How can Artificial Intelligence help in Identifying Identity Theft
The threat of identity theft is increasing as we see innovative advancements in technology. In most cases, it is done to commit financial fraud such as making transactions or scamming people in the name of someone else. It has been going on for some time now and there has been a sharp rise in identity theft cases.
In 2022, businesses across the country lost $20 billion to it. But thanks to artificial intelligence, one can avoid becoming a victim of such frauds and thefts. If you’re running a business or carrying out financial transactions frequently, it should be of paramount importance to place security measures.
However, you can use a number of apps and software you can use to ensure safety, but the one thing that will keep it running is an internet connection because AI works in real-time. So be sure to have a reliable internet connection like Mediacom. Call the Mediacom phone number now to find out about its fast speed and pocket-friendly plans.
Furthermore, here are all the ways AI has been helping in dealing with the malice of identity theft.
1. AI Securing Businesses
As threats are increasing, businesses are forcing the companies that create protective AI to increase safety levels. Almost all businesses are moving towards higher-risk online transactions, making them more vulnerable. Even the customer risk is increasing as they prefer online transactions over in-person transactions due to convenience. Almost all businesses gather user data before carrying out transactions. This is where AI can be implemented to ensure data safety.
This also creates a balance between user trust and user experience. But even fraud prevention technologies have proved to be insufficient as synthetic fraud has become quite successful. The best way to prevent this is to make sure that trust points are awarded to the vendor only after a significant time of transactions has passed.
2. Use of Synthesized Data
The effectiveness of protection of the collected user information largely depends on the quality of data the organization has. Statistics show that data scientists in companies still spend most of their time collecting and preparing data rather than processing it. This happens when faulty data strategies are being used.
Using the technique of employing synthesized data not only makes internal processing easier but also keeps the data safe as well.
All identifiable information is removed from the data when AI makes randomized changes. By doing so, the organization reduces the risk of identity theft and ensures compliance with data protection regulations. Additionally, this reduces the time it takes for transactions and theft identification on the part of the organization.
3. Scaling ID Authentication
These days, identity documents are being scanned to check the various elements of identity. These documents include the likes of driving license and passport. This scanning may happen on the spot or remotely through mobile phone apps. Bringing AI into this process makes it easier, more efficient, mistake-free, and safe from data theft. The information on these documents is sensitive and can be used against a person like knowing their location through travel details.
It becomes even easier when an untrained individual is involved in the process. In order to collect anonymous internal data, a mechanism should be used that can store and sort the data so that it can be retrieved at any time. It also keeps data safe from any cyber threat as it is stored anonymously.
4. Safety from Unauthorized Access
A major threat to data security is unauthorized access to the systems, which can make them vulnerable to identity theft. This can be avoided if the speed of checking and verifying a person’s identity is faster. AI can provide this facility to organizations with ease.
When the company systems are protected, there is little chance of identity theft. Real-time information about the ID use can be given which makes it easier and quicker for the software to detect any suspicious activity. It also makes it difficult for cybercriminals to carry out their theft as just the credentials are not enough to get access.
5. Predictive Analytics
In order to detect anomalies in the identity, the predictive analytics of AI are proving very beneficial. As more data is fed into the machine learning model for training, the more accurate the fraud detection scores become. This also provides real-time information about each transaction, making it more secure.
So when you’re choosing a fraud detection platform, make sure that you choose one which can combine insights from unsupervised and supervised machine learning. This is because it creates a more secure environment and their trust score is actually believable. The most advanced mechanisms can learn from the data patterns generated in machine learning algorithms.
Conclusion
Identity theft is a bigger danger than many think it is. It is important that businesses keep their and customers’ identities safe by using AI’s superior services for data safety.
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