How to improve your online user identification process

This is a sponsored article brought to you by OCR Studio AI.

An online user identification process is critical in any software requiring logins to access its features. Authentication ensures that the person logging in is the rightful account owner. It safeguards personal data and reduces the risks of fraud. 

User identification ensures the privacy and security of the system. For instance, online banking often utilizes two-factor authentication to restrict access to sensitive information to verified users only.

Many countries also have regulations requiring financial institutions to implement KYC (know your customer) measures. Systems without proper authentication could become vulnerable to malicious attacks, leading to data breaches, credit card fraud, and potential legal implications.

Accommodate different user types

Picture this: someone attempts to sign up for your service but quickly runs into a hurdle, they can’t follow the instructions. While it’s not an impossible issue to fix, you’ve likely just lost a potential customer. To address this, think about whether you can support users no matter their device, accessibility requirements, language, or location.

This doesn’t mean you need to accommodate everyone, restricting access based on certain device signals or locations might be necessary for security reasons. However, it’s crucial to support the needs and preferences of your target users. With that in mind, ensure your IDV provider’s global reach aligns with your business objectives.

Provide several authentication methods

Support for multiple document types and verification methods can help minimize delays and reduce user drop-offs. For example, if you require government ID verification, it benefits users when you accept a variety of options such as driver’s licenses, state IDs, national IDs, or passports.

Leveraging modern identification methods like an ID scanner for mobile driver’s licenses and e-passports can streamline the process. These electronic IDs not only accelerate verification but also limit the personal information shared with the requesting organization and help prevent errors caused by unclear or low-quality images.

Categorize users according to risk level

Adopting a progressive, risk-based segmentation approach balances verification, conversion, and user experience. By understanding the risks unique to your organization, you can group users according to their specific risk indicators and tailor their experience dynamically when needed. The signals you consider and their relative importance may vary, but possible risk indicators include:

• Active signals: Information provided directly by the user, such as their name, Social Security number, identification documents, or a selfie.
• Behavioral data: Insights gathered from how users interact with a website or application.
• Passive signals: Data collected without input from the user, such as their IP address or browser fingerprint.
• Third-party data: Information from external sources like certified databases, watchlists, adverse media reports, and detailed risk analyses on addresses, emails, and phone numbers.

User segmentation may be necessary to meet specific regulatory requirements, such as verifying age.

Request only what’s necessary

The risk-based segmentation and verification process helps determine the minimum information users require. For instance, onboarding new users could be treated as a low-risk activity, where you only ask for a name and phone number to start. A phone risk report can then be run discreetly in the background, enabling users to proceed smoothly or prompting you to request additional details based on the findings.

This flexible method ensures you can identify potential threats while minimizing friction for low-risk users. Once onboarded, you can introduce further verification steps at key moments, such as when users conduct specific transactions or update their account information.

Maximize automation

Automating identity verification offers numerous advantages for both organizations and users:

• Boosts conversion rates
• Supports organizational growth
• Protects user data 
• May reduce bias in decision-making
• Enhances the customer experience 
• Cuts down on the need for manual application reviews

With advances in computer vision, machine learning (ML), and other forms of AI, implementing these solutions has become more accessible. For example, users uploading a photo of their ID alongside a selfie might value the convenience of automated image capture (removing the need to press a button) and having forms pre-filled using the collected data.

Behind the scenes, these automated systems extract details from the ID, compare the document photo with the selfie, run database checks, and determine whether to approve, block, or request further details from the user, all within seconds, thanks to automation.

Endnote – how to improve your online user identification process

With the rise in online interactions and transactions, safeguarding customer identity is crucial to any business operation. By adhering to these best practices and continually enhancing your identity verification process, you can secure your customers’ sensitive data while strengthening trust and bolstering your company’s reputation.