Fraud Detection

What is fraud detection?

Fraud detection applies to banking and finance, insurance, medicine, government agencies and law enforcement, to name a few. Advanced data mining tools are used to analyze millions of transactions to identify patterns associated with fraudulent behavior. Today, fraud detection analytics solutions are tightly integrated into business systems and can not only detect fraud, but also prevent it in real time. These solutions include some of the latest technologies, such as big data, advanced analytics and artificial intelligence (AI).

What are the business benefits of fraud detection?

With AI-based fraud detection solutions, organizations can detect and stop ongoing fraud, whether it's a payment, an insurance claim, or a doctor's visit. The ability to detect real fraud in real time reduces both the loss and cost of manual intervention.

Fraud detection protects customer and business information, assets, accounts, and transactions through real-time, near real-time, or batch analysis of user activity and other targeted entities (such as kiosks). It uses server-side background processes that learn the access patterns and behavior of users and other defined objects, and typically compare this information to the expected profile. Fraud detection does not hinder the user if his actions do not arouse suspicion.

Literal Meanings of Fraud Detection

Fraud:

Meanings of Fraud:

1. The of theft or the unauthorized acquisition of money by fraudulent means.

2. Any form of deception carried out to obtain an unfair, undeserved and/or advantage.

3. Adopting a false identity for such a deceptive purpose.

4. A person who performs such a trick.

Detection:

Meanings of Detection:

1. The act of feeling or feeling something, discovering something that was hidden or veiled.

2. Detection of a component, signal, agent, etc. usually with a specific device or method.