I Need To Know How To Bypass Ebay , Amazon , Walmart Fraud Detection Successfully ? .. What's The Best Methods I Found Some Methods And Some Carders Said "Use This Method Ans Some Carders Said Don't Do This Method" ... What Is The Best Method .. I Think This Will Helpful For Newbies
How To Bypass Ebay, Amazon, Walmart Fraud Detection?
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Fraud Detection and Fighting Methods FRAUD
Imagine: you see a lot of interesting offers on the Internet and are trying to urgently take advantage of this by paying for the purchase with a card, but suddenly you find that your card was blocked by the bank without warning.
Or you suddenly receive an SMS about the deletion of a large amount: oh horror! the card is being used by unknown villains who stole your data ...
I will explain to you how banks and businesses use fraud detection systems (anti-fraud) and protect our money (sometimes from ourselves).
Content
1 What is fraud?
1.1 Overview of weak links in the online purchase chain
1.2 Who is affected by this type of fraud?
2 Antifraud
2.1 How antifraud works
2.2 Stop Lists
2.3 Risk assessment
2.4 How the system recognizes suspicious transactions
2.5 System solution
2.6 How the system authenticates a user
2.7 Work of fraud analyst
2.8 An example of the anti-fraud system
2.9 Such systems consist of the following functional parts:
2.10 Viewing a separate case (group of events)
What is fraud?
Fraud in a general sense is fraud, actions with the aim of taking possession of someone else's property (goods or money) through deception.
This concept includes actions from taking a loan on fake documents to abusing the conditions for returning goods in a store.
In fact, fraud can be called actions that pose a financial risk to an individual or organization, and at the same time do not include open robbery using aggressive methods.
According to statistics, most cases of fraud are caused by card fraud.
An overview of the weak links in the online shopping chain
To understand the features of the anti-fraud system, first, we will schematically consider the chain of events that make up any purchase on the Internet.
Each arrow represents an interaction that requires data transfer. If a fraudster becomes the first link in the chain, then all of the following links will suffer in one way or another:
For a shopper, an online purchase appears to be the only real-time billing transaction, but downstream billing occurs within days. If the fraud is not detected immediately, the investigation will be difficult.
Who suffers from this type of scam?
No matter how we sympathize with the citizens whose data was stolen, it is always worth considering the difficulties encountered by other participants in the transaction. If the store, bank or payment system did not have time to respond, you, as the injured party, can ask the bank to return the debited amount without your knowledge. Usually the bank tries to meet you halfway and initiate a so-called chargeback.
But a store that has authorized payment using stolen data will be forced to return the purchase price from its own pocket.
If, among all transactions of the store, it turns out that 1% or more of the total amount is fraudulent, international payment systems may impose a fine on the acquiring bank and store. This damages the portfolio and reputation of the seller and the bank, impairing the possibility of their future cooperation with other organizations.
To eliminate these complications, a bank, payment system or online store uses fraud protection systems.
Antifraud
In the modern sense, antifraud is an analytical system and a set of measures used to assess financial transactions (including online) in terms of the likelihood of fraud.
Fraud protection systems try to detect fraudulent activity based on the characteristics of the transaction and the customer.
By detecting unusual behavior and applying built-in filters, the anti-fraud solution assesses the risk of a transaction and applies special measures to prohibit or allow its execution, or recommendations for further processing of the event by bank employees (fraud analysts).
There are many similar solutions on the market with their own architecture and functionality, but the principles of their work are similar.
How antifraud works
When shopping in an online store, add items to your cart, place an order and go to the checkout page. The minimum details you must also provide are card number, holder name and CVC code.
However, there is much more data actually transferred: it is information about the runtime environment (browser, operating system and device), IP address, cookies, including the http session ID, etc.
When making a purchase, the user performs an action in a browser or mobile application, the transaction is sent (without specifying details) to the internal server of the bank, and then to the internal information systems of the bank for settlements.
General principles of the anti-fraud system on the bank's side.
The bank's internal server transmits information about the transaction to the anti-fraud system and waits for permission to “make” the payment and record it in automated banking systems.
An anti-fraud system (and sometimes a fraud analyst) analyzes the information to decide if the transaction is legal.
The fraud protection system processes incoming events (payments), assesses your risk, starts other services if necessary (for example, additional client authentication) and sends the solution back.
