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Tips What is Anti-Fraud:Tasks and Methods
- Thread starter Serafim
- Start date
ty
To combat fraud and theft of confidential information, banking systems use antifraud. These systems are aimed at detecting and preventing fraudulent attacks, and this is implemented by dozens of different methods.
What is antifraud: tasks and methods
Let's talk about the goals and methods of antifraud that are relevant at the moment.
Let's understand the terminology
Antifraud system is a set of measures that allow you to evaluate banking or Internet transactions for the degree of the likelihood of fraud. To do this, the system tries on certain criteria for each operation - and if it does not correspond to them, then it checks it more thoroughly and signals it.
Built-in filters help to recognize unusual behavior and assess the risks of the operation, and then apply measures to allow or deny it. In disputable situations, the final solution to the issue is passed on to the bank's employees, who are called fraud analysts (fraud is fraud in order to take possession of other people's funds or property by fraud).
Banks and regulators have been actively cooperating with each other in recent years, creating new recommendations for identifying fraudulent schemes. Financial organizations exchange information with each other, and self-learning anti-fraud systems analyze Big Data and learn to make decisions based on this analysis. According to a study by the National Bureau of Credit Histories, already in 2017, shortly after the massive introduction of anti-fraud systems in banks, the number of loans with suspicious signs decreased by 15%. Similar solutions are increasingly being implemented by representatives of small and medium-sized businesses, especially due to the availability of low-cost cloud solutions on the market.
How the anti-fraud process works
Each transaction first goes through the first "line of defense": it is checked for compliance with the established restrictions, such as the limit on the volume of purchases on the card, the maximum one-time purchase amount, the number of users of one card, the number of cards for one client, etc. If all these checks have passed successfully, then the next, more serious ones come into play.
Based on their results, the antifraud assigns one of the conditional "labels" to the operation:
For all checks, the user must be recognized according to one or another algorithm. The standard protection settings are also taken into account - protection from the selection of confidential data and payment information. The map is analyzed by country of issue, geography of use, owner. The history of previous payments is being studied.
- Red. Danger of fraud, cardholder authentication is required. Such a label is automatically assigned to translations with non-standard characteristics - for example, a user from France pays for a purchase in a Russian online store with a card issued in the UK.
- Yellow. For example, if the amount of payment is significantly higher than the average for a particular store. There is a possibility of fraud, additional verification is required.
- Green. Payment is carried out within one country, the payment amount is average. Minimal chance of fraud.
Relationship between antifraud and user authentication * Hidden text: cannot be quoted. *
* Hidden text: cannot be quoted. *
What antifraud tasks does the product solve?
ANTIFRAUD allows you to control internal and external fraudulent schemes and process each loan application within 40 seconds. Main functions:
When a rule is triggered, the entire database is analyzed. Alarms are clearly visualized, the system instantly adapts to changes in conditions. With the help of control of internal and external schemes, the likelihood of obtaining loans for fake details, for invalid documents or for goods for the purpose of cashing is reduced to zero. In addition, applications with photocopies of documents or made in collusion / under pressure are rejected. Confirmed fraud profiles are added to the blacklist, after which the updated data is transmitted to the automated banking system.
- Checking information about the applicant against blacklists.
- Identifying data inconsistencies in loan applications by cross-checking and comparing with other applications.
- Supplementing the client's personal data with information from external sources.
- Fuzzy data comparison algorithms.
Living in the age of information technology, we are constantly faced with fraudulent schemes of one kind or another - as soon as one attacker manages to deceive the system, he spreads a loophole among the rest. Fortunately, modern security services can learn and are becoming more productive every day. We offer to order a presentation and see for yourself how the anti-fraud works effectively.
ty
To combat fraud and theft of confidential information, banking systems use antifraud. These systems are aimed at detecting and preventing fraudulent attacks, and this is implemented by dozens of different methods.
What is antifraud: tasks and methods
Let's talk about the goals and methods of antifraud that are relevant at the moment.
Let's understand the terminology
Antifraud system is a set of measures that allow you to evaluate banking or Internet transactions for the degree of the likelihood of fraud. To do this, the system tries on certain criteria for each operation - and if it does not correspond to them, then it checks it more thoroughly and signals it.
