Automated Background Screening: How It Works & Top Benefits

Background screening is a critical step in the recruitment process. But traditional methods of manual background checks can slow down hiring and increase risks in your talent acquisition.

New automation technologies are transforming background screening – making it faster, more accurate and helping organizations like yours minimize bias.

In this comprehensive guide, we‘ll explore:

What automated background screening is and how it works
The challenges and pain points with manual background checks
Top benefits of intelligent automation for screening
How you can implement automated background checks in your organization
Key factors to consider for fair and unbiased screening
The future of automated background verification

Let‘s get started.

What is Automated Background Screening?

Background screening refers to the process of checking and verifying information provided by applicants during hiring. This typically includes validating elements like:

Identity
Past employment
Education
Criminal history
Motor vehicle records
Credit history
Sanctions list verification

Traditionally, this has been a manual process requiring extensive time and effort from recruiters.

However, intelligent automation technologies are now enabling organizations to complete background checks faster and more efficiently.

Automated background screening utilizes technologies like artificial intelligence (AI), robotic process automation (RPA), blockchain and integrations to automate various tasks involved in the background check process.

Key Technologies Powering Automation

Here are some of the main technology categories driving automation of background screening:

AI tools like natural language processing (NLP), computer vision and intelligent document processing to extract information from unstructured data and documents.
RPA bots to automate repetitive processes like data collection, verification, notifications and reporting.
Blockchain to create tamper-proof, shareable records that enable instant verification of credentials.
Integration platforms to connect background check systems with applicant tracking systems (ATS), HR databases and other tools.

Automating Background Screening Workflows

These technologies help automate a number of manual screening workflows:

Automatically collecting consent from applicants for initiating background checks.
Aggregating data from various sources like court records, education institutes, credit bureaus, previous employers, etc.
Digitizing paper-based records using OCR and document processing.
Autopopulating input forms with extracted data.
Cross-verifying applicant data against multiple sources to identify discrepancies.
Generating consistent background check reports quickly for reviewers.
Securely maintaining verification records and audit trails.
Scheduling periodic background checks and automated alerts for employees.

This provides a standardized and streamlined approach to background screening versus slow, disjointed manual methods.

Challenges with Manual Background Verification

Manually conducting background checks comes with several downsides:

Time Consuming Process

Background checks through manual searching, data gathering and verification can take 4-5 days on average according to estimates – sometimes even weeks.
Critical hiring decisions get delayed as a result, hurting your competitiveness. Research shows 60% of candidates are lost to competitors due to delays in hiring.

Prone to Errors and Inconsistencies

Manual processes rely heavily on humans, which increases chances of misinterpreting data, overlooking red flags or entering wrong information.
Lack of standardized procedures also leads to inconsistencies in background checks on different candidates.

Difficult to Customize for Different Roles

Tailoring screening procedures to specific jobs or candidates is challenging without predefined, automated processes.
Nuanced considerations can get overlooked during manual background checks.

Risk of Biases and Discrimination

Recruiters may inadvertently favor certain candidates if guidelines are unclear, or penalize minor offenses disproportionately.
This can lead to claims of employment discrimination under Title VII of the Civil Rights Act.

In fact, over 65% of recruiters admit having hired candidates who misrepresented information because manual background checks took too long or were inadequate, according to Checkster.

Automated solutions can help plug these gaps.

Benefits of Automated Background Screening

Intelligent automation delivers significant advantages over manual processes for background verification:

Faster Screening Turnaround Time

AI tools can quickly mine thousands of structured and unstructured data sources and accelerate information processing.
Bots can work 24/7 to slash background check times from days to just hours in some cases.
Blockchain verifies credentials instantly through digital records instead of manual verification.

For instance, the University of Melbourne reduced degree verification times from 7-14 days to just seconds using blockchain-issued digital degrees.

More Accurate and Consistent Screening

Automated workflows apply standardized, compliant processes for every candidate. This minimizes variability in checks.
Automation reduces reliance on error-prone human processing, improving accuracy.
Structured processes also result in complete, auditable records, reducing compliance risks.

Helps Minimize Biases

AI algorithms objectively assess candidates based on factual data versus subjective human criteria.
Automation provides clear audit trails and consistent procedures that help reveal and tackle biases.

