What is customer verification?

Customer verification is a process used by contact centers to substantiate the customer’s information and validate their identity.

This allows organizations to reduce risks related to fraud or identity theft, protect their reputations, and comply with government laws and regulations, while adhering to guidelines set by regulatory bodies.

In today's digital age, customer identity verification has become even more critical. With the rise of online transactions and the increasing threat of identity theft, businesses must take steps to verify their customers' identities to protect themselves and their customers.

Why is customer identity verification essential?

Here are some reasons why customer identity verification is essential for your business:

It can prevent fraudulent activities. One of the main reasons to implement customer identity verification is to prevent fraudulent activities. By verifying a customer's identity, you can ensure that they are who they say they are.
It can protect your reputation. If your business falls victim to identity fraud, it can damage your reputation and erode customer trust. By implementing customer identity verification, you can protect your business and your customers.
It helps you comply with regulations. Many industries have regulations that require businesses to verify their customers' identities. For example, financial institutions must comply with Know Your Customer (KYC) and Anti-Money Laundering (AML) regulations. By implementing customer identity verification, you can ensure that you are compliant with these regulations.
It improves the customer experience. While customer identity verification may seem like an extra step, it can actually improve the customer experience. By verifying a customer's identity, you can prevent delays and ensure that they have access to your services or products quickly and easily.

There are several methods of customer verification, including passive verification, knowledge-based authentication, biometric authentication, phone number verification, document verification, and facial recognition. Two-factor authentication or multi-factor authentication, which combine two or more verification methods, are also becoming increasingly popular.

Passive verification vs. active verification

You can break down all verification procedures into two main categories: passive and active.

Passive verification is the process of authenticating callers without interacting with them. This includes calls authenticated before they reach an agent, using methods like matching phone numbers with the database or voice recognition software. This saves valuable agent time and enables the contact center to add more self-service options in the IVR.

For e-commerce and online businesses, passive identity verification can be done in real-time using APIs and other verification solutions. This can help automate the customer verification process and improve the user experience.

Active verification is a form of customer identity verification using knowledge-based questions. Agents are required to ask questions, like the customer’s date of birth, to verify their identity. This is a safer method leading to fewer false positives.‍

For financial institutions and other providers of financial services, active identity verification is an essential part of the onboarding process, typically involving verifying a customer's identity using a driver's license or social security number, as well as their bank account information.

What are the different types of customer verification?

Multi-factor verification: This is the most common customer verification process in banks as it adds layers of security using two or more pieces of evidence. These could include knowledge (something they know), possession (something they have), and intrinsic (something they are).
Age verification: This form of customer verification involves authenticating identity by asking for their birthdate. It is often used for services that require customers to be of a certain age for getting access.
OTP verification: One-time passwords or OTPs are sent to customers via SMS or email as unique and limited-time authentication methods.
Knowledge-based verification: This method requires customers to submit critical information like full name, mailing address, home address, phone number, age, or email to then match with the database.
Photo verification: A particularly newer method, photo verification requires the customer to hold a particular document to verify their identity and capture their photo.
Video verification: This verification method works just like photo verification but via a video call.

Keeping sensitive customer details secure

Equally as important for call centers that are engaging in customer verification is the ability to keep information safe and secure. After all, verification typically requires that the customer share highly sensitive, personal information. Being unable to effectively protect this information is a compliance breach and almost always leads to financial lawsuits, imposing of penalties, and loss of brand reputation.

This is where redaction comes in. But legacy redaction techniques are prone to compliance misses while erroneously redacting critical data. Automation and AI can improve this process.

Observe.AI’s Selective Redaction

Observe.AI’s Selective Redaction, for example, uses attention-based deep neural networks to detect and redact only relevant entities of customer information. This unique approach ensures the precise amount of customer data is removed based on the specific compliance needs of each organization, while empowering the contact center to maximize visibility and actionable insights that impact quality assurance and agent performance workflows.

This level of accuracy and efficiency is impossible to achieve with traditional legacy methods, such as agent-initiated stop-and-resume or keyword-based and numeric redaction.

“Today's digital-first contact center contains a wealth of business-critical yet sensitive customer information,” said Swapnil Jain, CEO at Observe.AI. “By harnessing AI to increase accuracy and precision of the redaction process, we’re letting contact centers adapt to the needs of their business and selectively hide customer information without losing the context of their conversations. This not only solves the compliance problem but also drives better agent performance and business results.”

Ultimately, customer identity verification is an essential step for any business that wants to protect itself from fraud, comply with regulations, and improve the customer experience. By implementing customer identity verification, you can protect your reputation and your customers' information, and ensure that your business is operating in a secure and compliant manner.

How can automation and AI improve customer verification?

Most companies evaluate only about 2% of customer interactions, because the process of analyzing conversations is time-consuming, manual, and often painstaking. That means it’s extremely hard to check agents are staying compliant with customer verification protocol because only a small sliver of calls can be reviewed. Insights are sporadic, slow to surface, and based on a small and random selection of calls.

Call center AI offers a variety of solutions to this problem.

Contact Center Conversation Intelligence

Observe.AI, for example, offers an end-to-end conversation intelligence platform that records and analyzes 100% of customer interactions and performs automated QA, allowing managers to accurately assess agent compliance when it comes to customer verification, and to target coaching to individual agents and their needs for maximum results.

Real-Time AI

AI also allows for coaching and course correction in real time. Observe.AI’s Real-Time agent assist feature, for example, can ensure agents are in compliance while still on the call by continuously analyzing the conversation and offering tips and alerts in real time.

Generative AI for Contact Centers

Meanwhile, Observe.AI’s Generative AI-powered Auto Summary feature can also automatically generate call notes for agents in text form, allowing contact center leaders to quickly see if the proper customer verification protocol was followed and identify areas for improved compliance.

Combining Generative AI with a contact center’s knowledge bases enable agents to answer customer questions and respond to pushback quickly and easily; for example, if a customer asks why their social security number is needed and what it’s used for, the agent can type that question into Knowledge AI and get automated, highly accurate answers based on industry- and company-specific data and documentation.

Learn more about how AI and automation can impact your customer verification process and agent performance. Get a demo of Observe.AI.