How to use azure sentinel for fraud detection

Introduction

In the current era of digitization, businesses are transacting online and are exposed to numerous fraud risks. Such fraud risks can cause significant financial losses to the company if not detected and prevented in time. Machine learning and AI technologies have brought new and reliable approaches to fraud detection in the industry. In this context, Azure Sentinel is gaining popularity among businesses because of its high-quality features for fraud detection. Businesses can leverage Azure Sentinel for fraud detection to detect and respond to fraudulent activities proactively.

Azure Sentinel is a cloud-native tool that brings together multiple data sources across the company's cloud, on-premise infrastructure, and beyond to deliver optimized security analytics. Utilizing the cloud infrastructure enables Azure Sentinel to handle a massive amount of data, including security logs, network events, and system records, among others. The present article will explain how to leverage the Azure Sentinel platform for fraud detection in your company.

Understanding the Common Types of Fraudulent Activities?

Fraudulent activities are widespread and can be conducted in numerous ways. Businesses must identify the common types of fraudulent activities to prevent and mitigate the risks associated with such activities. Here are some of the prevalent types of fraudulent activities in businesses:

Cyber phishing

This type of activity involves sending fraudulent emails claiming to be legitimate, aiming to extract sensitive information from the recipient.

False invoicing

Involves creating incorrect or fake invoices to receive payments from suppliers or customers.

Payment fraud

Involves unauthorized individuals gaining access to customers' or employees' payment information intending to make fraudulent transactions.

Identity theft

This kind of fraud involves a criminal using an individual's personal information, usually obtanined illegally, to defraud the business or the person whose identity was stolen.

Financial statements

This involves manipulating financial statements in a manner intended to conceal the financial information or fake incomes.

Leveraging Azure Sentinel for Fraud Detection

Azure Sentinel is a cloud-based tool that enables businesses to monitor their cloud and on-premises infrastructure, detect fraudulent activities, and respond proactively to mitigate the risks associated with such activities. Here is a detailed explanation of how businesses can utilize Azure Sentinel for fraud.

Step 1: Azure Sentinel Configuration

The first step is to configure and set up Azure Sentinel in your business environment. A repository to store event data is necessary at this point. Azure Sentinel supports multiple sources of event data, including logs from various security solutions, network events, database logs, and system records, among others.

Once the data sources have been identified and configured, one can leverage Azure Logic Apps, a workflow automation tool that Microsoft Azure provides, to monitor the data sources and configure alerts for suspicious activities. Azure Logic Apps can integrate different applications and services from various providers, thereby enabling automated data flow between the data sources and Azure Sentinel.

Step 2: Creation of Custom Entities for Fraud Indicators

Creating custom entities can help to identify patterns in fraudulent activities. For instance, a business can create custom entities such as suppliers or customers deemed high-risk, thereby identifying unusual activities associated with such partners. The Azure Sentinel platform supports the creation and tracking of custom entities, which can be used to detect suspicious activities and allow the business to take action to prevent fraudulent activities from occurring.

Step 3: Developing Fraud Detection Analytics

Fraud detection analytics is a set of mathematical models that enables the business to detect fraudulent activities in the data collected. Fraud detection analytics uses various algorithms, including machine learning models, to identify patterns of fraudulent activities in the business's data sources. This can be achieved using the Azure Machine Learning Studio, which offers pre-built modules for executing machine learning routines, making it easy to tag fraudulent activities.

One can also use an open-source tool, Spark cognitive training, including within Azure Databricks. This tool enables businesses to develop robust predictive models that can distinguish normal from abnormal patterns of activities. Data scientists can use these tools to build and refine models for monitoring indicators of fraud.

Step 4: Analysis and Reporting

Once the data has been analyzed, the next step is to review the analysis and report on suspicious activities detected. Azure Sentinel provides pre-built reporting templates that can be used to generate reports highlighting the activities identified as fraudulent activities. These reports can be used to provide specific details to law enforcement agencies or used to identify and resolve issues within the business rapidly.?

Step 5: Reducing False Positives

The goal of fraud detection is to maximize the number of fraudulent activities detected while minimizing the occurrence of false positives. A false positive is an event that triggers an alert, but upon review, is shown to be a legitimate activity. Azure Sentinel allows one to minimize false positives by refining the models and analyzing the data sources more deeply, thereby increasing the accuracy of the algorithms used.

Conclusion

Azure sentinel for fraud detection is an ideal platform for businesses to detect and prevent various types of fraudulent activities. Azure Sentinel helps to monitor and analyze data from various sources, develop custom entities, and train predictive models to identify fraudulent activities effectively. Additionally, the platform provides easy-to-use reporting features that generate detailed reports about the identified activities. Despite its functionality, businesses must understand that the tool is not flawless; businesses must persistently monitor and finetune the tool following changing circumstances, and risk scenarios, and adding new data sources to it. By utilizing the Azure Sentinel platform, businesses can identify fraudulent activities accurately and prevent untimely financial losses for the organization.