Built-in filters help to recognize unusual behavior and assess the risks of the operation, and then apply measures to allow or deny it. In disputable situations, the final solution to the issue is passed on to the bank's employees, who are called fraud analysts (fraud is fraud in order to take possession of other people's funds or property by fraud).
Banks and regulators have been actively cooperating with each other in recent years, creating new recommendations for identifying fraudulent schemes. Financial organizations exchange information with each other, and self-learning anti-fraud systems analyze Big Data and learn to make decisions based on this analysis. According to a study by the National Bureau of Credit Histories, already in 2017, shortly after the massive introduction of anti-fraud systems in banks, the number of loans with suspicious signs decreased by 15%. Similar solutions are increasingly being implemented by representatives of small and medium-sized businesses, especially due to the availability of low-cost cloud solutions on the market.
How the anti-fraud process works
Each transaction first goes through the first "line of defense": it is checked for compliance with the established restrictions, such as the limit on the volume of purchases on the card, the maximum one-time purchase amount, the number of users of one card, the number of cards for one client, etc. If all these checks have passed successfully, then the next, more serious ones come into play.
Based on their results, the antifraud assigns one of the conditional "labels" to the operation:
For all checks, the user must be recognized according to one or another algorithm. The standard protection settings are also taken into account - protection from the selection of confidential data and payment information. The map is analyzed by country of issue, geography of use, owner. The history of previous payments is being studied.
- Red. Danger of fraud, cardholder authentication is required. Such a label is automatically assigned to translations with non-standard characteristics - for example, a user from France pays for a purchase in a Russian online store with a card issued in the UK.
- Yellow. For example, if the amount of payment is significantly higher than the average for a particular store. There is a possibility of fraud, additional verification is required.
- Green. Payment is carried out within one country, the payment amount is average. Minimal chance of fraud.
Relationship between antifraud and user authentication * Hidden text: cannot be quoted. *
* Hidden text: cannot be quoted. *
What antifraud tasks does the product solve?
ANTIFRAUD allows you to control internal and external fraudulent schemes and process each loan application within 40 seconds. Main functions:
When a rule is triggered, the entire database is analyzed. Alarms are clearly visualized, the system instantly adapts to changes in conditions. With the help of control of internal and external schemes, the likelihood of obtaining loans for fake details, for invalid documents or for goods for the purpose of cashing is reduced to zero. In addition, applications with photocopies of documents or made in collusion / under pressure are rejected. Confirmed fraud profiles are added to the blacklist, after which the updated data is transmitted to the automated banking system.
- Checking information about the applicant against blacklists.
- Identifying data inconsistencies in loan applications by cross-checking and comparing with other applications.
- Supplementing the client's personal data with information from external sources.
- Fuzzy data comparison algorithms.
Living in the age of information technology, we are constantly faced with fraudulent schemes of one kind or another - as soon as one attacker manages to deceive the system, he spreads a loophole among the rest. Fortunately, modern security services can learn and are becoming more productive every day. We offer to order a presentation and see for yourself how the anti-fraud works effectively.
eplyTo combat fraud and theft of confidential information, banking systems use antifraud. These systems are aimed at detecting and preventing fraudulent attacks, and this is implemented by dozens of different methods.
What is antifraud: tasks and methods
Let's talk about the goals and methods of antifraud that are relevant at the moment.
Let's understand the terminology
Antifraud system is a set of measures that allow you to evaluate banking or Internet transactions for the degree of the likelihood of fraud. To do this, the system tries on certain criteria for each operation - and if it does not correspond to them, then it checks it more thoroughly and signals it.
Built-in filters help to recognize unusual behavior and assess the risks of the operation, and then apply measures to allow or deny it. In disputable situations, the final solution to the issue is passed on to the bank's employees, who are called fraud analysts (fraud is fraud in order to take possession of other people's funds or property by fraud).
Banks and regulators have been actively cooperating with each other in recent years, creating new recommendations for identifying fraudulent schemes. Financial organizations exchange information with each other, and self-learning anti-fraud systems analyze Big Data and learn to make decisions based on this analysis. According to a study by the National Bureau of Credit Histories, already in 2017, shortly after the massive introduction of anti-fraud systems in banks, the number of loans with suspicious signs decreased by 15%. Similar solutions are increasingly being implemented by representatives of small and medium-sized businesses, especially due to the availability of low-cost cloud solutions on the market.