As a result, the user's payment is confirmed or rejected.
What happens inside the anti-fraud system.
Stop Lists
These are "hard" filters: if the characteristics of the transaction contain information relevant to the stop list, all subsequent checks are canceled and the transaction is rejected. Usually the card number, IP address, point of sale and country are checked.
The anti-fraud system will check if the card number is on the list of numbers used by criminals or leaked to the black market when a business is flagged as suspicious.
Large online stores often do not accept cards issued in certain countries in Asia, Latin America and Africa, as international statistics indicate a large number of fraudulent transactions with bank cards from these regions.
Risk assessment
If a transaction is not immediately blocked based on stop lists, the anti-fraud system applies a number of rules to assess the degree of risk.
Firstly, information about the transaction is supplemented with information about the client, his card, payment history, "pulled" from various banking systems and other sources (for example, the user's movement speed can be estimated from the geolocation data from your mobile device).
The transaction receives a specific score, ranging from “safe” (green) to “requiring additional verification” (yellow) or “very suspicious” (red).
How the system recognizes suspicious transactions
The anti-fraud system rules set restrictions (limits) on transactions based on factors such as:
Fraud protection systems store and process large amounts of data using sophisticated mathematical methods and can reveal connections that are not obvious even to an attentive employee, and unusual new patterns that have not yet been described by existing scenarios in the system.
However, there are examples of situations that the anti-fraud system is likely to assess as carrying a high risk.
Typical suspicious online purchases include:
System solution
Provisional scores indicating the degree of risk of a transaction (score) determine whether it will be deemed harmless and approved, requiring additional confirmation of the customer's identity (authentication) and / or verification by an analyst, or immediately classified as fraudulent and rejected.
How the system authenticates a user
If the anti-fraud system has assigned a risk level to a transaction that requires additional authentication, after entering the card details, you can receive an email requesting a purchase confirmation, an SMS with a code word, a push notification in the mobile application. ...
In addition, the bank may block a small amount on your card and then ask you to enter the exact amount to ensure that the card really belongs to you. For large transaction amounts, a bank employee may call you to confirm the payment.
After successful authentication, the fraud protection system gives a green light: the transaction can be completed successfully.
Fraud analyst work
In manual operation, a fraud analyst considers an event (an “incident”) to classify it as “definitely fraudulent” or “definitely legal”. The final status of a transaction's legitimacy may not depend on the decision of an individual employee, but on the cumulative assessment of several analysts working independently of each other.
An example of the anti-fraud system
Let's move from bank customers to anti-fraud analysts for a few minutes and go through the stage of transaction analysis using the example of one of the most famous anti-fraud systems SAS AML (SAS AntiMoney Laundering - the name speaks for itself).
Such systems consist of the following functional parts:
1. Data storage
Without going into technical details, we note that the fraud protection system has information about customers and their transactions, technical information about the data structure, customizable rules and stop lists, as well as a history of all alerts about suspicious transactions committed by the system and the history of all decisions taken by the employees of the Bank's Anti-Fraud Department based on these reports.
2. Notifications and scripts
This part of the system, like the data storage, is hidden from the eyes of an ordinary user, but it is arranged in a rather interesting way.
A scenario is understood as a certain typical situation to which the system must react in a certain way.
In addition to the library of typical scripts already available in the system, bank employees can create their own.
The system allows you to react to events and transactions based on various rules:[/I]
3. Investigation
Transactions marked as suspicious by the system are not always automatically blocked.
There is another level of control - manual investigation carried out by bank employees.
Typically, events that are automatically flagged as suspicious are sent by the system to specific employees or groups for review (for example, a bank may have a special department responsible for monitoring transactions of international legal entities).
Upon closer inspection, employees see a screen like this.
Viewing information about an individual bank client: at the top - notifications about individual transactions, at the bottom - information about all transactions.
By clicking on a separate notification, the fraud analyst will see information about a specific fraud case.
Viewing a separate case (group of events)
The screen contains a textual description of the situation (a number of criminals seen in the sale of illegal drugs had accounts in the same bank), information about the category of the scenario (cash transactions), etc.
If the notification was unsuccessful, the employee can mark the trigger as false, which will be recorded by the system logic.
In the future, this saved information will be used to refine the rules for activating scripts.
