The finance sector is becoming a victim of fraud risks. While expanding services Verification of Documents to global customers by making digital banking the new normal, they are also attracting criminals. They deploy advanced spoofing, deepfake, and identity theft techniques to exploit systems, escape regulatory checks, and launder high sums of money. Hence, identifying fraudsters during digital onboarding has become a major challenge.

In order to verify customers and the legitimacy of their funds, financial institutions need to integrate automated verification of documents. AI-powered IDV tools such as Optical Character Recognition (OCR) are making it easier to extract information and Machine Learning (ML) is limiting fraud instances by thorough authentication. This blog entails how online document verification solutions enable financial institutions to ensure risk-free digital banking. 

Online Document Validation – Solutions for Frictionless and Secure Onboarding

Financial institutions are striving to boost customer engagement and retention while embracing digitization. However, the adoption of digital banking has become somewhat risky due to identity theft, data breaches, money laundering, and inadequate verification of documents. Criminals create synthetic profiles and easily steer clear of customer identification processes. In return, financial institutions face a spike in the flow of illicit funds which further increases their chance of ending up in legal proceedings. 

Document forgery is the main factor that aids in criminals bypassing identity verification. They create counterfeit papers by using fake or identical holograms, watermarks, signatures, stamps, and other authenticity characteristics. Therefore, financial institutions need to integrate efficient document attestation solutions. With IDV solutions in place, they can accelerate secure digital banking without worrying about criminal threats. 

Online verification of documents enables financial institutions to identify imposters in real-time by using OCR for data extraction and ML for validation. This process adds an additional layer of accuracy and security to customer onboarding. In order to safeguard their digital banking operations, financial institutions often increase friction and hassle for customers. These factors are sure to drive users away as they are more concerned about convenience. However, AI-powered verification of documents automates onboarding, accelerating the adoption of digital banking. 

Working Mechanism of AI-Powered Document Verification Process

Document templates, customer verification requirements, and security standards differ across distinct jurisdictions. This makes user identification tricky as manual IDV methods are not capable enough. 

Financial institutions require AI-powered verification of documents to limit human errors, long processing times, and inaccurate results. Furthermore, automated IDV solutions are capable of analyzing different formats, templates, and legitimacy characteristics. They involve the following stages for accurate document validation:

• Checking the Validity of Papers

The first step in the online verification of documents involves validating the originality of papers. The AI-powered IDV tools look for crumbled edges and dim light while ensuring the images are clear.  

• Cross-Checking Formats

AI-powered verification of documents offers self-analyzing techniques which eliminate the need for manual interpretation. They further enable banks to access global financial databases and records for cross-validation of formats. While criminals target high-risk countries to conceal their identities and launder high sums of money, AI-powered IDV tools place necessary registration in their way. ML technology analyzes different formats and counters fraud attempts more efficiently. 

• MRZ Code Authentication

Online customer identification solutions automate the verification of documents as they rely on mathematical algorithms rather than manual interpretation. The IDV systems extract the required information by using OCR. Furthermore, MRZ codes authentication identifies forgeries or signs of tampering. Document validation tools then decode this information and cross-match it across global records for improved accuracy.

• Detects Tampering and Forgery Signs

Paper documents are prone to wear and tear. Fraudsters see this disadvantage as a key to conceal their real identities. Furthermore, it helps them perform malicious financial activities while hiding regulatory scrutiny. However, online IDV solutions restrict criminals by deploying AI-powered document fraud prevention techniques. By using ML tools, the system identifies signs of tampering with holograms, signatures, ink types, and other legitimate traits. 

• Identifies Authenticity Features  

Government-issued proof of identity documents come with distinct legitimacy features including holograms, stamps, ink color, and others. These traits are a true representation of authentic customer identities. Criminals forge legitimacy features to trick online verification of documents and avail illicit digital onboarding. In return, these fraud attempts expose financial institutions to non-compliance risks and legal penalties. However, AI-powered document verification solutions leave less space for forgeries and enable banks to safeguard their digital service. 

Key Takeaways

Customers tend to abandon complex and frictional onboarding processes. They will choose some other institutions with enhanced security and hassle-free registration. In this regard, AI-powered verification of documents reduces friction by automating user identification. Using OCR and ML lessens the time taken for customer authentication. Hence, automated document attestation solutions are a reliable bet for financial institutions to provide secure, seamless, and fraud-free digital banking services.