Use-cases Of Artificial Intelligence In The Digital World

How Artificial Intelligence pave the way of Digital Security for Businesses

by Tanveer Ahmad — 5 years ago in Artificial Intelligence 4 min. read
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The world is getting digitized at a lightning speed. The advent of digitization has set the stage for a variety of businesses by providing them new growth opportunities. The consumers can avail online services in a frictionless manner whether it is digital banking, gaming or e-shopping.

Technological advancements in the form of Artificial Intelligence (AI), Machine Learning (ML), and Big Data have contributed a lot in revamping the business operations in the digital environment. Whether it is to compete with the demands of consumers or provide seamless digital services, technology is playing a vital role. 

In this article, exceptional reformations through Artificial Intelligence technology are discussed that have remodeled the traditional organizational operations by making them robust, reliable, automated and secure.

The following are some major use-cases of Artificial Intelligence in the digital world

Detection of Malevolent Activities

AI models are trained and used for the detection of malicious patterns and activities in the system. The fraudulent entities are a potential threat to the digital environment.

To get unauthorized access, they perform malicious activities such as phishing attacks, illegal transactions above the specified threshold, financial crimes such as money laundering and terrorist financing, silent data breaches and many more. Traditional and conventional malware detection methods are unable to fight against innovative fraudulent tricks.

Artificial Intelligence addresses the malware detection issues through its strong underlying algorithms and techniques. Neural networks employing AI technology are trained against huge data that include all the possible incidents taking into consideration the loopholes that can be exploited by the attackers.

The model is trained and tested in real scenarios to detect the malware executables injected into the systems.

A branch of AI, pattern recognition detects suspicious patterns and malware behavior by backtracking the activity path. In this way, any fraudulent attempt is caught by AI models instantly to protect the system from a big loss.

Digital Biometric Authentication

An increasing number of cyberattacks having multiple facets such as credit card fraud in e-commerce, unauthorized transactions in digital banking, account takeover frauds, phishing attacks, and identity theft.

All these cyberattacks are a result of uncontrolled access that cannot be handled by traditional authentication methods present currently in the online platforms. PIN sand passwords authentication is thing of the past. To deal with innovative fraudulent activities, innovative solutions are required.

Detection of Malevolent Activities 

Biometric logins and authentication systems, for example, facial recognition can help the security of platforms by allowing only registered users to avail services, not fake identities. 

AI-powered facial recognition systems perform identity verification online by matching the facial biometrics of an individual against the ones stored in the database at the time of account registration.



The large and well-reputed companies have been the victims of cyberattacks that compromised personal customer information databases which included name, email addresses, financial information, contact details, and passwords. Security breaches cost the businesses, as well as customers whose data, is been compromised. 

AI-based identity authentication solutions have the potential of verifying each individual based on facial biometric which is, on one hand, a robust and on the other hand, a secure authentication method.

Facial recognition technology employs AI algorithms if 3D perception and liveness detection that deters the risk of spoofing attacks. The techniques ensure the physical presence of customers at the time of identity verification and make sure that it is not the fraudulent attempt of users.

AI-based facial recognition technology is capable of detecting the printed images, photoshopped or tampered face image, masks, and similar facial spoofing elements. 
Also read: Best CRM software for 2021

Behavioral Analytics 

AI algorithms with a blend of ML techniques have the ability for behavioral analytics in the system. The behavioral analysis of regular online customers is done to identify customer behaviors.

Here big data comes in. Big data technology has the ability to provide useful insights about consumer behaviors by training the collected data from user activities in the ML models that learn and predict what could be the next big trend. The e-commerce market employs the method more to increase productivity and revenue.

The data from online customer activities, behavior and demands are identified and trained to the ML models, they learn and predict the trend which will be penetrated in the digital world. Moreover, the data collected is analyzed to make a strong business strategy that can ultimately contribute to increased revenue. 

Organizations all over the world and online businesses are paying close attention to their network security. It is a regulatory requirement as well to protect the information of customers.

For instance, the General Data Protection Regulation (GDPR) declares it mandatory for online heiresses to take special care of their customers’ online data. Any discrepancy in the form of data breaches can lead to severe regulatory penalties and monetary loss for the business.

Under such strict regulations, AI is need of an hour. It has introduced revolutionized solutions for businesses to ensure security over their platforms. 

Firewall installations for cybersecurity are employing AI algorithms that can detect the suspicious IP addresses, their source, and destination and in real-time accept or reject the connection required.

In this way, the chances of system hacking get lower. Other than this, malicious executables and scripts injections into the user programs can also be detected through advanced AI technology. After identifying the scope of technology, businesses are shifting regular practices by harnessing technology to the full, ensure security as well as customer experience concurrently.

Tanveer Ahmad

I've been a writer for almost ten years, have experience in (concerning topics). Writing and blogging is my passion. I worked in a bank for 4 years and one day when I was drafting an email to a client I realized that I'm not fit here and creativity runs in my blood. So I left the 9 to 5 job and now I'm an all-time writer. My book is also in the pipeline so my hands are full, which never lets me look back or resent my decision as it changed my life for good.

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