How the anti-fraud process works
Each transaction first goes through the first "line of defense": it is checked for compliance with the established restrictions, such as the limit on the volume of purchases on the card, the maximum one-time purchase amount, the number of users of one card, the number of cards for one client, etc. If all these checks have passed successfully, then the next, more serious ones come into play.
Based on their results, the antifraud assigns one of the conditional "labels" to the operation:
For all checks, the user must be recognized according to one or another algorithm. The standard protection settings are also taken into account - protection from the selection of confidential data and payment information. The map is analyzed by country of issue, geography of use, owner. The history of previous payments is being studied.
- Red. Danger of fraud, cardholder authentication is required. Such a label is automatically assigned to translations with non-standard characteristics - for example, a user from France pays for a purchase in a Russian online store with a card issued in the UK.
- Yellow. For example, if the amount of payment is significantly higher than the average for a particular store. There is a possibility of fraud, additional verification is required.
- Green. Payment is carried out within one country, the payment amount is average. Minimal chance of fraud.
Relationship between antifraud and user authentication * Hidden text: cannot be quoted. *
* Hidden text: cannot be quoted. *
What antifraud tasks does the product solve?
ANTIFRAUD allows you to control internal and external fraudulent schemes and process each loan application within 40 seconds. Main functions:
When a rule is triggered, the entire database is analyzed. Alarms are clearly visualized, the system instantly adapts to changes in conditions. With the help of control of internal and external schemes, the likelihood of obtaining loans for fake details, for invalid documents or for goods for the purpose of cashing is reduced to zero. In addition, applications with photocopies of documents or made in collusion / under pressure are rejected. Confirmed fraud profiles are added to the blacklist, after which the updated data is transmitted to the automated banking system.
- Checking information about the applicant against blacklists.
- Identifying data inconsistencies in loan applications by cross-checking and comparing with other applications.
- Supplementing the client's personal data with information from external sources.
- Fuzzy data comparison algorithms.
Living in the age of information technology, we are constantly faced with fraudulent schemes of one kind or another - as soon as one attacker manages to deceive the system, he spreads a loophole among the rest. Fortunately, modern security services can learn and are becoming more productive every day. We offer to order a presentation and see for yourself how the anti-fraud works effectively.
goodTo combat fraud and theft of confidential information, banking systems use antifraud. These systems are aimed at detecting and preventing fraudulent attacks, and this is implemented by dozens of different methods.
What is antifraud: tasks and methods
Let's talk about the goals and methods of antifraud that are relevant at the moment.
Let's understand the terminology
Antifraud system is a set of measures that allow you to evaluate banking or Internet transactions for the degree of the likelihood of fraud. To do this, the system tries on certain criteria for each operation - and if it does not correspond to them, then it checks it more thoroughly and signals it.
Built-in filters help to recognize unusual behavior and assess the risks of the operation, and then apply measures to allow or deny it. In disputable situations, the final solution to the issue is passed on to the bank's employees, who are called fraud analysts (fraud is fraud in order to take possession of other people's funds or property by fraud).
Banks and regulators have been actively cooperating with each other in recent years, creating new recommendations for identifying fraudulent schemes. Financial organizations exchange information with each other, and self-learning anti-fraud systems analyze Big Data and learn to make decisions based on this analysis. According to a study by the National Bureau of Credit Histories, already in 2017, shortly after the massive introduction of anti-fraud systems in banks, the number of loans with suspicious signs decreased by 15%. Similar solutions are increasingly being implemented by representatives of small and medium-sized businesses, especially due to the availability of low-cost cloud solutions on the market.
How the anti-fraud process works
Each transaction first goes through the first "line of defense": it is checked for compliance with the established restrictions, such as the limit on the volume of purchases on the card, the maximum one-time purchase amount, the number of users of one card, the number of cards for one client, etc. If all these checks have passed successfully, then the next, more serious ones come into play.
Based on their results, the antifraud assigns one of the conditional "labels" to the operation:
For all checks, the user must be recognized according to one or another algorithm. The standard protection settings are also taken into account - protection from the selection of confidential data and payment information. The map is analyzed by country of issue, geography of use, owner. The history of previous payments is being studied.
