Manual vs. Automated Document Verification

Document verification can be done manually, with trained employees checking identity documents, or automatically, using software and specialized devices to read, validate, and authenticate documents.

This article explains how manual and automated document verification differ, how automated checks work, where they are most useful, and when human review should still stay in the loop.

Document verification is the process of verifying the validity and authenticity of passports, driver's licenses, ID cards, and other ID documents. It involves examining the document to ensure that it is not counterfeit, tampered with, obsolete, or expired. 

The thoroughness of the process depends on the specific situation in which it is required. There are three stages of this process in terms of the depth of verification:

In the latter two scenarios, specific characteristics such as stamps, watermarks, lenticular printing elements, fonts, and other security features are investigated using hardware devices and dedicated software.

First and foremost, verifying documents is mandatory for governmental institutions, including border control services, immigration departments, unemployment agencies, and other social organizations responsible for paying benefits and allowances. The goal is to ensure that only authorized individuals are granted access to their services, facilities, or territories.

Second, document verification is a prerequisite for industries tied to KYC compliance requirements. They include: 

• Banking, Fintech, and any other finance organizations

• Telecom companies

• Travel and Hospitality

• iGaming & Gambling businesses

• Insurance providers

• Vehicle sharing companies

• e-Learning platforms, etc.

Last but not least, document verification is essential for organizations handling sensitive personally identifiable information. A good example is healthcare institutions.

Manual verification may be enough when document checks are rare and low-risk. Automated document verification is a better fit when speed, scale, fraud detection, and auditability matter.

In the first scenario, it’s an employee's task to ensure the ID is legitimate. This can be effective in small-scale scenarios, such as a front-desk check at a local service provider or an age check in a small shop.

Automated document verification uses software and, in some cases, purpose-built hardware to do most of the verification work. The system can capture the document, assess image quality, identify the document type, extract data, check formats and security elements, and flag suspicious cases for review.

Note that automation in this case doesn't eliminate a human from the loop, but does most of the heavy lifting. For instance, identity verification software built into a bank’s mobile application checks a customer's ID in seconds. However, when one or more checks fail, the software can notify a manager, who can provide additional manual verification of the document image.

For example, passport control cannot rely only on visual inspection when thousands of travelers must be processed quickly, and the cost of a missed fake document is high. That’s why automated document verification is a commonly used practice at land and air border crossing checkpoints. The personnel are equipped with specialized devices, such as passport readers for instant checks and video spectral comparators for more detailed examination by forensic experts. 

Airlines and carriers also need automation to reduce queues, avoid manual data entry, and keep passenger workflows moving.

In banking and fintech, video interviews or manual document reviews can slow down onboarding and increase compliance costs. Automated checks help verify documents faster while escalating risky or failed cases to a human reviewer.

Age-restricted goods and services are another area where document verification is a must. While manual checks may be commonplace in corner shops, big alcohol and tobacco retailers may consider age verification automation as an alternative. The potential benefit will depend on sales volume and expected ROI.

Manual document verification may seem like a more affordable alternative for some companies. However, labor costs for employees, even if they are outsourced specialists, are usually higher than the cost of licenses for automated verification.

Additional risks are associated with the more sophisticated document forgery schemes fraudsters use today. Experienced specialists can still spot mismatches in physical documents by manually checking them, but even experts use specialized devices for this; machines can detect the tiniest details on documents that are beyond human vision.

Remote flows raise the bar further, because reviewers work with images or scans rather than physical documents.

Document verification using automation tools includes four main steps:

Let’s have a look at each of them:

Step 1. Document capture

At this stage, a device or software application should recognize the submitted document and assess its quality, including text and image clarity, size, and form. 

This step also impacts overall UX from the very beginning. The solution must guide the user through the image capture process to achieve the best shot. The better the image, the more accurate the verification results. 

When choosing a solution, see how many users are asked to retake an image. The higher the number, the worse the UX is.

Step 2. Document assessment

During this step, the solution accesses the document template database to validate the data. The bigger it is, the wider the possible use cases, and the more document types and countries it can read and verify. 

Document verification tools assess the presence of security features such as MRZ, barcode, and RFID chip. They can also automatically identify the type of the submitted document, for example, a Swiss passport or a Utah driver’s license.

