiple stages is often referred to as the “identity lifecycle”. This lifecycle is crucial to establishing trust whenever there are transactions between people, identity providers, and public and private sector parties.
The identity lifecycle starts during the identity proofing stage of onboarding, when a person first registers and creates their identity online. That identity is then verified and their attributes and credentials are updated over time. Identity authentication is then implemented at different stages of the lifecycle by corroborating documents and biometrics. The identity lifecycle ends when an identity record is retired or invalidated. For example, the individual requests to remove their profile.
The area of identity verification (such as biometric verification) is complex and forever evolving, which is why it is so vital for organizations to keep their knowledge up to date to protect themselves and their customers from the increasingly sophisticated attacks of fraudsters. This article will help break down the most common terms used within the IDV space, specifically within the identity lifecycle.
Authentication is the process of validating a known user’s identity to allow access to an account, device, or location. Common authentication types include something the user knows (like a password), something the user has (like a mobile phone or token), and something the user is (like a biometric).
Bias in biometrics
Bias in biometrics refers to the bias applied to decisions made by machine learning algorithms. They are a result of inequalities or lack of representation present in the training data, and human prejudices/errors that consciously or unconsciously get applied during algorithm development. When bias exists within a biometric algorithm, it results in unequal outcomes for certain users based on their age, race, or gender. Learn more about demographic bias in biometrics.
Biometrics (physical and behavioral)
Physical biometrics are biological measurements such as fingerprints and face matching commonly used as a means of identifying and authenticating individuals in a reliable and fast way. Behavioral biometrics analyze a user’s digital, physical and cognitive behavior. They identify people based on how they behave and interact online rather than by static information or physical characteristics. Examples are keystroke movements and touchscreen behavior.
Customer experience is how customers perceive and feel about a company or brand based on the interactions they experience at all stages of the customer journey. This includes how they experience interacting with marketing materials, the sales experience, the quality of the product or service itself, and the customer service they receive post-purchase.
Continuous authentication is a method of confirming user details in real time and granting them access to online services, such as a banking session from beginning to end, based on acceptable levels of risk or contextual information. Continuous authentication relies on continuous data processed by a risk engine that applies the appropriate level of authentication during the entire session.
Deepfake software uses AI, neural networks and machine learning to create a video of a person in which their face or body has been digitally altered so that they appear to be someone else. There is fraud risk associated with this because the content can potentially be used to falsify and impersonate the identity of customers during onboarding processes.
A digital identity is essentially the electronic equivalent of your identity in the physical world. A digital identity allows individuals to securely verify their identities when making transactions online. In practice, digital identity is an extension of physical ID documents such as driver’s licences, passports, and bank cards. However, it provides more privacy and control over how personal information is used and shared.
Ecommerce fraud, also referred to as payment fraud, is illegal payment transactions that criminals or fraudsters make on a website without the account owner’s knowledge. This is commonly done by falsifying the person’s identity or using fake or stolen credit cards.
Facial recognition, a category of biometric security, is a method for identifying or authenticating an individual’s identity using facial features from photos, videos, or in real-time. A facial recognition system works by running an analysis on multiple images that are stored either on a personal device, or in a larger server / database, to find a match.
When it comes to criminal activity, fraudsters adjust their tactics depending on the generational preference being targeted. According to the Javelin report 2021 Identity Fraud Study: Shifting Angles, millennials experience financial crime more often through text scams promising rewards, or peer-to-peer (P2P) transfer confirmations. Boomers, on the other hand, have a higher chance of receiving robocalls disguised as healthcare providers
For an extra layer of risk reduction, identity verification is offered as a service, where vendors have fraud experts who do the entire identity lifecycle check on behalf of organizations. Mitek Mobile Verify's Agent Assist helps organizations create a frictionless customer experience while ensuring scalability and business continuity of document identity verification processes.
Identity proofing is the process of proving a user is who they claim to be. The term is synonymous with “Identity Verification.” It is usually introduced during the onboarding experience.
The digital customer journey is the path to customer purchase and retention. The journey combines all the touchpoints (i.e. points of interaction) a customer has with a business, including consumer data, transaction information, cross-device browsing history, and customer service interactions. The five stages in the digital customer journey are awareness, consideration, purchase, experience using the product/service, and brand loyalty. Read about how identity verification is involved throughout the customer journey.
Know your customer (KYC)
The Know Your Customer, or Know Your Client, are standards that have been designed to protect financial institutions against fraud, corruption, money laundering, and terrorist financing. KYC identity verification involves establishing the customer’s identity, understanding the nature of the customer’s activities, qualifying that the source of funds is legitimate, and assessing the associated money laundering risks.
Lifecycle of identity
The identity lifecycle involves verifying and authenticating a user’s identity throughout their online interactions with a financial institution. This involves using a combination of documents and biometric solutions to establish a foundation of trust with customers, and continuing to protect that trust over time. Learn about best practices for the digital customer lifecycle.
