Five Factors for Digital Identity Verification Success

In recent years, knowing who the customer is, across channels and at all times, has become more challenging, yet increasingly critical. Detecting and deterring fraud without negatively impacting the customer experience has brought digital identity verification to the forefront of strategic considerations for businesses of all sizes. Last year, for the first time in the history of IDology’s Annual Fraud Report, identity verification was reported as the biggest challenge to combating fraud.

Each and every aspect of how a business operates is touched by digital identity verification, meaning careful consideration must be given to the right approach. The stakes are high as fraud continues to rise. Juniper Research forecasts that in 2024, there will be an excess of $44 billion lost to fraudulent digital commerce transactions, including fraudulent online purchases and bank transfers, rising from $27 billion in 2020.
With the rapid adoption of digital services and rising fraud attempts, which factors determine digital identity verification success?

  1. Frictionless onboarding
  2. Customizability
  3. Transparency and Leveraging Artificial Intelligence (AI)
  4. Control
  5. Consortium Networks

Frictionless Onboarding

Frictionless Onboarding

The abandonment rate among American consumers continues to grow steadily each year. In 2020, nearly half of Americans bailed on signing up for a new account because the process was untrustworthy or too time-consuming.

The onboarding process must be simple enough for a digital newbie, such as a senior citizen who may not use technology often, and seamless enough for tech-savvy people who want to get to the end result quickly. Regardless of a customer’s comfort level with technology, removing unnecessary steps during the identity verification process is the beginning of a positive digital experience.


Every business is different and should verify differently based on its unique needs, making it critical to have the ability to customize how identity verification tools work, based on industry, geography, customer needs and business goals. With varying regulations, business models and verification requirements, a one size fits all approach won’t work well. For example, a gambling company will see account takeover attacks used to take control of account credit. However, in lending and finance, this could be used to fraudulently apply for credit.


In each case, escalation steps and criteria should be customized to ensure they provide an effective barrier to fraud. By customizing controls, businesses can better evaluate risk during the verification process to avoid turning away potentially important customers.

Transparency and Leveraging Artificial Intelligence (AI)

Most identity verification platforms that leverage AI use ambiguous scoring that results in “black box” models and templates that don’t allow for reason visibility, data intelligence or customization. This type of scoring lacks transparency and fails to provide actionable intelligence that businesses can use to make data-driven decisions and adjustments to fine-tune identity verification processes.

Identity verification tools, data, and decisions must be fully transparent. Additionally, closed-loop data feedback is critical for explaining regulators and customers, further customizing decisioning models, and gaining valuable business insights.


We live in a world where changes in consumer behavior can drive massive shifts in fraud and how customer identities are verified. The ability to view and understand novel shifts in customer data, rework assumptions and adjust systems to higher levels of sophistication on the fly, without the need for IT, will be necessary for businesses to keep pace.

Consortium Networks

Visibility into data is incredibly valuable in fighting fraud and growing customer loyalty. It’s even more useful when shared across industries and businesses. Real-time fraud intelligence shared between companies and across industries, allow businesses to leverage the fraud mitigation efforts of others.

Consortium Networks

At IDology, we use a combination of machine learning and human intelligence to detect repeat transaction attempts across the network and flag specific attributes associated with known fraud.

Five Factors, One Path to Trust

When considered together, these factors make up a powerful digital identity verification strategy. For customers, this means a secure and frictionless digital experience that fosters trust. A safe process that gets customers verified quickly means businesses drive revenue faster.
To learn more about IDology and how we can help deter fraud and establish digital customer trust, contact us today.

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