Even if identity theft is a rising worry, it has a solution. This article will guide that artificial intelligence (AI) and machine learning is an ideal way to minimize identity theft risk.
Identity theft has turned into big trouble all across the globe. Over the past few years, the world has witnessed several unexpected identity theft cases that include the case of Abraham Abdallah, Gabriel Jimenez, Phillip Cummings, Andrea Harris-Frazier, and more.
Although these cyber-criminal acts have alarmed law enforcement agencies around the world and forced them to make strict rules and regulations, the identity theft issue is still growing at an alarming rate.
Identity theft is a rising worry, especially for those businesses that gather personal information from their customers. In the same way, it’s a big concern for consumers who share their private information with such companies in any form.
In a survey conducted by TransUnion, 83% of consumers admitted that they are concerned about identity theft. They said they might become the victim of identity theft within a year or two by having their data stolen from a business.
So, what’s the solution? How can businesses take the identity security of their consumers and staff to the next level?
Well, AI or artificial intelligence seems an ideal solution to minimize this risk. Since AI facilitates computer systems to make a human-like decision, the technology can be utilized for identity verification and fraud deterrence. Let’s get to know more about it in the following sections.
Identity Authentication with Artificial Intelligence & Machine Learning
AI and its subsets of machine learning are taking the identity authentication process to a whole new level. Machine learning lets you establish a powerful identity verification system that requires negligible human interference.
Machine learning-based identity authentication systems are intended to conduct faster and better identity verification than a human.
Let’s have a quick look at some of the significant features of artificial intelligence-enabled identity verification solutions.
- Since machine learning ID verification solutions make decisions based on their past experiences, they can continuously learn and correct themselves whenever required. However, for the same, you will need to provide them accurate data and training.
- Artificial intelligence can be combined with human intelligence to improve the verification process and make it effortless.
Is the Use of Machine Learning in ID Authentication Effective?
Machine learning can prove very competent when it comes to identity fraud prevention. Not only machine learning-based solutions are user-friendly but also capable of identifying the difference between good and bad IDs.
In addition to this, these fraud prevention solutions can expose fraudulent patterns that are not easily detectable by humans or traditional methods.
Since machine learning doesn’t rely on a set of rules to detect frauds, instead of acts according to the behavior of a person, it can determine even if a thief develops a new fraud technique.
Machine learning makes the authentication process exceptionally easy. It supports an internal data collection machinery that stores information on the identity authentication process and then shares this data automatically with the responsible authority. Thus it saves time.
As different types of documents such as passport, military ID, driver’s license, resident card, and more are used as proof of identity, understanding these variations can be challenging for standard software or identity fraud application. However, AI-enabled identity verification depends on the collection of metadata on the different document-verification process.
Indeed, the metadata does not contain information about the document being processed; instead, it encloses the information about the authentication processes and their outcome.
By examining this data, machine-learning software teaches itself to detect complicated patterns and produce correct results.
Unfortunately, sometimes machine learning solutions don’t work correctly, especially when it comes to verifying IDs that are physically damaged or contain minor manufacturing errors such as slight changes in design.
To cope with such situations, you must teach your machine learning program or computer to verify IDs that are worn and damaged but valid.
In the past couple of years, machine learning has been proved to be extremely helpful in detecting online frauds as well. As a result, numerous online businesses have started using this technology to determine problematic online purchasing behaviors.
Deep-Learning Biometric Solutions for Identity Management
Biometric identity verification is a popular method to authenticate an identity. Usually, the process involves voice or facial recognition. This user-friendly identity verification method eliminates the requirement of using personally identifiable information (PII) and remembering the password.
Biometric security solutions use deep learning to process complicated information such as faces and languages.
With the help of deep learning, biometric face-recognition technology matches the image of an ID document with a person’s face. Since it uses complex algorithms, it can easily analyze various other patterns, such as the shape of the eye, mouth, and nose.
At last, it gives output that specifies whether or not the image matches with ID’s face.
Automated System with Human Supervision is the Highest Accuracy
If you want to achieve the highest accuracy in identity authentication, you can’t merely rely on automated systems.
Don’t forget that they are machines, not humans, and they might fail to identify complex identities. Although automated systems are designed to identify different data points, they can’t replace humans – at least for now.
A human eye can better identify variations in IDs due to damage and manufacturing defects. So, to achieve the highest accuracy and avoid bad customer experiences, use human supervision and automated fraud detection together (find this solution in our Startup and Business packages).
Identity fraud is a big issue. The number of data breaches and fraudulent transactions has dramatically increased over the past few years. According to a report, identities of around 60 million Americans were wrongfully obtained in 2018. Another study reveals that every 2 seconds, a new person becomes the victim of identity theft.
Although machine learning and artificial intelligence are playing an important role in helping businesses fight against identity fraud, they still have a long way to go. However, it can’t be denied that with the proper human support, they can fight against complex identity frauds even at this stage.
If you’re in search of an advanced identity verification service for your business, we have got your covered, contact us. At iDenfy, we help you minimize frauds and make your business smoother and profitable. We have a wide range of automated identity verification solutions, including face recognition, liveness detection, identity document check, and more.