- Red. Danger of fraud, cardholder authentication is required. Such a label is automatically assigned to translations with non-standard characteristics - for example, a user from France pays for a purchase in a Russian online store with a card issued in the UK.
- Yellow. For example, if the amount of payment is significantly higher than the average for a particular store. There is a possibility of fraud, additional verification is required.
- Green. Payment is carried out within one country, the payment amount is average. Minimal chance of fraud.
A csalás és a felhasználói hitelesítés közötti kapcsolat * Rejtett szöveg: nem idézhető. *
* Rejtett szöveg: nem idézhető. *
Milyen csalás elleni feladatokat old meg a termék?
Az ANTIFRAUD lehetővé teszi a belső és külső csalárd rendszerek ellenőrzését, és az egyes hitelkérelmek feldolgozását 40 másodpercen belül. Fő funkciók:
Amikor egy szabály elindul, a teljes adatbázist elemezzük. A riasztások egyértelműen láthatók, a rendszer azonnal alkalmazkodik a körülmények változásaihoz. A belső és külső rendszerek ellenőrzésének segítségével nullára csökken a hamis részletekhez, érvénytelen dokumentumokhoz vagy árukhoz történő kölcsönszerzés valószínűsége. Ezenkívül a dokumentumok fénymásolatával vagy összejátszással / nyomás alatt benyújtott kérelmeket elutasítják. A megerősített csalási profilokat hozzáadják a feketelistához, majd a frissített adatokat továbbítják az automatizált bankrendszerhez.
- A kérelmezővel kapcsolatos információk ellenőrzése a feketelisták ellen.
- A hitelkérelmek adatkonzisztenciáinak azonosítása keresztellenőrzéssel és más alkalmazásokkal való összehasonlítással.
- Az ügyfél személyes adatainak kiegészítése külső forrásokból származó információkkal.
- Homályos adat-összehasonlító algoritmusok.
Az információs technológia korában élve állandóan szembesülünk valamilyen csalárd rendszerrel - amint az egyik támadó képes megtéveszteni a rendszert, kiskaput terjeszt a többiek között. Szerencsére a modern biztonsági szolgálatok megtanulhatnak és minden nap termelékenyebbé válnak. Kínálunk egy prezentáció megrendelésére és annak megismerésére, hogy a csalás elleni küzdelem hogyan működik hatékonyan.
ty
tyTo combat fraud and theft of confidential information, banking systems use antifraud. These systems are aimed at detecting and preventing fraudulent attacks, and this is implemented by dozens of different methods.
What is antifraud: tasks and methods
Let's talk about the goals and methods of antifraud that are relevant at the moment.
Let's understand the terminology
Antifraud system is a set of measures that allow you to evaluate banking or Internet transactions for the degree of the likelihood of fraud. To do this, the system tries on certain criteria for each operation - and if it does not correspond to them, then it checks it more thoroughly and signals it.
Built-in filters help to recognize unusual behavior and assess the risks of the operation, and then apply measures to allow or deny it. In disputable situations, the final solution to the issue is passed on to the bank's employees, who are called fraud analysts (fraud is fraud in order to take possession of other people's funds or property by fraud).
Banks and regulators have been actively cooperating with each other in recent years, creating new recommendations for identifying fraudulent schemes. Financial organizations exchange information with each other, and self-learning anti-fraud systems analyze Big Data and learn to make decisions based on this analysis. According to a study by the National Bureau of Credit Histories, already in 2017, shortly after the massive introduction of anti-fraud systems in banks, the number of loans with suspicious signs decreased by 15%. Similar solutions are increasingly being implemented by representatives of small and medium-sized businesses, especially due to the availability of low-cost cloud solutions on the market.
How the anti-fraud process works
Each transaction first goes through the first "line of defense": it is checked for compliance with the established restrictions, such as the limit on the volume of purchases on the card, the maximum one-time purchase amount, the number of users of one card, the number of cards for one client, etc. If all these checks have passed successfully, then the next, more serious ones come into play.
