Windows 10: how can I call Microsoft Fraud Dept?

Proventure Business Cards · Feb 25, 2025 at 3:07 PM

A message has locked my computer when I use the Brave search engine. It says to call Microsoft at 800-811-2820. Is this a fraud or scam? I cannot access my E-mail using Brave. Please respond to this E-mail: WACChik @ AOL.com.

:)

Brink · Feb 25, 2025 at 3:10 PM

Microsoft AI solution to detect mobile bank fraud in less than 2 secs

The future of mobile banking is clear. People love their mobile devices and banks are making big investments to enhance their apps with digital features and capabilities. As mobile banking grows, so does the one aspect about it that can be wrenching for customers and banks, mobile device fraud.

Problem: To implement near real-time fraud detection

Most mobile fraud occurs through a compromise called a SIM swap attack in which a mobile number is hacked. The phone number is cloned and the criminal receives all the text messages and calls sent to the victim’s mobile device. Then login credentials are obtained through social engineering, phishing, vishing, or an infected downloaded app. With this information, the criminal can impersonate a bank customer, register for mobile access, and immediately start to request fund transfers and withdrawals.

Artificial Intelligence (AI) models have the potential to dramatically improve fraud detection rates and detection times. One approach is described in the Mobile bank fraud solution guide. It’s a behavioral-based AI approach and can be much more responsive to changing fraud patterns than rules-based or other approaches.

The solution: A pipeline that detects fraud in less than two seconds

Latency and response times are critical in a fraud detection solution. The time it takes a bank to react to a fraudulent transaction translates directly to how much financial loss can be prevented. The sooner the detection takes place, the less the financial loss.

To be effective, detection needs to occur in less than two seconds. This means less than two seconds to process an incoming mobile activity, build a behavioral profile, evaluate the transaction for fraud, and determine if an action needs to be taken. The approach described in this solution is based on:

Feature engineering to create customer and account profiles.

Azure Machine Learning to create a fraud classification model.

Azure PaaS services for real-time event processing and end-to-end workflow.

The architecture: Azure Functions, Azure SQL, and Azure Machine Learning

Most steps in the event processing pipeline start with a call to Azure Functions because functions are serverless, easily scaled out, and can be scheduled.

The power of data in this solution comes from mobile messages that are standardized, joined, and aggregated with historical data to create behavior profiles. This is done using the in-memory technologies in Azure SQL.

Training of a fraud classifier is done with Azure Machine Learning Studio (AML Studio) and custom R code to create account level metrics.

Recommended next steps

Read the Mobile bank fraud solution guide to learn details on the architecture of the solution. The guide explains the logic and concepts and gets you to the next stage in implementing a mobile bank fraud detection solution. We hope you find this helpful and we welcome your feedback.
Click to expand...

Source: Two seconds to take a bite out of mobile bank fraud with Artificial Intelligence | Blog | Microsoft Azure

Brink · Feb 25, 2025 at 3:10 PM

Microsoft AI solution to detect mobile bank fraud in less than 2 secs

The future of mobile banking is clear. People love their mobile devices and banks are making big investments to enhance their apps with digital features and capabilities. As mobile banking grows, so does the one aspect about it that can be wrenching for customers and banks, mobile device fraud.

Problem: To implement near real-time fraud detection

Most mobile fraud occurs through a compromise called a SIM swap attack in which a mobile number is hacked. The phone number is cloned and the criminal receives all the text messages and calls sent to the victim’s mobile device. Then login credentials are obtained through social engineering, phishing, vishing, or an infected downloaded app. With this information, the criminal can impersonate a bank customer, register for mobile access, and immediately start to request fund transfers and withdrawals.

Artificial Intelligence (AI) models have the potential to dramatically improve fraud detection rates and detection times. One approach is described in the Mobile bank fraud solution guide. It’s a behavioral-based AI approach and can be much more responsive to changing fraud patterns than rules-based or other approaches.

The solution: A pipeline that detects fraud in less than two seconds

Latency and response times are critical in a fraud detection solution. The time it takes a bank to react to a fraudulent transaction translates directly to how much financial loss can be prevented. The sooner the detection takes place, the less the financial loss.

To be effective, detection needs to occur in less than two seconds. This means less than two seconds to process an incoming mobile activity, build a behavioral profile, evaluate the transaction for fraud, and determine if an action needs to be taken. The approach described in this solution is based on:

Feature engineering to create customer and account profiles.

Azure Machine Learning to create a fraud classification model.

Azure PaaS services for real-time event processing and end-to-end workflow.

The architecture: Azure Functions, Azure SQL, and Azure Machine Learning

Most steps in the event processing pipeline start with a call to Azure Functions because functions are serverless, easily scaled out, and can be scheduled.

The power of data in this solution comes from mobile messages that are standardized, joined, and aggregated with historical data to create behavior profiles. This is done using the in-memory technologies in Azure SQL.

Training of a fraud classifier is done with Azure Machine Learning Studio (AML Studio) and custom R code to create account level metrics.

Recommended next steps

Read the Mobile bank fraud solution guide to learn details on the architecture of the solution. The guide explains the logic and concepts and gets you to the next stage in implementing a mobile bank fraud detection solution. We hope you find this helpful and we welcome your feedback.
Click to expand...

Source: Two seconds to take a bite out of mobile bank fraud with Artificial Intelligence | Blog | Microsoft Azure

Bill Smithers · Feb 25, 2025 at 3:10 PM

Microsoft Refund Dept.

Most of these calls originate from countries that are outside Western Law Enforcement jurisdiction.

And this has been happening for many years to 1,000s of people evey day all around the world.

@@@@@@@@@@@@@@@@@@@@@@@

It is a Scam.

Microsoft will never contact you with cold-calls, popups, etc.

This is the advice given to anyone who has any phone calls, etc. like this about Malware, License Expiry, etc.

And your machine does not send out messages to anyone saying that it has problems or is infected with Malware, etc.

We all have errors and warnings in our event viewer, which is another ploy they use to scare you

These so-called "Microsoft" Tech Companies either want to sell you worthless software, or gain Remote Access to your Computer to try and steal your Banking and Credit Card details and to also carry out an Identity Theft on you.

You are the only one who knows if you have given them Remote Access.

If you have given them Remote Access and if you do Internet Banking, contact your Bank, explain it to them and change Passwords.

If you use your Credit Card online, cancel it and get a new one issued to you.

And the only way that you willl know that you are free of them is to save your Data and do a clean install of your Operating System.

@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@

And Microsoft does not contact you, unless YOU have made prior arrangements with them to do so.

There is a section in the link I am supplying you about this at the end of it

Read this Microsoft Information:

"Avoid tech support phone scams"

Microsoft security help and learning

Do not trust unsolicited calls. Do not provide any personal information.

Here are some of the organizations that cybercriminals claim to be from:

Windows Helpdesk

Windows Service Center

Microsoft Tech Support

Microsoft Support

Windows Technical Department Support Group

Microsoft Research and Development Team (Microsoft R & D Team)

Report phone scams

Help Microsoft stop cybercriminals by reportinginformation about your phone scam.

In the United States, use the
FTC Complaint Assistant form.

In Canada, the Canadian Anti-Fraud Centre (CAFC) can provide support.

In the United Kingdom, you can report
fraud as well as
unsolicited calls.

Cheers.

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FRAUD PHONE CALL!!!!!