By Gairika Mitra, Tech Enthusiast
A technology that has been leveraged by most sectors over the years, Computer Vision has been expanding on a global scale. While it was discovered in the early 1970s, it had gained ground with the advent of Optical Character Recognition (OCR), in order to extract data from scanned images. Computer Vision further assists computer or any other devices to analyse images, videos, and other visual inputs. Mostly recognised by facial recognition in mobile apps, and it has also been deploying the image display of social networking sites.
Quite often Facebook has been leveraging computer vision in order to improve the quality of images and videos, the most recent one includes integrating Computer Vision in Tesla’s self-driving cars. Researchers state that the market share of Computer Vision is expected to grow by $17 million by 2025, with an expected CAGR of around 25.40% between 2019-2024. Most researchers have opined that this kind of technology must be utilised in the Banking, Financial Services and Insurance sector (BFSI) that could be helping in mitigating fraud, increasing cybersecurity, customer experience, sentiment analysis, and back and front office processing.
Increase in Frauds and Scams in the BFSI sector
The past few years have stated that the global banking sector has been grappling with an increase in frauds and scams. This was even after stringent measures that were being deployed, the BFSI sector as a whole has been continuing to be threatened by fraud. These scams have disrupted the operations in the sector that have led most consumers to lose their faith in banks. Deploying Computer Vision techniques like that of facial recognition and biometric authentication could help in improving the internal security, mitigate scams and frauds.
KYC Processing Could Become Easier
Most banks face the key challenge of identifying fraudsters or scammers in the early stages of transactions. Herein, Computer Vision could be leveraged for enhancing the Know Your Customer (KYC) service, so that one can effectively identify and match the users’ profile. Also, mostly the BFSI sector performs tasks that are time-consuming and mundane. By using Computer Vision, document classification could be automated, and data extraction process could be used for enhanced, efficient and accurate operations.
Improvement in Commercial Banking
Most commercial banks utilise the traditional OCR software that helps in reading the documents, scanning documents, and also extracting data from the scanned documents. Computer Vision could be used in reading different templates that would be helping in delivering a promising result of accurate data classification, efficient data extraction and improved data processing.
Most insurance papers that require identifying the ideal and immediate candidature for insurance is indeed a tasking process. Also, this involves a process of huge documentation and paperwork that would be fulfilling the protocol of granting insurance. Additionally, the physical verification of assets requires too much time, in which Computer Vision could be leveraged for insurance companies that could be helping insurance companies to remotely analyse the images of properties and assets for which the insurance is to be given for.
The BFSI sector has mostly been providing a positive outlook on Computer Vision. Most researchers believe that the banks and insurers must be exploring the option of deploying Computer Vision in their operations.
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