Based on their results, the antifraud assigns one of the conditional "labels" to the operation:
For all checks, the user must be recognized according to one or another algorithm. The standard protection settings are also taken into account - protection from the selection of confidential data and payment information. The map is analyzed by country of issue, geography of use, owner. The history of previous payments is being studied.
- Red. Danger of fraud, cardholder authentication is required. Such a label is automatically assigned to translations with non-standard characteristics - for example, a user from France pays for a purchase in a Russian online store with a card issued in the UK.
- Yellow. For example, if the amount of payment is significantly higher than the average for a particular store. There is a possibility of fraud, additional verification is required.
- Green. Payment is carried out within one country, the payment amount is average. Minimal chance of fraud.
Relationship between antifraud and user authentication * Hidden text: cannot be quoted. *
* Hidden text: cannot be quoted. *
What antifraud tasks does the product solve?
ANTIFRAUD allows you to control internal and external fraudulent schemes and process each loan application within 40 seconds. Main functions:
When a rule is triggered, the entire database is analyzed. Alarms are clearly visualized, the system instantly adapts to changes in conditions. With the help of control of internal and external schemes, the likelihood of obtaining loans for fake details, for invalid documents or for goods for the purpose of cashing is reduced to zero. In addition, applications with photocopies of documents or made in collusion / under pressure are rejected. Confirmed fraud profiles are added to the blacklist, after which the updated data is transmitted to the automated banking system.
- Checking information about the applicant against blacklists.
- Identifying data inconsistencies in loan applications by cross-checking and comparing with other applications.
- Supplementing the client's personal data with information from external sources.
- Fuzzy data comparison algorithms.
Living in the age of information technology, we are constantly faced with fraudulent schemes of one kind or another - as soon as one attacker manages to deceive the system, he spreads a loophole among the rest. Fortunately, modern security services can learn and are becoming more productive every day. We offer to order a presentation and see for yourself how the anti-fraud works effectively.
Good infoTo combat fraud and theft of confidential information, banking systems use antifraud. These systems are aimed at detecting and preventing fraudulent attacks, and this is implemented by dozens of different methods.
What is antifraud: tasks and methods
Let's talk about the goals and methods of antifraud that are relevant at the moment.
Let's understand the terminology
Antifraud system is a set of measures that allow you to evaluate banking or Internet transactions for the degree of the likelihood of fraud. To do this, the system tries on certain criteria for each operation - and if it does not correspond to them, then it checks it more thoroughly and signals it.
Built-in filters help to recognize unusual behavior and assess the risks of the operation, and then apply measures to allow or deny it. In disputable situations, the final solution to the issue is passed on to the bank's employees, who are called fraud analysts (fraud is fraud in order to take possession of other people's funds or property by fraud).
Banks and regulators have been actively cooperating with each other in recent years, creating new recommendations for identifying fraudulent schemes. Financial organizations exchange information with each other, and self-learning anti-fraud systems analyze Big Data and learn to make decisions based on this analysis. According to a study by the National Bureau of Credit Histories, already in 2017, shortly after the massive introduction of anti-fraud systems in banks, the number of loans with suspicious signs decreased by 15%. Similar solutions are increasingly being implemented by representatives of small and medium-sized businesses, especially due to the availability of low-cost cloud solutions on the market.
How the anti-fraud process works
Each transaction first goes through the first "line of defense": it is checked for compliance with the established restrictions, such as the limit on the volume of purchases on the card, the maximum one-time purchase amount, the number of users of one card, the number of cards for one client, etc. If all these checks have passed successfully, then the next, more serious ones come into play.
Based on their results, the antifraud assigns one of the conditional "labels" to the operation:
For all checks, the user must be recognized according to one or another algorithm. The standard protection settings are also taken into account - protection from the selection of confidential data and payment information. The map is analyzed by country of issue, geography of use, owner. The history of previous payments is being studied.
- Red. Danger of fraud, cardholder authentication is required. Such a label is automatically assigned to translations with non-standard characteristics - for example, a user from France pays for a purchase in a Russian online store with a card issued in the UK.
- Yellow. For example, if the amount of payment is significantly higher than the average for a particular store. There is a possibility of fraud, additional verification is required.
- Green. Payment is carried out within one country, the payment amount is average. Minimal chance of fraud.
