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There is no denying the fact that ID theft has become one of the most feared threats in the digital world today. As the number of high-profile data breaches are on the rise, security has become a greater concern for individuals and organizations alike. KYC norms have been revised to include ID verification to enhance the security measures levied through KYC.
Through the implementation of KYC procedures, organizations can remain compliant with their regulations while at the same time, enjoying their clients’ confidence towards data security. In order to facilitate safe and secure ID verification technology, it is important to understand the logic behind the working of ID verification. This way, one can only hope to understand how ID theft happens, and what can be done to prevent such attacks on personal data.
An increasing number of organizations are rapidly arming themselves with technology, which is aimed at protecting themselves and their customers from the likes of malware, viruses, and even traditional forms of ID theft. As ways of ID theft becomes sophisticated, it is important to play the game the way any hacker would ideally do. In lieu of this, new tools are emerging almost every day, thereby helping organizations tackle the ominous threat of ID theft. The ideal question to ask is, “Is the customer really who he/she claims to be?”
Without further ado, let’s look at the top 3 trends which are taking the process of ID verification to an all-new level. This way, one can also understand the different segments in ID verification, and why it is important in the sphere of ID verification.
1. Comprehensive integration: Fintech companies are seeking the use of ID verification tools and making it a part of their KYC procedures to understand the ways to mitigate the impact of ID theft for their clients’ data. Companies specializing in the development of fintech business solutions are realizing the need to develop technologies which can help them enhance a business’s verification systems.
When it comes to changing their core processors, companies refrain from making drastic changes to their inherent core systems. Since this is an expensive decision, most of the companies are not too keen on making these changes. Instead, ID verification technologies are linking their core processors into the existing technological models, making the procedures easier to manage and undertake. Any development/running issues are addressed during the development stage, making the implementation seamless and streamlined.
2. Biometric Tech: Biometric verification has become one of the most widely recognized ID verification techniques these days. Biometric includes fingerprint scans, iris scans, and facial recognition, amongst other things. This type of technology was first introduced with Apple’s iPhone 5S launch, as it transgressed to facial recognition with the launch of iPhone X. This has increasingly been advanced and used to identify customers.
Companies have incorporated biometric procedures within their KYC procedures, which help in identifying the customers through their physical features. This is not only a cost-effective method but also a very effective solution for companies fighting the common issue of ID theft. Add the possibility of remote verification to the list of advantages, and you have a ready winner on your hands. Such are the advantages of biometric touch when launched successfully within the KYC procedures.
Biometrics can be enabled using geolocation, social media accounts, along with the traditional methods of iris, facial and fingerprint recognition. However, the most common issue faced with biometric technology is making users adopt the changes readily. Till this procedure becomes a common functionality with the common masses, it will be difficult to convince consumers to use this as a common KYC procedure.
3. Machine Learning and Artificial Intelligence work as a double-edged sword: As per the Breach Level Index, since 2013, close to 15 billion data records have been exposed to hackers. In Q1 2018, 25 million records were compromised daily, which included the likes of medical, credit cards and even financial data, along with personally identifiable information (PII). So, the question is, “How can Machine Learning and Artificial Intelligence enable prevention of ID theft?”
The answer is rather simple in this regard. With the launch of Machine Learning and Artificial Intelligence, one can enable trust across different technology enablers and service providers to prevent attacks. Using these technologies, companies can expect to keep hackers at bay, thereby allowing a wider scope of ID theft prevention.
These are the 3 trends to look out for in the world of identity verification. As we progress technologically, the trends will continue to change, thereby giving way to advanced, yet better solutions.