How AI is helping to Fight Identity Fraud

As cyber technology is becoming a part of our daily lives, and more and more people are using the internet, identity theft incidences are growing at an alarming rate. Millions of people are victims of identity theft across the world. Most of these involve stealing credit card and bank details and personal information, including social security numbers, which the rogues use for opening new bank accounts or credit accounts. In many cases siphoning of money from bank accounts and fraudulent use of credit cards leave users helpless. Hackers stealing personal information can use it for blackmailing the victims too.

Over the last few years, US consumers have reported the highest number of identity thefts to FTC, which now tops the crime chart. And the number is growing every year. In 2017, the number of US adults falling victim to identity theft rose to 16.7 million, an eight percent increase over the preceding year, as revealed in a study named identity fraud Study 2018 conducted by Javelin.

AI can help to protect against identity theft

Criminals use advanced technology to dupe users. The same kind of cutting-edge technology based on AI or artificial intelligence can stop hackers and criminals on their tracks and protect users’ personal and sensitive information. For example, the company Identity Guard offers identity theft protection packages based on the use of AI which monitor the systems and process millions of data to alert users about possible threats. The company derives its strength from its commitment to stay updated with the latest technology to protect user interests.

How AI works in protecting the identity

AI derives its power from machine learning and can scan various identity documents like passports, driver’s licenses, social security cards, etc., to test different ID elements remotely with mobile devices or on premises.  A typical example of an authentication test is the confirmation of the security threads and genuine microprint text, validation of special paper, and ink. It also includes data validity tests, comparing barcodes, magnetic strips, OCR, and facial recognition or biometrics to link the credential data to the individual.

Automation leads to accurate and faster data processing

Rather than humans verifying the documents that leave enough room for errors and takes a longer time, machine learning ensures a more accurate and error-free authentication of data at lightning speed. Typical AI-based identity theft solutions contain an internal data collection mechanism that remains anonymous and can gather and store information about software operations. This data reaches the provider daily that helps to maintain surveillance and keep the users protected. Automation improves the quality of results and saves time.

The purpose of data identification by using AI that relies on machine learning is to distinguish between good and bad IDs most efficiently. However, it requires system supervision to ensure that the algorithm’s logic does not exclude genuine identities. Even valid IDs might not pass the tests for various reasons like manufacturing defects or errors, wear, tear physical damage of any type, and variations in the cards’ production process.

Author’s Bio:

Pete Campbell is a social media manager who has worked as a database administrator in the IT industry who always describes and suggests using Identity Guard. He loves to travel, write and play baseball

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