The rapid digitization of the world has led to a significant rise in cybercrimes, including hacking, data theft, phishing, and scamming. Financial criminals commit extreme crimes such as money laundering and terrorist financing using digital means. Various software solution-providing companies have developed sufficient technologies to combat these crimes. These SaaS companies provide businesses with adequate tools to counter financial crimes and ensure compliance with anti-money laundering and counter-terrorism financing regulatory benchmarks. Identity verification is an essential strategy for an organization’s KYC procedures, and biometric facial recognition is an ideal ID verification solution.
What is the Facial Recognition Technology?
Facial recognition technology is a machine learning-backed computer technology that detects and recognizes a human face. It is used for the real-time tracking of humans. It uses artificial intelligence that teaches computers to process data like the human brain. It is known as neural network technology. An estimate states that the biometric facial recognition market, which was roughly USD 5 billion in 2021, is projected to reach USD 12.67 billion by 2028. Such astounding figures showcase the value of facial recognition in the present times of digital technologies.
The above-mentioned stats hint at the rapid transitioning of multi-sectoral businesses and financial institutions toward biometric face recognition online technologies. This is because of facial recognition’s vital role in enhancing the security of enterprises, specifically financial organizations like banks. Biometric facial recognition proves to be a potent security solution for fraud deterrence, identity theft, and shielding data from criminals. It ensures a seamless customer onboarding process and aids organizations in swift KYC and AML/CFT compliance.
Facial Recognition System
Biometric facial recognition comprises several functions such as face tracking, face analysis, and facial recognition system.
- Machine learning-backed face tracking detects, identifies, and tracks human faces in videos and images.
- Face analysis in biometric facial recognition processes humans’ facial expressions in detecting parts of a digital image or video to determine age and gender. It also has the capability to detect human emotions.
- Lastly, the facial recognition system detects data to generate a faceprint and compares it with the already-stored image. Faceprint is just like a fingerprint unique to every human being and is used for an individual’s biometric identity verification.
Businesses or financial organizations must switch to biometric facial recognition verification procedures in their KYC mechanism to mitigate fraud, prevent financial crimes, and comply with AML regulations.
Face Match Online
The face match uses artificial intelligence to detect and identify faces from digital images and lists them. It is also a technique of biometric facial recognition and is used to compare human faces with high precision. Face match online is used to verify whether a person is a natural human. If organizations suspect any customer with a criminal record, they can verify the customer’s identity from the online database of images. They can compare their customer’s photographs against millions of faces using facial recognition online methods. There are various online face-match search engines that work by recognizing human faces in pictures and videos, determining if the person’s face appears in two images, and searching for it among numerous different photos. Biometric facial recognition uses high-tech cameras to compare the faces of passersby with pictures of people on a pre-defined list that come from various sources such as social media accounts, criminal databases, etc.
Benefits of the Facial Recognition Technology
Financial organizations, especially financial institutions like banks can reap immense benefits from biometric facial recognition. Firstly, facial recognition technology allows prompt and seamless identification for their customers, specifically remote ones, because it consumes less time and effort. Therefore, it enhances a firm’s credibility and the trust of its customers. Secondly, biometric facial recognition can be integrated into several sectors like aviation, transport, commerce, law enforcement, finance, etc. The most significant advantage of the AI-powered face recognition technology is that it guarantees a swift customer onboarding process and allows you to achieve AML compliance.
Online Face Recognition Technologies in Law Enforcement
Biometric facial recognition has numerous advantages for law enforcement agencies. Police and other security organizations have adopted machine learning-based biometric facial recognition technology into their investigative mechanisms. Online face recognition technologies compare the images and videos of a suspect, coming from different sources, with those in the database of a security agency. It allows the LEAs to identify, detect and trace the offenders in real time. Hence, it significantly enhances the security apparatus of a law enforcement agency.
Online Facial Recognition and Deep Learning
Biometric facial recognition is backed by artificial intelligence and uses neural network technology. It is a type of machine learning that comprises interconnected neurons or nodes in layered structures, just like human brain functions. This phenomenon, known as deep learning, consists of algorithms that identify facial features. It first detects and identifies human eyes, followed by other features such as eyebrows, mouth, etc. This high-tech machine-learning facial recognition is a revolutionary innovation in biometric identity verification technologies that ensures security and prevents multiple crimes.
In a Nutshell
Biometric facial recognition holds immense significance for any business or organization because it enhances the security of your firm’s customer onboarding process. Moreover, it ensures KYC, AML, and CFT compliance and mitigates the possibility of crimes through a standardized customer verification mechanism.