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How Fintech Uses Computer Vision Technology

Fintech, AI, Cybersecurity, AR/VR

How Fintech Uses Computer Vision Technology

Computer Vision is the term given to machines that can see and all the associated science and technology that helps make that a reality. In business, it’s manifested mostly in Augmented Reality (AR) and Virtual Reality (VR) applications. The fintech sector is using computer vision to boost growth, transforming financial services by using appealing visuals and helping accentuate the difference between fintech and the traditional finance industry.

Computer Vision Changes How We Interact with Numbers

In general, people make better decisions when they take on information visually, rather than through a stack of numbers. Computer vision gives people working in finance a new way to see data. In today’s financial world, when there is more data than ever, this can be invaluable when making decisions about where to move money. 

Many different companies are developing apps around computer vision. Salesforce teamed up with Oculus Rift to develop a VR app that brings data to life, creating  an immersive 3D VR environment for salespeople to visualise data, including contacts, opportunities and closed deals. 

 

Stock-City-Oculus-Hampleton-Partners

 

Fidelity Investments also created an Oculus App called StockCity. It is an immersive virtual world that visualises an investor’s portfolio, allowing them to make trading decisions based on price movements. The Polish tech company Comarch has also developed a VR trading platform. 

Whilst this sort of application is in its infancy, the potential is clear. A secure virtual world where traders can interact, making faster and better-informed investment decisions, gives investors an edge over their competitors.

Visualisation Helps Training and Education

For training up new starters in financial organisations, or equipping existing staff with new skills, computer vision has vast potential. This is because, not only do people take in more information when it is presented visually, VR and AR allow trainees to experience a situation as if it is in the real world. 

For example, computer vision could be used to place a financial trader in a virtual market to see how they would respond to a change in stock prices. VR could be used to show a new starter how to deal with a customer’s questions. The possibilities are endless. 

An additional benefit comes from being able to remove human teachers from the process after the first time a scenario is programmed enables organisations to subsequently train at scale using VR scenarios anywhere in the world, repeatedly.

Computer vision can be used to help customers too. Banks are using AR in their mobile apps to help customers find their nearest branch or ATM. 

Computer Vision Appeals to A Wide Audience

Computer vision can also be used to broaden the appeal of fintech and finance as a whole. In a world where younger people question the need for having a bank at all, anything that makes banking more accessible is desirable. 

Banks all over the world are incorporating VR and AR into their offerings, to make banking less onerous. For example, BNP Paribas developed a consumer VR app where customers can manage their accounts and payments in a virtual world.

Gaming is a sector where computer vision and fintech meet. Micropayments within games are common. As VR gaming becomes more popular, fintech companies are developing systems to meet this challenge. MasterCard teamed up with Wearality to establish a system where gamers can pay for products without leaving their virtual world

 

Golf-Masters-Mastercard-VR-Transactions

 

Finally, fintech is using computer vision to address a significant concern for consumers – security. Computer vision technology is being used to develop biometric security, verifying who people are by reading their eyes. Eventually, this technology could be used in banks and at ATMs instead of chips or PINs.

The mission of the fintech sector is to disrupt the traditional financial industry using technology and make it more accessible. Computer vision certainly helps it do that. It’s especially effective at reaching a younger audience who had previously no interest in finance – new solutions for a new world, where seeing is believing.

This article was published by:

Jonathan-Simnett

Director

Jonathan Simnett

Jonathan has been involved in the enterprise technology business for over three decades, managing and turning around existing business and helping management and their investors in fast-growth technology segments to grow, manage change, enter markets, transfer technologies, acquire, merge and sell. He’s worked with large and public infrastructure and system integration companies including: AT&T, Avaya, BroadSoft, BT, C&W, Cisco, HP, Global Switch, GMC, Huawei, Informix, Infosys, Intel, Myriad Group, Novell, IBM, IGT,  Nortel, OpenReach, Pace, TCS, and Sybase.


In addition, he has also worked with fast growth and venture-backed companies taking many to trade sale/public offering including: Calyx, Cambridge Cognition, CloudApps, Concateno, e2v technologies, Ecotricity, Engensa, free2give, Getjar, Holition, Intuwave, Interoute, Logicalis, Medelinked,  Multiven, Natural Machines, NMQA, Qinec, Socialbakers, Thorn Medical and Zomm.

He holds a Master’s degree in Science and Technology Policy from The University of Manchester, attended the Stanford Graduate School of Business and blogs on technology innovation, marketing and management  at "The World According to WestFour".