Regula Document Reader SDK relies on Regula’s extensive document template database, the largest in the world, compiled and regularly updated by the company's experts. It’s not just composed of driver’s licenses and passports — the solution verifies many other types of identity documents, as you may also want to verify ID cards, voter cards, or work permits, for instance.   

Step 3. Data extraction

Once the software gets the data, it’s time to read and cross-validate it. Employing OCR technology, the solution extracts and reads the data from the Visual Inspection Zone (VIZ), MRZ, barcode, and electronic chip. It is important to consider how many languages a tool supports, especially if you need to process identity documents issued in countries with non-Latin alphabets.

Step 4. Document verification

Once the data is extracted from the various elements, it should also be cross-checked across the sources to ensure consistency. For example, Regula performs document number format analysis, date validity and correctness checks, static text validation, blank deprecation detection, barcode and MRZ format checks, and server-side NFC verification of the embedded RFID chip. It also checks whether data is present or absent in the mandatory fields on the data page. 

In a hardware scenario, authentication can also be performed in different lighting modes, such as IR, UV, and coaxial light. 

Note that different vendors implement different sets of checks in the document verification flow. As a customer, you should clarify what parameters are verified in each case.

In a nutshell, yes, you can. There are at least four reasons:

1. Reducing human error to zero

The manual verification process may involve personnel, such as casino administrators, who are not forensic experts. As a result, the quality of checks may be impaired due to a lack of knowledge of what to do and how to do it. 

Automated solutions can fill this gap. They investigate each tiny detail and detect the slightest discrepancy, such as a relocated or resized element. For example, Regula Document Reader SDK can identify inappropriate font size and placement on a passport, driver’s license, or other ID document.

2. Proven verification process

The process behind automated document verification follows a precise sequence of actions, supported by best practices in information security. It’s based on guidelines that describe each step of the process, including, for example, the logging format (the way machine-readable data should be structured, encoded, and stored). 

There are two core standards: Technical Guideline BSI TR-03135 from the German Federal Office for Information Security (BSI) and ICAO Doc 9303 about machine-readable travel documents. 

Both guides are widely used across different industries, including non-regulated ones, as the basis of document verification procedures. Compliance with these standards is a must for identity verification solution vendors as well. 

3. Extensive knowledge base

Hardware and software solutions use extensive document template databases as data sources and “know” more about identity documents, including foreign ones, than your employees do. 

A regular bank clerk can hardly imagine what an Albanian ID card or an Uruguayan driver’s license should look like. But advanced software such as Regula Document Reader SDK knows for sure. Thanks to the database, which includes over 16,000 document templates, the solution can verify ID cards and passports from 254 countries and territories.  

4. In-depth analysis and fraud detection

Automated document verification usually includes more steps than a manual check. Using specialized devices and software enables deeper analysis of captured data, such as MRZ reading and document liveness detection. Also, an automated verification session may include additional authenticity checks to ensure all security boxes are ticked.

The fact that automated document verification is now a legal requirement in some industries, such as Aviation and Border Control, further confirms its reliability.

At the end of the day, a document flagged as questioned by an automated solution can be submitted for additional manual verification. So, you can always perform double checks involving in-house or external experts if necessary.

The right document verification software should match your risk level, document coverage, user journey, and deployment requirements. A simple OCR tool may be enough for data entry, but regulated or fraud-prone workflows need deeper checks.

Before choosing a vendor, look at:

• Document coverage: Which countries, territories, document types, and document versions can the system recognize and verify?

• Data sources: Can it read data from the VIZ, MRZ, barcodes, and RFID chips where available?

• Authenticity checks: Does it validate document formats, security features, expiry dates, mandatory fields, and data consistency across document zones? Can it confirm document liveness in remote scenarios?

• Image capture quality: Does the system guide users through capture and reduce unnecessary retakes?

• Fraud detection: Can it flag altered documents, suspicious scans, obsolete blanks, inconsistent data, or other signs of tampering?

• Biometric verification: Can document verification be combined with face matching and liveness detection when you need to confirm the document holder?

Automated document verification is a game-changer for businesses looking to streamline their processes and stay compliant with industry regulations. By automating this task, companies can save time and money while ensuring the accuracy and authenticity of document checking. Whether you're in Finance, Aviation, Insurance, or any other industry that requires document verification, automation is the way to go. 

Regula's solutions for automated document verification can help you meet all requirements, while making the process simpler and smoother for your customers. Embrace automation and enjoy its benefits by checking out a free trial or requesting a demo.