Machine learning is a type of artificial intelligence that uses data and algorithms to mimic how humans learn and make decisions. The algorithms learn from historical data and apply what they have learned to predict future outcomes. It is constantly improving its accuracy over time.
Multimodal authentication refers to the use of multiple biometric modalities for enabling user access. For example, a mobile application can layer voice biometrics and facial recognition for high security with minimal friction.
Near-field communication (NFC)
Near-field communication is an evolution of RFID (radio frequency identification) technology. The reader device, such as a smartphone, generates a magnetic field. When activated by another chip nearby, any stored data on the tag can be wirelessly transmitted to the reader. Mobile Verify NFC collusion contains optical and biometrics verification features to deliver a single-point IDV solution.
Neural networks are a subset of machine learning. They are algorithms that imitate the way a human brain works to recognize underlying relationships and patterns in a set of data. Multiple layers of neural networks arranged in a hierarchy enable Deep Learning, an advanced type of machine learning capable of making intelligent decisions without guidance.
Customer onboarding is the process new users go through when setting up their account to use a digital product or service. It covers the whole customer journey, from initial sign-up to product activation and first use, and involves identity verification and authentication. Creating a frictionless experience is key to establishing trust with the customer.
Passive vs. active liveness
When using biometrics for identity verification or authentication, liveness detection refers to establishing the presence of a live user in front of the capture device (i.e. camera, microphone, fingerprint reader). Passive liveness detection requires no action by the user. As a result, it is a faster process, less confusing for the user, and has lower abandonment rates. Active liveness detection relies on the user’s movements such as nodding, blinking, smiling, or correctly positioning one’s face in a frame.
With scams getting more sophisticated each passing year, financial institutions need to be at the forefront of preventive measures. Cybercriminals are diversifying their targets and using stealthier methods to commit identity theft and fraud. That is why it is critical for organizations to ask the right questions when determining which identity verification and authentication solution is the best approach for the company and their customers.
Regulation & compliance
Various federal and industry-specific regulations exist to ensure data security and privacy. This includes PCI, Sarbanes-Oxley, and HIPAA. Each are designed to keep sensitive customer data safe. Failure to comply with them can be costly in terms of fines, penalties, and other negative repercussions such as loss of trust with the public. Identity and access management solutions can be used to meet numerous compliance requirements.
Step up authentication
With step-up authentication, users can access one layer of resources with a set of credentials, but are required to submit additional credentials in order to access more sensitive resources or information. An example of a transaction that requires stronger authentication is if funds are being transferred over a certain amount.
Trust is an imperative aspect of any relationship, especially when building a loyal customer base. It is even more crucial when conducting transactions and establishing relationships online. Different businesses require different identity verification models depending on the risks associated with their specific industry, but ultimately, building a customized identity verification model is essential for identifying and ensuring trustworthy transactions and customers.
A user experience that is founded in addressing customer needs and providing value can be key to making - or breaking - an organization’s bottom line, reputation, and customer loyalty. Many customer touchpoints have become digital-first, and with other industries like ecommerce leading the way in providing exceptional customer experiences, expectations are higher than ever for financial institutions to provide a seamless and easy user experience.
Voice verification is a form of biometrics that confirms a user’s identity by analyzing their unique voice characteristics. It does this by comparing their voice to the voiceprint stored in a company’s database. A voiceprint includes more than 100 unique physical and behavioural characteristics of each individual, such as length of the vocal tract, nasal passage, pitch, and accent.
Wallets (Digital wallets like Apple, Venmo, Cash App, and PayPal)
Digital wallets contain a digital version of your credit and debit cards. The information is stored in wallet apps on a mobile device, such as a smartphone or smartwatch. Card numbers and personal information are not stored directly on the device. Examples of digital wallets include Apple Wallet, CashApp, and Venmo.
X marks the spot
When it comes to the identity lifecycle, the sweet spot for any organization is where security, trust, and convenience intersect. To find that overlap, it is vital to have in place a sustainable and secure digital infrastructure. Establishing a foundational digital identity layer in the lifecycle is made possible by customer identity solutions that have evolved to support enterprise-level digital transformations.
Protecting your organization and customers from hackers and fraud means protecting digital identities. If done well, digital identities will ensure that all business activities and interactions are made easier and more secure. This will ultimately increase customers’ confidence with conducting online transactions, and build their trust in financial institutions.
Zero is the number of people who have the exact same physical and behavioral biometrics. Biometric characteristics are unique to each individual, so the only way for a digital identity to be compromised is if it is done fraudulently. This is why identity verification and authentication are so critical to maintaining safe digital identities throughout the entire identity lifecycle.
Many organizations have already adopted biometric-based verification and embraced technology for continuous authentication as a means to enhance the customer experience while protecting digital identities throughout the entire lifecycle. Identity and access management has become easier and stronger with advanced solutions offering a wide variety of features, such as face & voice recognition and NFC authentication. To assure customer's identities are safeguarded throughout the lifecycle, companies must continue to adapt through a layered approach to allow the right people in and keep the bad guys out.