The system reconstructs the logic of activating scripts, filters and rules, memorizing information about false notifications and decisions made by bank employees.
Most likely, the general monitoring of events is performed by some kind of “duty” analyst, whose duties include assigning difficult cases to colleagues who specialize in a particular type of operation.
Therefore, the next stage of the investigation will be the selection of the employee who will be charged in the cases presented on the screen.
In the list at the bottom right - the names of employee users to whom you can assign this case for consideration.
When routing an incident, many departments and employees can be involved - for example, some cases can be sent to the technical service. If the technical failure is not confirmed, then it is then sent to the security service.
4. Built-in analytics
This is the “brain” and “soul” of the fraud protection system, hidden from the average user, but very important to work.
Big data engines can detect fraud patterns that are not covered by any fixed scenario that exists today. Fraud protection systems use not only numerical methods, but also natural language analysis.
Data visualization solutions help you visualize the big picture.
SAS Anti-Money Laundering. The graph clearly shows the volume of transactions and the relationship between different customers.
Well, the decision on how to interpret this beautiful picture is still mostly left to the bank.
5. System administration
This is the most annoying part and includes support, maintenance and additional configuration of the fraud protection system.
For example, the bank split routing scheme can be configured in the following window:
Example of Configuring Notification Routing Scheme for Investigation.
So, now you have a general idea of how anti-fraud systems work using the example of the SAS AML solution.
To protect yourself from fraudsters and keep your card details safe:
Imagine: you see a lot of interesting offers on the Internet and are trying to urgently take advantage of this by paying for the purchase with a card, but suddenly you find that your card was blocked by the bank without warning.
Or you suddenly receive an SMS about the deletion of a large amount: oh horror! the card is being used by unknown villains who stole your data ...
I will explain to you how banks and businesses use fraud detection systems (anti-fraud) and protect our money (sometimes from ourselves).
Content
1 What is fraud?
1.1 Overview of weak links in the online purchase chain
1.2 Who is affected by this type of fraud?
2 Antifraud
2.1 How antifraud works
2.2 Stop Lists
2.3 Risk assessment
2.4 How the system recognizes suspicious transactions
2.5 System solution
2.6 How the system authenticates a user
2.7 Work of fraud analyst
2.8 An example of the anti-fraud system
2.9 Such systems consist of the following functional parts:
2.10 Viewing a separate case (group of events)
What is fraud?
Fraud in a general sense is fraud, actions with the aim of taking possession of someone else's property (goods or money) through deception.
This concept includes actions from taking a loan on fake documents to abusing the conditions for returning goods in a store.
In fact, fraud can be called actions that pose a financial risk to an individual or organization, and at the same time do not include open robbery using aggressive methods.
According to statistics, most cases of fraud are caused by card fraud.
An overview of the weak links in the online shopping chain
To understand the features of the anti-fraud system, first, we will schematically consider the chain of events that make up any purchase on the Internet.
Each arrow represents an interaction that requires data transfer. If a fraudster becomes the first link in the chain, then all of the following links will suffer in one way or another:
- The buyer in this scheme is the real owner of the card or a fraudster who has become the owner of his data.
- Merchant (TP, in terms of electronic payments: merchant) - for example, an online store.
- Electronic payment system - a service that accepts payment via the Internet
- Acquiring bank - a bank that provides card payment processing services to a store
- Payment system (for example, Visa, Master Card, MIR) - responsible for settlements between banks
- Issuing bank - the bank that issued the card with which the buyer is trying to pay for the goods.
For a shopper, an online purchase appears to be the only real-time billing transaction, but downstream billing occurs within days. If the fraud is not detected immediately, the investigation will be difficult.
Who suffers from this type of scam?
No matter how we sympathize with the citizens whose data was stolen, it is always worth considering the difficulties encountered by other participants in the transaction. If the store, bank or payment system did not have time to respond, you, as the injured party, can ask the bank to return the debited amount without your knowledge. Usually the bank tries to meet you halfway and initiate a so-called chargeback.
But a store that has authorized payment using stolen data will be forced to return the purchase price from its own pocket.
If, among all transactions of the store, it turns out that 1% or more of the total amount is fraudulent, international payment systems may impose a fine on the acquiring bank and store. This damages the portfolio and reputation of the seller and the bank, impairing the possibility of their future cooperation with other organizations.
