The Importance of Identity Verification Match Rates, Explained

Organizations that can verify customer identities quickly, accurately and cost-effectively can position themselves to keep pace in a constantly evolving digital and regulatory landscape.

That onboarding imperative places critical emphasis on identity verification match rates and the importance of ongoing monitoring and optimization. It’s a make-or-break process for organizations because verification speed and accuracy influence the customer’s onboarding experience, which, in turn, directly affects abandonment rates and an organization’s bottom line.

Match Rate Calculations

An identity match occurs when a person’s information meets the requirements for verification. The match rate is the percentage of submitted identities from a particular group that meet the criteria for verification. 

To understand match rates, it’s helpful to shift from the group metric to the individual level.

People who positively match the identity information they provide are considered verified. If a person doesn’t reach the verification threshold, the organization often must invest further resources for a deeper investigation. Multiply that scenario by thousands, or even millions, of customers, and the importance of match rates becomes apparent.

Problems that occur at the individual level for identity verification have the potential to scale up.

Conditions for Success

Behind the scenes, identity verification technologies are a blend of art, science and continuous improvements. Here are a few conditions for successful verification.

Accurate, Comprehensive Data

Superior match rates start with accurate data. Out-of-date or irrelevant data can hamstring match rate performance. 

That data also has to apply to the organization’s target audience. The more coverage the data provides, the higher the potential match rate. 

A verification program’s success often depends on how well the organization understands the strengths and weaknesses of its data sets.

Reliable Data Inputs

No matter how high-quality and far-reaching an organization’s data sources are, there’s no way to ensure the information formats will match what people submit. If the data a potential customer submits doesn’t match the expected format, a no-match can occur.

Phone number fields illustrate the broad range of formats.

555-1234

555.1234

5551234

604-555-1234

604.555.1234

6045551234

+1 604-555-1234

Successful verification hinges on how well organizations can calibrate data inputs to accommodate regional nuances and audience demographics.

Agility in Meeting Verification Criteria

Every jurisdiction, industry, company and customer differs, and verification requirements vary to match those differences. When organizations calibrate verification processes, they take into account use cases, regulatory requirements, the risk-management approach and onboarding costs.

A simple name-phone number verification might be sufficient in some instances. Higher-risk or regulated circumstances could require verifying multiple data points and ID documents. 

When organizations quickly adjust to different verification requirements, they position themselves to maintain consistent match rates.

Match Rate Expertise

Successful identity verification programs rely on a clear understanding of the interplay among different match rate factors.

Those programs continually optimize results by mixing and matching different data sets and sources. They anticipate different data input formats and extract the right information to get the best match results. They adjust to different onboarding scenarios and tailor verification based on an organization’s needs, risk tolerance and desired cost per good, verified user.

The Importance of Continuous Data Optimization and Routing

An identity verification program flourishes with access to the right data and the ability to turn that into superior match rates. But those programs also rely on expertise and experience across markets and use cases to deliver the results organizations expect.

Intelligent Data Sequencing

The sequence of data sources significantly affects verification performance. When organizations correctly order sources to prioritize the most relevant data, they can triangulate cost, performance and coverage to optimize onboarding.

Data Optimization and Routing

Ongoing data source acquisition and optimization through a single trusted partner can be the key to preventing match rates from stagnating. Organizations can also boost those rates by leveraging AI and machine learning through that trusted partner to intelligently route to the optimal data sources for each country and use case 

When organizations rely on disparate point solutions to accomplish those objectives, the layers of integration, mapping and orchestration can hinder efficient onboarding and diminish match rates. 

A comprehensive verification platform, backed by in-house data science and expertise, can deliver the ongoing optimization that helps organizations achieve peak identity verification match rate performance.