Relationship between antifraud and user authentication * Hidden text: cannot be quoted. *
* Hidden text: cannot be quoted. *
What antifraud tasks does the product solve?
ANTIFRAUD allows you to control internal and external fraudulent schemes and process each loan application within 40 seconds. Main functions:
When a rule is triggered, the entire database is analyzed. Alarms are clearly visualized, the system instantly adapts to changes in conditions. With the help of control of internal and external schemes, the likelihood of obtaining loans for fake details, for invalid documents or for goods for the purpose of cashing is reduced to zero. In addition, applications with photocopies of documents or made in collusion / under pressure are rejected. Confirmed fraud profiles are added to the blacklist, after which the updated data is transmitted to the automated banking system.
- Checking information about the applicant against blacklists.
- Identifying data inconsistencies in loan applications by cross-checking and comparing with other applications.
- Supplementing the client's personal data with information from external sources.
- Fuzzy data comparison algorithms.
Living in the age of information technology, we are constantly faced with fraudulent schemes of one kind or another - as soon as one attacker manages to deceive the system, he spreads a loophole among the rest. Fortunately, modern security services can learn and are becoming more productive every day. We offer to order a presentation and see for yourself how the anti-fraud works effectively.
go go.To combat fraud and theft of confidential information, banking systems use antifraud. These systems are aimed at detecting and preventing fraudulent attacks, and this is implemented by dozens of different methods.
What is antifraud: tasks and methods
Let's talk about the goals and methods of antifraud that are relevant at the moment.
Let's understand the terminology
Antifraud system is a set of measures that allow you to evaluate banking or Internet transactions for the degree of the likelihood of fraud. To do this, the system tries on certain criteria for each operation - and if it does not correspond to them, then it checks it more thoroughly and signals it.
Built-in filters help to recognize unusual behavior and assess the risks of the operation, and then apply measures to allow or deny it. In disputable situations, the final solution to the issue is passed on to the bank's employees, who are called fraud analysts (fraud is fraud in order to take possession of other people's funds or property by fraud).
Banks and regulators have been actively cooperating with each other in recent years, creating new recommendations for identifying fraudulent schemes. Financial organizations exchange information with each other, and self-learning anti-fraud systems analyze Big Data and learn to make decisions based on this analysis. According to a study by the National Bureau of Credit Histories, already in 2017, shortly after the massive introduction of anti-fraud systems in banks, the number of loans with suspicious signs decreased by 15%. Similar solutions are increasingly being implemented by representatives of small and medium-sized businesses, especially due to the availability of low-cost cloud solutions on the market.
How the anti-fraud process works
Each transaction first goes through the first "line of defense": it is checked for compliance with the established restrictions, such as the limit on the volume of purchases on the card, the maximum one-time purchase amount, the number of users of one card, the number of cards for one client, etc. If all these checks have passed successfully, then the next, more serious ones come into play.
Based on their results, the antifraud assigns one of the conditional "labels" to the operation:
For all checks, the user must be recognized according to one or another algorithm. The standard protection settings are also taken into account - protection from the selection of confidential data and payment information. The map is analyzed by country of issue, geography of use, owner. The history of previous payments is being studied.
- Red. Danger of fraud, cardholder authentication is required. Such a label is automatically assigned to translations with non-standard characteristics - for example, a user from France pays for a purchase in a Russian online store with a card issued in the UK.
- Yellow. For example, if the amount of payment is significantly higher than the average for a particular store. There is a possibility of fraud, additional verification is required.
- Green. Payment is carried out within one country, the payment amount is average. Minimal chance of fraud.
Relationship between antifraud and user authentication * Hidden text: cannot be quoted. *
* Hidden text: cannot be quoted. *
What antifraud tasks does the product solve?
ANTIFRAUD allows you to control internal and external fraudulent schemes and process each loan application within 40 seconds. Main functions:
When a rule is triggered, the entire database is analyzed. Alarms are clearly visualized, the system instantly adapts to changes in conditions. With the help of control of internal and external schemes, the likelihood of obtaining loans for fake details, for invalid documents or for goods for the purpose of cashing is reduced to zero. In addition, applications with photocopies of documents or made in collusion / under pressure are rejected. Confirmed fraud profiles are added to the blacklist, after which the updated data is transmitted to the automated banking system.