To eliminate these complications, a bank, payment system or online store uses fraud protection systems.
Antifraud
In the modern sense, antifraud is an analytical system and a set of measures used to assess financial transactions (including online) in terms of the likelihood of fraud.
Fraud protection systems try to detect fraudulent activity based on the characteristics of the transaction and the customer.
By detecting unusual behavior and applying built-in filters, the anti-fraud solution assesses the risk of a transaction and applies special measures to prohibit or allow its execution, or recommendations for further processing of the event by bank employees (fraud analysts).
There are many similar solutions on the market with their own architecture and functionality, but the principles of their work are similar.
How antifraud works
When shopping in an online store, add items to your cart, place an order and go to the checkout page. The minimum details you must also provide are card number, holder name and CVC code.
However, there is much more data actually transferred: it is information about the runtime environment (browser, operating system and device), IP address, cookies, including the http session ID, etc.
When making a purchase, the user performs an action in a browser or mobile application, the transaction is sent (without specifying details) to the internal server of the bank, and then to the internal information systems of the bank for settlements.
General principles of the anti-fraud system on the bank's side.
The bank's internal server transmits information about the transaction to the anti-fraud system and waits for permission to “make” the payment and record it in automated banking systems.
An anti-fraud system (and sometimes a fraud analyst) analyzes the information to decide if the transaction is legal.
The fraud protection system processes incoming events (payments), assesses your risk, starts other services if necessary (for example, additional client authentication) and sends the solution back.
As a result, the user's payment is confirmed or rejected.
What happens inside the anti-fraud system.
Stop Lists
These are "hard" filters: if the characteristics of the transaction contain information relevant to the stop list, all subsequent checks are canceled and the transaction is rejected. Usually the card number, IP address, point of sale and country are checked.
The anti-fraud system will check if the card number is on the list of numbers used by criminals or leaked to the black market when a business is flagged as suspicious.
Large online stores often do not accept cards issued in certain countries in Asia, Latin America and Africa, as international statistics indicate a large number of fraudulent transactions with bank cards from these regions.
Risk assessment
If a transaction is not immediately blocked based on stop lists, the anti-fraud system applies a number of rules to assess the degree of risk.
Firstly, information about the transaction is supplemented with information about the client, his card, payment history, "pulled" from various banking systems and other sources (for example, the user's movement speed can be estimated from the geolocation data from your mobile device).
The transaction receives a specific score, ranging from “safe” (green) to “requiring additional verification” (yellow) or “very suspicious” (red).
How the system recognizes suspicious transactions
The anti-fraud system rules set restrictions (limits) on transactions based on factors such as:
- The number of purchases by one client or one card for a certain period of time
- The amount of one purchase by card (or by one customer) for a period of time
- The number of cards used by one client for a certain period of time
- The number of users making purchases with the same card
- The history of the transactions of the given customer of the store / cardholder (especially - purchases and withdrawals)
- The profile of the average shopper of a store where an online purchase is made
Fraud protection systems store and process large amounts of data using sophisticated mathematical methods and can reveal connections that are not obvious even to an attentive employee, and unusual new patterns that have not yet been described by existing scenarios in the system.
However, there are examples of situations that the anti-fraud system is likely to assess as carrying a high risk.
Typical suspicious online purchases include:
- Payment by one card from different devices with different IP addresses
- Payment from the same device and IP address using different cards
- Repeated unsuccessful attempts to confirm a transaction
- Using the same card to pay for orders from different accounts in the same online store
- Differences in the name of the account of the online store buyer and the cardholder with which the order was paid
- Different countries of the buyer, store and card issuing bank
System solution
Provisional scores indicating the degree of risk of a transaction (score) determine whether it will be deemed harmless and approved, requiring additional confirmation of the customer's identity (authentication) and / or verification by an analyst, or immediately classified as fraudulent and rejected.
How the system authenticates a user
If the anti-fraud system has assigned a risk level to a transaction that requires additional authentication, after entering the card details, you can receive an email requesting a purchase confirmation, an SMS with a code word, a push notification in the mobile application. ...
In addition, the bank may block a small amount on your card and then ask you to enter the exact amount to ensure that the card really belongs to you. For large transaction amounts, a bank employee may call you to confirm the payment.
After successful authentication, the fraud protection system gives a green light: the transaction can be completed successfully.
