Implementing computer vision in finance proves to be beneficial to companies as well as customers in general. Although it seemed far-fetched five years ago, in their operations, financial institutions used advanced technologies. Those innovations make it possible for businesses to boost customer experience and to lighten the workload of employees. It is projected that the global computer vision market will grow to USD 18.24 billion by 2025 at a CAGR of 7.7 percent. Nonetheless, there remains a certain degree of skepticism among institutes and consumers in the financial sector’s adoption of computer vision.
Key Use Cases for Computer Vision in Finance
Machine learning is slowly but surely making inroads with major banks already exploiting their ease-of-use process in the financial sector. This paves the way for automated processes to replace the current routine and repetitive procedures practiced by financial institutions.
Using computer vision technology, a simple KYC process currently takes hours, can be reduced to minutes. To ease this process, many major banks have already begun to capitalize on computer vision technology. For example, for KYC verification, the Banco Bilbao Vizcaya Argentaria (BBVA) bank uses computer vision. Through a video call, customers can now open an account using a smartphone. The need for manual verification is eliminated by this digital verification method. From the comfort of their home, the customer can open an account. It also proves to be a win-win situation for banks as they can attract more clients and use the time and human resources saved to accomplish more important tasks.
The Reality Of Cardless Payments Is Supported By AI And Computer Vision
One of the most important aspects of using computer vision in finance is to eliminate our physical currency dependency. Computer vision can help banks to replace traditional currency, credit cards and debit cards. These are replaced by one-time digital codes on the smartphones of customers. This process eliminates the need to carry physical cards, improves safety, and fights fraud. Wells Fargo announced in 2017 that it would operate its 13,000 ATMs without debit cards, replaced by codes generated on the user’s smartphone.
Major tech companies such as Apple, Google, and Samsung have already introduced their mobile payment system to help get rid of physical card carriage. They store digitally the user’s card information that is authenticated at the point of sale (POS) by biometrics. While these payment methods do not completely eliminate our dependence on cards for now, implementing computer vision in finance can help us in the future to achieve a truly digital society.
Key Benefits Of Computer Vision In Finance
Computer vision can help eliminate financial institution paperwork, save time, resources, and money. It can replace the traditional methods used by digital process services in the finance sector. Using digital methods, opening new accounts and verifying customers can be done quickly and more efficiently. It also helps to improve time-consuming backend operations.
A simple task, like opening an account with the customer verification process can take days or even a week is tedious in today’s environment. Using computer vision enabled services, this can be reduced to hours or even minutes.
Computer vision can also help us to get closer to the dream of a truly paperless and cashless future where every transaction on a smart device is done digitally. It is possible to use devices such as mobile phones and smartwatches to perform the transaction. Further improvement in this technology can lead to a scenario where even without digital codes transactions can be completed.
Customers can use biometric data such as an iris scan to verify themselves and authorize transactions. Since iris scans are difficult to replicate, this can enhance reliability and resolve privacy concerns. Bank fraud incidents can be significantly reduced, supplying the customer with a safer and more secure atmosphere. It improves the customer’s trust in the company and may even serve to attract new customers.
Computer vision can also be used to settle insurance claims quickly and correctly, particularly in the automotive market. Using computer vision, one can determine the extent of the damage and determine whether it was an unfortunate incident or whether it was performed with malicious intent. Using cameras helps quickly and accurately verify claims. In some instances, computer vision can reduce the need for human inspectors while providing accurate data in real-time. Insurance companies can greatly benefit from this because it eliminates the likelihood of fraud and false claims
The challenges of implementation of computer vision in finance
It is not without its limitations and challenges, as beneficial as computer vision can be for the finance sector. Consumers are sceptical about the use of computer vision technologies as they still prefer the traditional methods of pen and paper for services. Consumers continue to be accustomed to traditional practices as digital services have just begun to embark on working practices.
Consumers need to be educated on the benefits of efficiently using digital services without compromising their private data. For each advanced digital service, adequate information should be transmitted by banks informing customers about the do’s and don’ts.
There are many reported instances of bank fraud whereby criminals use their card information to cheat customers of their money. To obtain their confidential details, they spam them. Such instances raise fear among customers when they consider adopting other digital services or even continuing to use their existing ones. If not stored securely by the banks, customer data can be compromised and exploited. Banks must be one or more steps ahead of the scammers and put in place rigorous practices to avoid mishaps.
There are also the costs involved in software and hardware research and development that fraudsters can not easily exploit. There is a need to invest a lot of time and capital to provide a seamless and secure user experience. Not every financial institution can afford the capital and human resources needed to be invested. Only after the technology becomes affordable can, small institutes provide their customers with the services without significantly affecting their operating costs.
Using computer vision in finance can significantly help to reduce fraud that duplicates their money to customers and businesses. In the financial industry, it will create huge opportunities for banks to gain their customers ‘ trust while forgetting tedious procedures. It will help banks cut their costs and save time as with almost no human intervention; most services would be digitized. Therefore, if implemented well, the use of this technology can perform wonders, taking into account all the advantages and limitations of computer vision.