- Checking information about the applicant against blacklists.
- Identifying data inconsistencies in loan applications by cross-checking and comparing with other applications.
- Supplementing the client's personal data with information from external sources.
- Fuzzy data comparison algorithms.
Living in the age of information technology, we are constantly faced with fraudulent schemes of one kind or another - as soon as one attacker manages to deceive the system, he spreads a loophole among the rest. Fortunately, modern security services can learn and are becoming more productive every day. We offer to order a presentation and see for yourself how the anti-fraud works effectively.
okay thank youTo combat fraud and theft of confidential information, banking systems use antifraud. These systems are aimed at detecting and preventing fraudulent attacks, and this is implemented by dozens of different methods.
What is antifraud: tasks and methods
Let's talk about the goals and methods of antifraud that are relevant at the moment.
Let's understand the terminology
Antifraud system is a set of measures that allow you to evaluate banking or Internet transactions for the degree of the likelihood of fraud. To do this, the system tries on certain criteria for each operation - and if it does not correspond to them, then it checks it more thoroughly and signals it.
Built-in filters help to recognize unusual behavior and assess the risks of the operation, and then apply measures to allow or deny it. In disputable situations, the final solution to the issue is passed on to the bank's employees, who are called fraud analysts (fraud is fraud in order to take possession of other people's funds or property by fraud).
Banks and regulators have been actively cooperating with each other in recent years, creating new recommendations for identifying fraudulent schemes. Financial organizations exchange information with each other, and self-learning anti-fraud systems analyze Big Data and learn to make decisions based on this analysis. According to a study by the National Bureau of Credit Histories, already in 2017, shortly after the massive introduction of anti-fraud systems in banks, the number of loans with suspicious signs decreased by 15%. Similar solutions are increasingly being implemented by representatives of small and medium-sized businesses, especially due to the availability of low-cost cloud solutions on the market.
How the anti-fraud process works
Each transaction first goes through the first "line of defense": it is checked for compliance with the established restrictions, such as the limit on the volume of purchases on the card, the maximum one-time purchase amount, the number of users of one card, the number of cards for one client, etc. If all these checks have passed successfully, then the next, more serious ones come into play.
Based on their results, the antifraud assigns one of the conditional "labels" to the operation:
For all checks, the user must be recognized according to one or another algorithm. The standard protection settings are also taken into account - protection from the selection of confidential data and payment information. The map is analyzed by country of issue, geography of use, owner. The history of previous payments is being studied.
- Red. Danger of fraud, cardholder authentication is required. Such a label is automatically assigned to translations with non-standard characteristics - for example, a user from France pays for a purchase in a Russian online store with a card issued in the UK.
- Yellow. For example, if the amount of payment is significantly higher than the average for a particular store. There is a possibility of fraud, additional verification is required.
- Green. Payment is carried out within one country, the payment amount is average. Minimal chance of fraud.
Relationship between antifraud and user authentication * Hidden text: cannot be quoted. *
* Hidden text: cannot be quoted. *
What antifraud tasks does the product solve?
ANTIFRAUD allows you to control internal and external fraudulent schemes and process each loan application within 40 seconds. Main functions:
When a rule is triggered, the entire database is analyzed. Alarms are clearly visualized, the system instantly adapts to changes in conditions. With the help of control of internal and external schemes, the likelihood of obtaining loans for fake details, for invalid documents or for goods for the purpose of cashing is reduced to zero. In addition, applications with photocopies of documents or made in collusion / under pressure are rejected. Confirmed fraud profiles are added to the blacklist, after which the updated data is transmitted to the automated banking system.
- Checking information about the applicant against blacklists.
- Identifying data inconsistencies in loan applications by cross-checking and comparing with other applications.
- Supplementing the client's personal data with information from external sources.
- Fuzzy data comparison algorithms.
Living in the age of information technology, we are constantly faced with fraudulent schemes of one kind or another - as soon as one attacker manages to deceive the system, he spreads a loophole among the rest. Fortunately, modern security services can learn and are becoming more productive every day. We offer to order a presentation and see for yourself how the anti-fraud works effectively.