Over 70% of Americans want employers to limit automatic disqualification based on minor offenses to tackle racial and social inequities according to a Kelly Services survey.

Allows Continuous Monitoring

Automated solutions can enable continuous screening for employees, beyond just the hiring stage.
Bots can regularly check for any criminal record or sanctions list updates and alert reviewers.

However, employers must inform candidates and obtain consent as per FCRA and state laws.

Flexible and Scalable Screening

Automated platforms make it easy to customize checks based on type of job, risk level etc. with configurable bots.
Process automation also allows background screening to scale seamlessly across large applicant volumes.

According to estimates from Jumio, manual verification results in costs exceeding $100 per applicant. But automation brings this down to just $15, an 85% reduction.

Implementing Automated Background Screening

Here are some key steps to shift to automated background screening:

Assess Current Processes

Document your current background check workflows end-to-end. Identify the most manual, complex areas.
Gauge process efficiency metrics like cycle times, accuracy, compliance, costs etc. This provides the baseline.

Select the Right Automation Tools

Look for platforms that integrate APIs, RPA, AI and blockchain built specifically for background verification.
Carefully evaluate capabilities to automate your specific use cases like criminal checks, identity verification etc.
Ensure the tool allows easy connectivity with your ATS, HRMS and other recruitment systems.

Start with a Pilot

Plan a phased rollout starting with a limited pilot of high-volume, repetitive tasks.
Gradually scale automation across all process areas and candidates as you realize benefits.

Monitor for Biases

Periodically review automation results to ensure unbiased, compliant decision making.
Refine algorithms to address any demographic skew or discrimination.
Maintain human oversight over platform operations.

Comply with Regulations

Account for regulations like FCRA, EEOC, GDPR etc. in your automated workflows.
Continuously screen candidates only after taking proper consent.

Train Staff on Using Automation

Educate your recruiters, HR personnel and other staff on how to work with automated background check systems.
Encourage adoption by demonstrating benefits like faster hiring and reduced workload.

Key Factors to Consider for Fair Automated Screening

While automation offers many advantages, you need to be mindful of certain aspects to prevent unfair treatment:

Avoid over-reliance on public records: Arrests or convictions may not always accurately reflect a person. Consider individual context.
Focus on directly job-related offenses only: Only take into account offenses with a clear nexus to job duties for fairness.
Implement processes giving candidates a chance to review and dispute findings: Automated notifications and multi-stage reviews prevent mistaken disqualifications.
Have humans review all automated decisions before finalizing: Minimizes unjust outcomes.
Regularly tune algorithms to remove demographic and other biases: Audit for disparate impact across gender, race, age etc. and refine models accordingly.

The Future of Background Screening

Intelligent automation is transforming traditional background screening in multiple ways:

Wider adoption of tamper-proof digital credentials like blockchain-verified degrees is replacing manual checks. More than 500 universities have participated in blockchain credentialing initiatives as percredential engine Credly.
Use of predictive analytics to flag potential issues early. Advanced algorithms can assimilate a variety of employment, criminal and other data to forecast future risks.
Broader background data harnessing wider variety of sources like social media, court transcripts, personal references etc. beyond basic history.
Personalized assessments with background screening tailored to each role’s unique requirements using smart questionnaires and custom checks.
Continuous monitoring with ongoing screening of employees using automated scheduled updates instead of just one-time checks.

However, human oversight will remain crucial to prevent excessive intrusion into personal histories or discrimination through automation. Transparency and strong data governance practices are vital.

Key Takeaways

Automating background screening delivers numerous benefits over manual processes:

Accelerated turnaround: AI and RPA slash processing times from days to just hours.
Improved accuracy: Automation minimizes human errors and provides complete audit trails.
Reduced bias: Structured algorithms apply consistent standards across candidates.
Enhanced customization: Checks can be easily tailored to specific job needs.
Ongoing monitoring: Continuously screen employees beyond just hiring stage.
Scalability: Automation allows background checks to keep pace with growing applicant volume.
Compliance: Embedding regulations like FCRA into automated workflows minimizes legal risks.

Start small by first automating highly repetitive tasks, before expanding automation across end-to-end workflows. Monitoring operations and refining algorithms is key to prevent unintended bias.

Intelligent automation delivers huge advantages over manual methods for accurate, unbiased, and rapid background screening critical to hiring success.