In December 2020, 4iQ discovered a single file with the personal data of over 1.4 billion people which is the largest database found to date on the dark web. What was even scarier was that none of the passwords were encrypted and the passwords that were tested turned out to be authentic. This is a major issue for all of us. A recent report published by a cyber-security firm stated that almost 80-90% of the people that log in to a retailer’s e-commerce site are hackers stealing PII (personally identifiable information). Unsurprisingly, cybercriminals use techniques that have the least resistance and they simply buy the stolen credentials from data breaches from the dark web to create fake accounts and access internal systems. And obviously, passwords alone aren’t enough.
Unfortunately, traditional methods of verification such as knowledge-based authentication (KBA) and two-factor authentication/ multi-factor authentication, aren’t enough to keep fraudsters aware of internal systems. Fortunately, the latest AI-based technologies tend to be efficient when it comes to online identity verification.
How is it possible for modern companies to evolve beyond usernames and passwords? When verifying identity matters the most (home rental, creating new bank accounts, funds transfer), companies have to add a layer of real-world ID/identity verification to ensure that the person using the username and password is the same person to whom the account belongs to. This is where artificial intelligence comes into play.
Machine learning solutions and deep learning algorithms are slowly changing the industry trends where ID verification delivers a smooth experience that doesn’t compromise a positive customer experience for security. These technologies are being utilized for online ID verification to protect your consumers and businesses against fraud and account takeover.
Artificial intelligence, machine learning, and deep learning solutions are extremely efficient in distinguishing between real and fake documents used by fraudsters. With the growth of technology, it is easy for fraudsters to build fraudulent documents including driver’s licenses, proof of address documents, passports, and so on. These documents are scanned to onboard customers during account opening. AI and Machine Learning solutions can detect even the smallest of discrepancies in the documents, including the presence of genuine microprint text and other features, these solutions can even link the individual to an ID document.
Machine learning creates a more efficient and accurate process compared to relying on an untrained eye to examine and verify an ID document. Over the last four years, there have been hundreds of ID solutions popping out that help in simplifying the overall customer onboarding and verification process.
As customer IDs are physical documents, they tend to face wear and tear and they may even contain manufacturing defects. Plus, the way those documents (driver’s licenses, passports, and ID cards) are captured also possess a challenge while verifying customers. In most cases, the cameras in smartphones and laptops fail to provide the ideal quality for AI-based solutions to read the details on ID documents. In other cases, the user takes blurry photos or clicks a photo in insufficient light. In these cases, which happens more than often, the best machine learning solutions are tried and tested.
AI, Machine learning, or deep learning-based solutions are only as good as the algorithms and the data that is fed to them. In case the data is bad, the solutions won’t be able to find out the errors in the documents.
Other solutions help in simplifying the document verification process for KYC and AML compliance. DIRO online document verification software can help in instantly verifying documents by cross-referencing them with private and government sources. DIRO online document verification software can help banks, financial institutions, crypto, and other businesses to easily comply with regulations. The technology helps in eliminating screen scraping, and other tedious tasks from customer onboarding.