AI and technology are making it possible to automate more of the background screening process. But knowing that something can be automated is different from knowing where automation will actually make the process better.
Employment verifications make that distinction particularly clear. What may appear to be a straightforward task can involve researching an employer, validating contact information, determining the appropriate verification method, making repeated outreach attempts, resolving missing or conflicting information, and following client-specific instructions.
The opportunity is not simply to automate more of those steps. It is to understand where time and manual effort accumulate, then apply the right technology to make the overall process work more efficiently.
Consider what has to happen before anyone can complete a verification. First, you have to find the right source. For a well-known employer, that may be relatively straightforward. However, a smaller business with a common name and limited information can require considerably more research. In some cases, a person could spend as long as 40 minutes trying to find the right phone number.
Automation can reduce much of that research time. By combining AI with other services and data sources, we've seen the time spent on that research decrease by approximately 70%.
Once you find the right contact, you still have to reach them. Even with the correct phone number, an individual call has roughly a one-in-three chance of producing a completed verification. The person you need may be at lunch, on another call, or otherwise unavailable.
AI-enabled phone outreach can make multiple attempts at appropriate times, increasing the opportunities to reach a source without requiring someone to manually place every call. Other channels, including automated email and fax, provide additional ways to connect based on how a source prefers to respond.
Once someone responds, the work becomes less predictable. A start date may not align with the information on the order, an employee may be listed as inactive without an end date, or an answer may be incomplete or unclear. Completing the verification may require confirming what was heard, asking another question, or clarifying conflicting information while the source is still engaged.
Different client requirements add another layer of complexity. At InformData, for example, approximately 150 employment verification call flows account for different client requirements and scenarios. Introducing automation doesn't eliminate that variation. It has to account for it.
Sometimes, the right next step is a human handoff. If someone asks to speak with a person or an exception becomes too complex, the interaction can be handed off along with the information already collected, allowing the person to pick up where the automated interaction left off.
The goal is not to force every verification through an automated path. It's to keep the process moving, whether the next step is handled by technology or a person.
Finding the right contact sooner allows outreach to begin earlier, while more consistent outreach creates additional opportunities to reach the source. Questions can be resolved while the source is engaged, and effective handoffs can keep exceptions moving without losing work that has already been completed.
Together, these improvements are already making a measurable difference. On simpler verification packages, turnaround times have improved by close to 50%, with more completed verifications and fewer unable-to-verify results.
Those results come from improving multiple parts of the process, not automating every part of it. Depending on the problem, the right approach may involve AI, existing data, machine learning, traditional automation, or a person.
Bringing those pieces together can create a verification process that is faster, more efficient, and better able to move from request to completed result.
Talk to our team to see how the right combination of data, AI, automation, and human expertise can help you create a faster, more efficient verification process.