Computer Vision in Fintech

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For many people, the combination of “computer vision” and “fintech” looks extraordinary mostly because the financial industry is regarded as a field reluctant to change. And that is totally understandable. The complexity of operations, the scope of services financial institutions provide and the obvious significance of human resources makes its modernization almost unthinkable and hard to implement and handle. However, computer vision technology has already captured fintech, rapidly changing the field most skeptical to innovations.

Where AI Meets Fintech

In fact, there are a lot of convergence points between computer vision and the financial industry. Almost any dimension related to money, financial data security, sensitive data and client identification, assessment of their credibility for insurance purposes, and satellite-enhanced analyses in the real-estate field already benefit from the fresh blood of AI running in their veins. Today, it is safe to say that artificial intelligence helps fintech. Let us take a closer look at how exactly all this works.

Computer Vision For KYC Processes

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KYC is short for “Know Your Client” – a comprehensive and time-consuming process of checking the identity and credibility of a person before starting any kind of financial engagement with one. Every financial institution is mindful of the risks involved in personal data verification, especially since identity stealing has been frequently detected. With artificial intelligence, such thefts become almost impossible.

Facial recognition technology detects the face of a person alone or in the crowd, analyzes its key features such as eyes, nose, cheeks and lips. Then it compares it to the database of the known faces and searches for a match. Once the face is recognized, it either unlocks the doors and lets the person in or notifies the security team so as to respond to the unwanted person on the office premises. Of course, there is more behind this, but in general, this is how facial recognition technology works. 

“A computer vision solution has to offer a two-step visual identification through a smartphone camera. Some fintech companies offer video-call verification, others ask their clients to send a real-time photo of themselves and a photocopy of their ID card. Both variants are breach-free”.

Andrei Alkhouski, a computer vision developer at InData Labs

The New Era of Banking Service 

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Banking is a blue sky, an open field for the application of artificial intelligence. Computer vision technology has already introduced a face-identification level of security for internet banking payments and made debit cards kind of obsolete. That is not an innovation anymore, that is reality. But what about being able to use ATMs absolutely hands-free? With the current epidemiological updates, some advanced banks have already placed such ATMs powered by artificial intelligence software.

They identify a user by one’s appearance with the help of face recognition. What’s more, they even can tell if a person behaves suspiciously. To detect and estimate a person’s body movements helps pose estimation technology. Both technologies are a golden nugget to tackle ATM robberies and identity thefts. According to Crosstown, crime rate at the ATM machines spiked during the COVID-19. The reports included the cases of identity thefts, vandalism, and robberies. 

To solve the problem, technology comes to the rescue. Considering the statistics, banks are thinking about integrating face recognition in the ATMs to prevent crimes. 

Another weak spot of banking, especially commercial one, is paperwork overload. The amount of time and human resources engaged in dealing with financial papers is truly unthinkable taking into account far and wide digitalization. A lot of time and effort is spent on processing documents such as receipts, claims, statements, and more. The good news is that, finally, computer vision has been given the green light to help banks make documentation processing automated and well-edged. With OCR and data capture solutions, banks can outsource repetitive tasks to the software and free employees for more intelligent work. It may improve operational efficiency, and work performance.

A Major Shift in Real Estate Business 

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You might think, how real estate and AI are even related. The answer will be, “very closely today”. Satellite imagery combined with computer vision allows real estate companies to provide their customers with more profound and informed services. Satellite images can give us much more than just a picture, they give a substantial portion of big data, that AI can process and analyze, giving out a comprehensive image of a site, building, or even a parking lot to the potential buyer without the need of actual physical presence. 

A Boost For Insurance Companies

The above-mentioned satellite imagery-AI duo is an absolute necessity for today’s insurance companies. The basic process stays the same: machine vision reads the image and gives insurers an exhaustive set of data points related to the state of a building, possible risks, and other valuable insights. You might say that a professional insurer can do the same. Yes, but how much time and other precious resources will it take to complete such a task? And if there are thousands of sites waiting to be registered for insurance? The benefits of computer vision help here are indisputable.

Enhanced Investment Strategies

Investment is another field where AI and data science play first fiddle today. As a rule, it would take months to analyze the utility and potential of a site a person wants to invest in. Now it takes a couple of days or even hours before you’re given a full-scale portfolio with profound analyses, statistics, and forecasts. Is it still necessary to mention that such a smart approach will bring to a brand new level both the profits of investors and analytical companies they turn to?

The Final Thought

Computer vision technology is irresistible. Whatever challenges there might be on its way, AI will pave its road through all of them. The key thing here is to accept the power of change machine vision brings about and not to be afraid to make way for it. It does mean you have to go for radical shifts right away. Start slow and see how your company evolves hand in hand with AI.