Fraud analyst work
In manual operation, a fraud analyst considers an event (an “incident”) to classify it as “definitely fraudulent” or “definitely legal”. The final status of a transaction's legitimacy may not depend on the decision of an individual employee, but on the cumulative assessment of several analysts working independently of each other.
An example of the anti-fraud system
Let's move from bank customers to anti-fraud analysts for a few minutes and go through the stage of transaction analysis using the example of one of the most famous anti-fraud systems SAS AML (SAS AntiMoney Laundering - the name speaks for itself).
Such systems consist of the following functional parts:
- Data storage
- Triggers and alerts ("alerts")
- Investigation
- Built-in analytics
- Anti-fraud system administration
1. Data storage
Without going into technical details, we note that the fraud protection system has information about customers and their transactions, technical information about the data structure, customizable rules and stop lists, as well as a history of all alerts about suspicious transactions committed by the system and the history of all decisions taken by the employees of the Bank's Anti-Fraud Department based on these reports.
2. Notifications and scripts
This part of the system, like the data storage, is hidden from the eyes of an ordinary user, but it is arranged in a rather interesting way.
A scenario is understood as a certain typical situation to which the system must react in a certain way.
In addition to the library of typical scripts already available in the system, bank employees can create their own.
The system allows you to react to events and transactions based on various rules:[/I]
- Individual events (for example, a one-time change of the address of the bank client's location),
- A historical chain of events (for example, a series of purchases made at a short time interval in different locations),
- Behavioral scenarios (that is, a combination of various customer actions over a certain period of time - for example, changing the mobile number linked to the card, followed by the withdrawal of a large amount of cash from an ATM).
3. Investigation
Transactions marked as suspicious by the system are not always automatically blocked.
There is another level of control - manual investigation carried out by bank employees.
Typically, events that are automatically flagged as suspicious are sent by the system to specific employees or groups for review (for example, a bank may have a special department responsible for monitoring transactions of international legal entities).
Upon closer inspection, employees see a screen like this.
Viewing information about an individual bank client: at the top - notifications about individual transactions, at the bottom - information about all transactions.
By clicking on a separate notification, the fraud analyst will see information about a specific fraud case.
Viewing a separate case (group of events)
The screen contains a textual description of the situation (a number of criminals seen in the sale of illegal drugs had accounts in the same bank), information about the category of the scenario (cash transactions), etc.
If the notification was unsuccessful, the employee can mark the trigger as false, which will be recorded by the system logic.
In the future, this saved information will be used to refine the rules for activating scripts.
The system reconstructs the logic of activating scripts, filters and rules, memorizing information about false notifications and decisions made by bank employees.
Most likely, the general monitoring of events is performed by some kind of “duty” analyst, whose duties include assigning difficult cases to colleagues who specialize in a particular type of operation.
Therefore, the next stage of the investigation will be the selection of the employee who will be charged in the cases presented on the screen.
In the list at the bottom right - the names of employee users to whom you can assign this case for consideration.
When routing an incident, many departments and employees can be involved - for example, some cases can be sent to the technical service. If the technical failure is not confirmed, then it is then sent to the security service.
4. Built-in analytics
This is the “brain” and “soul” of the fraud protection system, hidden from the average user, but very important to work.
Big data engines can detect fraud patterns that are not covered by any fixed scenario that exists today. Fraud protection systems use not only numerical methods, but also natural language analysis.
Data visualization solutions help you visualize the big picture.
SAS Anti-Money Laundering. The graph clearly shows the volume of transactions and the relationship between different customers.
Well, the decision on how to interpret this beautiful picture is still mostly left to the bank.
5. System administration
This is the most annoying part and includes support, maintenance and additional configuration of the fraud protection system.
For example, the bank split routing scheme can be configured in the following window:
Example of Configuring Notification Routing Scheme for Investigation.
So, now you have a general idea of how anti-fraud systems work using the example of the SAS AML solution.
To protect yourself from fraudsters and keep your card details safe:
- Avoid using ATMs in suspicious locations (try to use ATMs located in bank buildings).
- Do not hand the card into the hands of trade employees and waiters.
- Be careful when using public WIFI networks (do not use the Internet bank and do not make online purchases using the free Internet in cafes, subways, on city streets).
- Do not provide the full details of your card if you make a purchase or sale from a private person on the Internet.
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