TMCnet Feature
November 23, 2022

Fraud Detection and Prevention models



Abuse, fraud, extortion – sometimes a moment of inattention is enough to become a victim of cybercriminals. Many companies and institutions are exposed to huge financial losses every day, as well as the leakage of confidential data that may threaten their security, and their customers. How to predict this type of behavior and get help in their rapid detection?



EFFECTIVE FRAUD DETECTION MODEL

One of the foundations of any good fraud prevention strategy is the use of data analytics (Fraud Analytics). By analyzing data from the past using analytical methods, we can distinguish features that are highly likely to contribute to fraud. On their basis, protective measures and procedures can be developed.

The main advantage of using analytics compared to analyzing single incidents is that any observations obtained during the analytical process can be used to scour the system and discover potentially harmful cases that may have been initially overlooked. Fraud Analytics is an effective tool that helps eliminate people and networks that are a source of fraud and increase the number of transactions with reliable customers.

DATA ANALYTICS IN THE CONTEXT OF FRAUD PREVENTION

Fraud Analytics is nothing more than fraud analysis, which combines technology and analytical techniques with human interaction. The process of fraud analysis consists in collecting and storing relevant data and their exploration in search of patterns, discrepancies and anomalies. The results are then translated into insights that can allow the company to manage potential threats before they occur, as well as to develop a proactive environment for fraud detection and bribery.

FUTURE CHALLENGES IN THE AREA OF FRAUD DETECTION

While new technologies continue to evolve and bring many opportunities to users, at the same time they are a place for the development of new forms of fraud. The number, variety and severity of cybersecurity threats is increasing on daily basis. Therefore, the security teams need to adapt and continuously improve to protect themselves from the constantly evolving security threats and to preserve the integrity of the database.

One of the types of fraud that has recently appeared in cyberspace is "ice phishing". This new type of cybercrime concerns cryptocurrencies. Microsoft (News - Alert) has issued a warning to users about a possible variant of a phishing attack, which is aimed in particular at Blockchain and Web3.

Web3 is a decentralized web environment in which Blockchain technology plays a key role. What does that mean? Blockchain is a decentralized database, the main task of which is to store cryptocurrency transactions.

Microsoft security analysts have discovered that the culprits are using a malicious smart contract that, signed by unconscious users, redirects tokens from portfolios that are not centralized to an address controlled by the attacker instead of their own. Due to the lack of transparency of the trading interface in Web3, detecting or tracking the movement of tokens is difficult.

DEVELOPMENT OF DATA ANALYTICS IN FRAUD DETECTION

The market for fraud detection and prevention is still developing dynamically. BlueWeave Consulting, in one of its studies, estimated the size of the global market for fraud detection and prevention at USD 28.36 billion in 2021. In the forecast period between 2022 and 2028, BlueWeave predicts that the global market for fraud detection and prevention will grow at a CAGR of 22%, reaching USD 110.17 billion by 2028.

Despite technological advances that make payments and access to data more accessible and easier, there are still growing concerns about digital fraud and, as a result, the need to implement solutions to detect fraud. These forecasts therefore show that there is a high demand for fraud detection and prevention software and services, which will certainly contribute to the dynamic development of this area in the future.



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