Using AI-based Tools for ID Verification
Identity theft has been growing rampantly in the corporate sector, and has become a menace. This has especially seen a rising trend with the growth of online shopping, and the incidents of online identity theft have increased rapidly. A 2019 Internet security report states that cybercriminals are using clever isolation strategies to commit identity theft and fraud. With the advances in technology they’re also using stealthier methods and diversifying their targets before committing crime. Losses resulting from fraud transactions have been running into a few billions of dollars, as recently as 2018.
Cybercriminals and fraudsters have become more adept and sophisticated in choosing their methods, and this only leads to a continuous increase in the number of fraudulent transactions and data breaches, which are already massive on periodic levels. Now, scientific research bodies all across the globe have developed and implemented various techniques based on Artificial Intelligence (AI) to identify, check, report and deal with such identity theft and data breach issues.
Artificial Intelligence, shortened as AI, and sometimes called as machine intelligence, is a simulation paradigm which enables computers and automated machines to perform human-like decisions and automate tasks and process flows on their own, based on some initial parameters and desired final outputs. These days many successful technologies like self-driving cars, search engines and facial recognition technologies are powered by AI-based techniques. The applications of AI can also be leveraged by cybersecurity gateways of institutions to prevent identity theft and false transactions.
The studies of machine learning and deep learning, which use computer algorithms to analyse available data and thus train detection models on those results, have made it possible to check, verify and authenticate user identities at scale. Some of the ways AI and machine learning are used for identity verification are:
Identity verification with machine learning
During opening of bank accounts, issuing of driver’s licenses and various other authorised documents / user accounts, users need to show their ID documents which are scanned for registration and verification. Document verification is used to check the originality of submitted documents, extract information using OCR, confirm genuine microprint text and facial recognition for matching identities.
However, the chances of forgery and theft increases in a normal online identification scenario. The addition of machine learning and automation techniques to the purposes of identity verification has created a faster , more secure and a more robust ID verification system which has made verification expertise through human senses redundant.
Features of an AI-powered ID verification solution:
To create a robust solution, the important criteria are as below:
Data is the first and foremost requirement to design, test, model and implement any machine learning algorithm, whether it be for facial recognition or a recommender system. Data is the fuel for machine learning paradigms, and it is imperative that suitable and relevant data be acquired for specific machine learning purposes.
Testing, Evaluation and Modelling
Next, it is important to define critical threshold parameters which define “approval” or “success” regardings tasks like identification. Specifically, ID verification requires a considerable number of accurate models to maintain maximum accuracy. For practical purposes, a model showcasing results with a minimum of 95% accuracy with real-time processing should be implemented.
Machine learning models require training which means that a model’s decision-making process is enhanced using various datasets and previous experiences. This way a model becomes a robust ID classifier. It is important to teach machines right from wrong.
Now, physical IDs undergo wear and tear and automated authentication checks may fail the verification. For this scenario human insights can be employed.
A hybrid approach using AI and HI
In those rare instances when automated AI fails to deliver accurate results regarding ID documents, human ID validation experts can step in and fill the gaps to maximize the detection accuracy and prevent bad customer experiences. This serves the following key purposes in the existing system:
- Identifying the key problems with the existing system
- Making the existing system better
A number of modern real-time ID verification solution providers employ AI and human intelligence in synergy to make the verification process easy and seamless, and this number is only increasing.
Augmenting ID authentication by including biometric verification
Since the rapid explosion of AI-based technologies into various technological, economic and commercial spaces, various existing technologies were pushed into the background. One of these existing technologies - biometric authentication – had not been explored much regarding online ID verification. However, facial recognition provides features like liveness detection and anti-spoofing to commercial setups whose goal is to ensure transparency at all levels on their commercial portal.
Face recognition also delivers exemplary performance as far as both onsite and offsite verification scenarios are concerned. When used in collaboration with document verification techniques, facial verification provides reliable ID services to commercial establishments who’re looking for impeccable, easily integrable and seamless solutions.
Businesses reaping a fair share of success due to their growth and appeal of ideas need to tackle the complex web of fraudsters who’re ever-present at their cyber portals. Employing AI in ID verification increases the security of commercial portals ten-fold, along with providing business with an edge over those who’re on the lookout to commit fraud. When used in conjunction with human intelligence, AI increases human ability to process data, thereby enabling businesses to process information intelligently and prevent being scammed. Even though AI-powered systems are far from perfect and need further refinement, this is the perfect time for businesses to incorporate AI-based solutions in their workflows for their better and more pronounced growth.