The two main sectors of the digital landscape are now evolving rapidly with the development of technologies and improved consumer satisfaction rates. Comparatively, the importance of biometric recognition is increasing regularly as security measures have been highlighted in the past few years of progression with the increase in the crime rate of false transactions and money laundering issues.
With the Statista’s research report for the year 2023, it was concluded that the Reserve Bank of India faced an increased rate of fraud, crossing 13,000 scams. It turned around the trend of the last decade. However, the loss of banks increased from 1.38 trillion to 302 trillion Indian rupees, which was recorded as a massive loss to the banking industry. Moreover, the statistical rate coming into the limelight makes it a concerning point for other industries, including fintech and financial institutions dealing with transactions on national and international levels.
This loss led the companies to take essential measures regarding the authentication of the identity involved in the transaction to avoid such massive damage in all financial services sectors. The identification of consumers was conducted through different methods
Use Cases of AI Face Recognition in Banking and FinTech Sectors
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Customer Onboarding
With the incorporation of artificial intelligence in face recognition systems, the onboarding process of consumers got a new direction towards a better security method. The face recognition solution onboard customers quickly and effortlessly by acquiring the simple selfie to verify their identity. It includes the verification of selfies against the end-user’s photos of government-issued documents. The validation helps make wise consumer decisions to protect businesses from criminal activities.
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Electronic Banking
E-banking has increased as everyone feels it is a more convenient way to make transactions. However, electronic banking also has a risk factor due to digital transactions. The risk factors can be concerning for businesses due to increased money laundering and transaction fraud cases. To prevent the threat rate, facial biometric identifications in online banking are applied to access the banking facilities, including transaction validation and KYC screening. With the security concern of credential protection, facial recognition can be widely applied to identifying and validating consumers and business entities.
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Face Check in ATM’s
Implementing the face ID check in ATMs has made it an enhanced version of the online debiting system. The ATM machines work by authenticating end users by looking at their faces, as every entity has different facial features. The facial recognition scanner scans the face with the sensor embedded in the system. The main goal of implementing these check methods is to secure ATM transactions to avoid and combat identity theft and black money dealings.
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Online Payments
Consumers are now moving towards the electronic payment method due to replacing businesses’traditional platforms to electronic websites. This change in the business world has made the payment methods effortless, consisting of high risk rates. Taking into account the threat rate, the fintech industry incorporated biometric facial checks that validated the entity’s identity to ensure that the individual behind the screen was the authentic person conducting the transaction. Another important aspect of face ID checks in electronic payment is that it evaluate the real data of the client by just using their face.
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Digital Trading
Face verification also works in the digital trading system. In digital trading, the business requires investments and transactions from the consumers’ side, which requires the authenticity of the entity involved in the funding. The digital trading methods can easily process millions of transactions effortlessly with the face ID check within minutes. It ensures the security of transactions and the credibility of the business handling digital trade.
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Credit Scoring
Biometric facial recognition plays a vital role in credit scoring. It includes the analysis of entities’ credit files. The face verification works by identifying the authenticity of the consumer’s profile and the history of transactions. It also includes the amounts the consumers owe, and new credits and debits carried out from the account. However, the ID verification tracks the imposters and fraudulent transactions along with keeping track of account takeovers.
Concluding Statement
Facial recognition services are effectively assisting both industries in a way that has helped them achieve higher customer satisfaction and conversion rates. All these advanced methods of verification make the onboarding experience seamless and helping organizations improve security levels. The multifactor workflow and face detection approach does not rely on any additional physical hardware codes. With the automated system, organizations can be sure that the entity carrying out the transaction or accessing the account details is legitimate. The facial recognition solution has replaced the simple bank payment method with a simple pay-by-face approach.