How Machine Learning helps with KYC verification & Fraud Prevention

machine learning

A larger number of businesses are now turning towards KYC verification services. This corporate strategy safeguards them from encountering users with fake credentials and ensures fraud prevention. The bounds of KYC verification and what kind of documents are used to offer such identity verification services are entirely dependent on customers.

They take into account regulatory guidelines and nature of their business before choosing specific verification service that they want a KYC software to perform. Several KYC service providers have introduced new features and technologies to introduce greater flexibility and scalability. Some have arranged for multiple verification services in a single verification cycle, others have customized KYC verification into different modes.

But the most significant variant introduced in the market is a KYC software that uses machine learning and Artificial intelligence. Shufti Pro is one such bespoke ID verification product that has integrated machine learning and AI into its services.

What is Machine Learning?
Machine Learning is a form of Artificial Intelligence that makes use of large data to help a specific programme or machine to perform certain tasks. It reduces the need of being programmed for individual uses cases and programming events. Machine Learning also reduces the computational time, substantially.

Machine Learning for KYC verification
Machine Learning has a lot of advantages for software and applications, especially those that tend to handle large data. KYC software performing identity verification services also has the responsibility to verify millions of data points. So a KYC verification service integrated with machine learning algorithms is a best use case for this smart technology. It opens up a lot of verification avenues and transparency opportunities for businesses. Most importantly, a KYC software or an identity verification service using Machine Learning algorithms will be able to verify the identity of users much more quickly. This seems to be the ultimate benefit for KYC industry, that is otherwise haunted by sloth-like speed for verification statuses.

Fraud Prevention – The Efficient Way
KYC verification service built upon machine learning does not only perform faster but it also provides different ways to curb online fraud. Various new services can be introduced inside the working mechanism of an online identity verification system with the help of machine learning technology. Services like Facial recognition can perform excellently when supported by machine learning algorithms. Document verification can become more comprehensive and checks for various safety features can be integrated easily. Matching of a real-life image with the image displayed on an official identity document also becomes totally hassle free, once machine learning takes over the verification process.

Larger Data, Easier Processing
The most interesting aspect of the partnership between machine learning and KYC verification is the smartness impact. It means that a larger volume of identity verification will result in quicker processing speed for the KYC software.

So, even if a customer is not satisfied with the initial time taken by a machine learning KYC service provider to complete a verification cycle, rest assured that once the system will be put into production mode, the speed will go higher and verification time will gradually start coming down, leading to a point where KYC verification will be completed in real-time.

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