Digital fraud means some type of unlawful action that is carried out on the Internet. Hackers use different techniques and tools to gain remote access to a computer and the information it contains.
It is an idea as diffuse as it is wrong that cyberattacks and cases of digital fraud only affect large companies. Computer crimes are current events throughout the world and if you have a computer with an Internet connection, you are also exposed to possible digital fraud.
The good news is that there are different measures and technologies that allow you to avoid cases of digital fraud:
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As we have mentioned before, adequate training on the most common types of digital fraud and the basic rules for safe use of the Internet are a key point to prevent unpleasant situations.
Artificial Intelligence (AI) finds numerous applications today, among which a very valid opportunity is shown in the prevention of internet fraud.
Artificial Intelligence allows to identify recurrent patterns between data , through the combination of supervised and unsupervised machine learning .
Unsupervised learning allows finding abnormalities and correlations between factors and emerging variables.
By combining AI based on supervised machine learning , which uses historical data , with unsupervised machine learning, companies get a clearer view of the risks of customer behaviors (predictive analytics).
The statistical data obtained is used to create software that generates ideal behavior patterns and detects those that do not respect that model.
However, AI is not only used to detect patterns in data (data analytics), but also plays an important role in data security .
Among the most applied strategies to guarantee data security is the activation of notifications to users when something strange is noticed. An example of a strategy of this type already applied for years is when, when connecting from a different device than usual, Google sends an alert message . Or still, if the system of some banks detects an anomalous behavior, such as an unusual or logical transaction, it notifies the client asking for their permission to carry out the operation (and of course, neither of these two cases are controlled by people).
In summary, artificial intelligence systems based on this model follow precise phases for the detection of possible digital fraud:
It is clear that artificial intelligence and Machine Learning can add a lot of value and improve data security in companies. However, there are opinions that focus more on its disadvantages than its current usefulness.
Among the frequent criticisms, it is worth highlighting the one that compares the power of artificial intelligence with that of human intelligence, associating the second with a subordinate condition to the first. It is worth wondering how these technologies will be developed in the future, but the vision of the human being completely dominated by technology and deprived of his freedom of action, remains a rather apocalyptic and unreal vision.
Another issue concerns the economic development of society . Some economists (and not only them) wonder how to solve the current social trend that sees the need for a smaller human workforce, partly replaced by technological automation. What perhaps these critics do not take into account is that everything evolves and the world of work as well; jobs do not disappear but evolve. Cybersecurity job offers are constantly growing. So training and flexibility will allow you to adapt to job changes.
Also Read: Data Analytics: Trends For 2022
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