Any economy’s financial foundation is its network of banks. They supply and manage short-term and long-term financial support to the economy as the principal credit provider for organizations, businesses, and people. Incorporating computer vision in banking will help banks function more effectively.
AI-based technologies like computer vision can automate banking procedures and processes to help humans complete repetitive activities more quickly and accurately. As a result, the processes become less prone to errors and more cost-effective.
Additionally, AI-based services can be used around the clock to offer customer support and reduce costs related to hiring human agents. Reportedly, by 2023, banks will have saved about $447 billion because of the use of AI technologies. For $416 billion, the front and middle offices will be responsible. According to a study, banking and financial services executives discovered that investing in AI-enabled them to minimize production costs by 13%. Executives also reported an average 17% rise in revenue in the areas where AI was used.
AI also aids banks in making wiser decisions when it comes to making secure loan-related decisions and managing portfolios. Banks determine a client’s creditworthiness using their credit ratings, credit history and customer references. AI can be used to analyze customer patterns, behaviors and a broader set of indicative data to decide whether a customer with a poor credit history might still be a good candidate for credit at present. The use of computer vision in banking can add a further layer of convenience and reliability to banking operations.
KEY APPLICATIONS OF COMPUTER VISION IN BANKING
Security
The most obvious application of computer vision in banking is security, not just for the physical premises of banking institutions but also for other components such as mobile banking apps and ATMs. The use of computer vision-based security solutions can strengthen the security of these systems by enabling multi-factor authentication that includes facial and retinal scans. Moreover, computer vision can also be used to analyze security camera footage to prevent robberies and other mishaps within a bank’s premises.
Data entry
Accurate and speedy data entry for various purposes, from updating customer information to recording paper-based transactions is another advantage that computer vision can bring to both banking providers and customers. For instance, computer vision systems can be used to verify physical documents before approving address-changes or can be used to scan physical invoices and forms to record important data pertaining to customers and transactions.
The use of computer vision in banking can drastically lower the chances of fraudulent activities and help protect consumers as well as businesses. It will open up a wealth of options for banks to win customers’ trust while reducing time-consuming procedures in the financial sector. As most of the services will be digitized with practically no human participation, it would help banks reduce their expenses and save time. As a result, if this technology is used correctly, taking into account both its benefits and drawbacks, computer vision has the potential to do great things in banking.
