Innovative technologies in the present world have transformed business workflow. Using intelligent technological systems makes corporate life easier for experts and helps specialists fight fraud and ensure compliance with KYC & AML regulations. The advanced approach enables corporations to keep up with the latest market trends and boost yearly profit rates. Applying machine learning facial recognition systems offers a smart approach towards fraud prevention and modernizing daily workflow in modern-day industries.
The following article looks closely at the significance of ML-based facial verification systems and how present-day industries can conveniently achieve corporate milestones.
Facial Recognition Services: Gaining Quick Insight
Face authentication is an AI-driven technology that verifies customers’ identity credentials by screening government-issued records such as passports. It ensures a positive user experience and discourages spoof attacks, deep fakes, and replay scams.
According to Mordor Intelligence, the global face verification market size will reach a CAGR of 21.9% for the forecast period (2018 to 2028). During the predicted time, the largest shareholder will be the North American region.
As per Fortune Business Insights, advanced video surveillance systems increase the demand for machine learning facial recognition solutions. This plays a vital role in the progress of the concerned market.
Notable 5 Innovative Applications of Machine Learning Facial Recognition Systems
Big giants such as MasterCard and Facebook utilize predictive analytics with the help of smartphones. Experts have offered selfie payments and tagging features to guarantee a positive customer experience. Geo filters in Snapchat and face recognition effects are efforts in the same direction to enhance customer satisfaction. The following points look closely at intelligent use cases of state-of-the-art technology in modern-day industries.
- Performing Identity Management in Government Agencies
The Australian government has created large databases containing people’s biometric data. Experts collect information through the registration of passports to ensure maritime security. Moreover, in the USA, 117mn adults’ data is in repositories which makes the system one of the biggest storage worldwide.
Government officials can easily use the data for census studies, voter identification, and law & order management. Hence, machine learning facial recognition technology supports effective identity management for experts.
- Executing Emotion & Sentiment Analysis in Retail Industry
For private companies, modern computational approaches such as signal processing and computer vision can have positive results. The latest face identification technology provides accurate facial expression analysis, detection of key emotions in customers, and other user engagement statistics. For example, at retail outlets, video surveillance systems can conveniently extract the image of a blacklisted entity or card counter. The innovative digital solution can cross-match data against information in company repositories to find a match.
The retail sector can also use face recognition technology-based attendance systems to keep track of loyal clients and offer discounts.
- Managing Product Portfolio in Marketing
Modern-day devices can analyze customers’ engagement in public spaces such as shopping malls. This can help experts conduct extensive market research and feasibility studies on user behavioral patterns on web pages, interaction with ads, and much more. Customers can participate from anywhere in the world. Hence, the advanced approach facilitates product portfolio management through high-fidelity data collection.
- Streamlining Healthcare Services in the Medical Sector
Face recognition technology offers a contactless service to users, ensuring convenience for customers. Through genetic screening, patients can easily check into hospitals and clinics. With the innovative digital solution, experts can easily fetch medical records within seconds instead of days or long hours. Doctors and nurses can also use sentiment analysis in professional settings to enhance the emotional well-being of patients. This can also make the telemedicine experience satisfactory for concerned parties. Finally, physiotherapists can improve medical care in sessions by tracking movements of the face, head, and eyes. Consequently, machine learning facial recognition services can further transform the medical sector in the coming five years.
- Modernising Authentication Systems in Financial Institutions
Nowadays, customers want friendly, fast, and reliable services from the financial sector. Clients demand high security and expect banking service providers to ensure transparency of procedures. This is important to boost not only yearly profits but also enhance customer satisfaction.
Deep learning facial recognition technology can streamline the cash withdrawal process from ATMs to ensure faster access. In addition, innovative approaches can facilitate the elderly while receiving pensions and other financial disbursements that demand Proof of Life.
Concluding Thoughts
Companies that do not use the latest machine learning facial recognition services face more fraud cases and lose market credibility. This way, criminals exploit organizations for malicious purposes. Experts in organizations that still use outdated security measures must opt for the latest digital solutions to deter bad actors while saving time & cost for the concerned enterprise.
Cutting-edge technology produces high-quality, reliable, and fast results. Moreover, industries can easily avoid hefty fines and permanent bans by following international regulatory standards. Hence, the transformative power of machine learning facial recognition solutions becomes evident.