Successful fraud prevention starts with thorough identity verification, especially in an increasingly online world where anonymity facilitates many scams. The demand for online services and products is growing faster than ever before, necessitating robust identity verification processes to protect businesses and consumers alike
Preventing fraud is important for businesses. One key way to do this is by verifying documents, especially when bringing in new customers.
In the United Kingdom, for example, The Guardian reported that in 2023, 70% of scams occurred via social media, online marketplaces, and dating apps. From 2022 to 2023, there was a 14% increase in scams, with consumers losing more than $10 billion to fraud in the UK. This highlights the prevalence of fraud and underscores the importance of proper document verification in protecting businesses and organisations from fraudulent activities.
What is Document Verification?
Document verification is the process of making sure a document is real, correct, and used for the right purpose. This could be a bank statement, employment record, or any other type of business document. Accurate document verification helps businesses verify customers, vendors, employees, and beyond. The process usually involves four steps:
- collecting the document,
- extracting data,
- validating the document, and
- manual verification.
This method checks if documents are real, extracts information using OCR software, and matches microprint text to confirm identities.
You can use document verification software like ZignSec to verify various official documents, including:
- ID cards
- Passports
- Driver’s licenses
- Bank statements
- Utility bills
- Tax bills
- Insurance agreements
- Employment documents
- Educational documents
- Employee letters, and many more
Verification checks for stamps, watermarks, holograms, fonts, and security features to approve documents automatically. This automation saves time and effort for organisations, allowing employees to focus on providing better services.
There are two main ways to verify documents: manually and automatically. Businesses choose between these methods based on what they need. Automated document verification, often seen as superior, uses AI to verify documents faster and more accurately, with fewer errors. For businesses that operate on a bigger scale, they are often the only viable solution.
Difference Between Automated & Manual Document Verification
Manual Verification: Manual verification involves human review and validation of documents through visual inspection and manual checks. This method may be suitable for businesses that only need to verify a few documents each week or have very high security needs. However, this can be prone to errors, is time-consuming, and not ideal for handling large volumes of documents.
Automated Document Verification: This method uses technology like Optical Character Recognition (OCR), AI, and machine learning to quickly and accurately read and verify information from documents such as passports, driver’s licenses, and bank statements. This process employs rule-based techniques, NFC checks, smart data matching algorithms, and other advanced methods to ensure efficiency and accuracy.
What it also does is check whether the photo sent has been tampered with using Photoshop or other editing software. By examining the document, our software can detect if it’s fraudulent. However, as mentioned earlier, adding more layers of security reduces the likelihood of encountering fraud.
How does online document verification work?
How exactly online document verification works depends on a number of factors, including the industry you operate within and the types of documents that you are dealing with. That being said, the online document verification process can be broken down into four discrete steps:
- Document collection
- Data extraction
- Document validation
- Manual verification
Examining the background processes, here's what is occurring at the core, along with some of the key features:
- Face and orientation detection
- Edge detection and cropping
- Front to back data correlation
- Cross checks on thousands of global IDs
- Colour space analysis
- Headshot integrity
- Selfie to ID photo match
- Selfie liveness detection
1. Document collection
The first step in document verification is to obtain it from the user. This process typically involves requesting the user to capture and upload one or more photos of the document.
Upon submission, the document undergoes pre-processing and analysis to verify its compliance with the business's standards. This includes confirming that the image corresponds to the correct document and is not irrelevant, such as a photo of a cat. The image must be clear, of high quality, and capture the entire document without any cropping. Additionally, it is examined for any visible signs of alteration and to ensure it contains all necessary details for verification.
Documents that do not meet these criteria will be rejected, while those that do will proceed to the next stage.
2. Data extraction
When a user submits a document for verification, they do so by providing a photo of the document. To access the information stored within the document, the data must undergo extraction. This extraction process can be carried out using various methods, such as optical character recognition (OCR), pattern recognition, and other techniques.
After extracting all relevant data, it is then cross-referenced with the data provided by the user. For example, if a user uploads a utility bill as proof of address, the address in the document is compared to the address initially provided by the user. Likewise, the data is meticulously verified for accuracy against the user-provided fields.
Discrepancies between the user-supplied data and the data within the document should be flagged for further investigation. While these discrepancies could stem from input errors, they could also indicate potential fraudulent activity.
3. Validation of Document
The next step in the process is to actually validate that the provided document is authentic. This involves a variety of different validation checks — potentially hundreds of different checks — depending on the type of document being verified.
Common validation checks include:
- Document completion: If the document consists of multiple pages, are all required pages uploaded?
- Edge detection and cropping: Does the edge of the document appear to be cropped or tampered with in any way?
- Special feature identification: Many official documents, such as government-issued IDs, are designed with special features that are meant to be difficult to forge. This can include watermarks, holograms, stamps, foils, fonts, textures, and more.
- Colour space analysis: A photo’s colour, lighting, and shadow all provide additional context that can signal whether a document is legitimate, forged, or tampered with.
Depending if the documented is validated, the next step should be issueing a identity data verificaiton.
4. Manual verification
When a document is flagged as suspicious, businesses are presented with two options. They can either reject it outright or escalate it to a manual review process for thorough analysis by a human reviewer. While manual review is a slower and less secure method, it has the potential to greatly reduce the instances of false negatives. This process may also involve gathering additional or alternative documents for validation.
Why is Document Verification important?
In the past, a significant portion of work relied on physical verification methods, such as in-person paperwork checks or hard copy reviews. The transition to digital verification techniques and remote work practices has led to a notable shift of document verification services to online platforms. When digital identity verification becomes necessary, technology offers a precise, swift, and efficient approach to document scrutiny and ID validation.
This procedure not only verifies identities and detects underage applications but also combats fraud and identity theft. Moreover, it simplifies administrative and security procedures for individuals across diverse situations and locations globally. Furthermore, it enables seamless remote onboarding for new clients, thereby enhancing the overall onboarding process.
OCR technology in Document Verification
Optical Character Recognition (OCR) is a technology that converts printed or handwritten text from documents into digital formats, such as databases, spreadsheets, or ERP systems. When applied to ID documents, OCR extracts essential text and inputs it into a document verification platform to ensure authenticity. This technology significantly speeds up the verification process and reduces errors associated with manual data entry.
Automated Document Verification for a Better User Experience
Today’s consumers expect a smooth and effortless onboarding process. Manual, in-person document verification has become a drawback, leading to frustrated customers and a damaged brand reputation. According to The Financial Brand, 26% of customers cite excessive manual entry and the need to provide identity verification information as major pain points.
ZignSec addresses these issues by integrating document verification with ID verification, along with other customer-friendly features like KYC TrustPath to improve customer experience. This combination allows customers in regulated industries to quickly complete automated workflows in a single session. Moreover, ZignSec's comprehensive digital identity verification system helps autofill information, reduce steps, and enhance the Know Your Customer (KYC) process.