LikedPara combatir el fraude y el robo de información confidencial, los sistemas bancarios utilizan sistemas antifraude. Estos sistemas tienen como objetivo detectar y prevenir ataques fraudulentos y se implementan mediante decenas de métodos diferentes.
¿Qué es la lucha contra el fraude? Tareas y métodos
Hablemos de los objetivos y métodos de lucha contra el fraude que son relevantes en este momento.
Entendamos la terminología
El sistema antifraude es un conjunto de medidas que permiten evaluar el grado de probabilidad de fraude en las transacciones bancarias o por Internet. Para ello, el sistema prueba determinados criterios para cada operación y, si no los cumple, los comprueba con más detalle y los señala.
Los filtros integrados permiten reconocer comportamientos inusuales y evaluar los riesgos de la operación, para luego aplicar medidas para permitirla o denegarla. En situaciones controvertidas, la solución final del problema se traslada a los empleados del banco, que se denominan analistas de fraude (el fraude es el fraude cuyo objetivo es apoderarse de los fondos o bienes de otras personas mediante fraude).
En los últimos años, los bancos y los organismos reguladores han estado cooperando activamente entre sí y han creado nuevas recomendaciones para identificar esquemas fraudulentos. Las organizaciones financieras intercambian información entre sí y los sistemas antifraude de autoaprendizaje analizan Big Data y aprenden a tomar decisiones basadas en este análisis. Según un estudio de la Oficina Nacional de Historial Crediticio, ya en 2017, poco después de la introducción masiva de sistemas antifraude en los bancos, el número de préstamos con signos sospechosos disminuyó en un 15%. Los representantes de las pequeñas y medianas empresas están implementando cada vez más soluciones similares, especialmente debido a la disponibilidad de soluciones en la nube de bajo costo en el mercado.
Cómo funciona el proceso antifraude
Cada transacción pasa primero por la primera "línea de defensa": se comprueba el cumplimiento de las restricciones establecidas, como el límite en el volumen de compras con la tarjeta, el importe máximo de compra única, el número de usuarios de una tarjeta, el número de tarjetas por cliente, etc. Si todas estas comprobaciones han pasado con éxito, entran en juego las siguientes, más serias.
En función de sus resultados, el sistema antifraude asigna a la operación una de las siguientes "etiquetas" condicionales:
Para todas las comprobaciones, el usuario debe ser reconocido según uno u otro algoritmo. También se tienen en cuenta las configuraciones de protección estándar: protección contra la selección de datos confidenciales e información de pago. El mapa se analiza por país de emisión, geografía de uso y propietario. Se estudia el historial de pagos anteriores.
- Rojo. Peligro de fraude, se requiere la autenticación del titular de la tarjeta. Esta etiqueta se asigna automáticamente a las traducciones con características no estándar; por ejemplo, un usuario de Francia paga una compra en una tienda en línea rusa con una tarjeta emitida en el Reino Unido.
- Amarillo. Por ejemplo, si el importe del pago es significativamente superior al promedio de una tienda en particular, existe la posibilidad de fraude y se requiere una verificación adicional.
- Verde. El pago se realiza dentro de un país, el importe del pago es medio. Mínima probabilidad de fraude.
Relación entre antifraude y autenticación de usuarios * Texto oculto: no se puede citar. *
Texto oculto: no se puede citar.
¿Qué tareas antifraude resuelve el producto?
ANTIFRAUDE le permite controlar los esquemas fraudulentos internos y externos y procesar cada solicitud de préstamo en 40 segundos. Funciones principales:
Cuando se activa una regla, se analiza toda la base de datos. Las alarmas se visualizan claramente y el sistema se adapta instantáneamente a los cambios de condiciones. Con la ayuda del control de los esquemas internos y externos, la probabilidad de obtener préstamos con datos falsos, documentos inválidos o bienes con fines de cobro se reduce a cero. Además, se rechazan las solicitudes con fotocopias de documentos o realizadas en colusión/bajo presión. Los perfiles de fraude confirmados se agregan a la lista negra, después de lo cual los datos actualizados se transmiten al sistema bancario automatizado.
- Verificación de información sobre el solicitante contra listas negras.
- Identificar inconsistencias de datos en solicitudes de préstamos mediante verificación cruzada y comparación con otras solicitudes.
- Complementar los datos personales del cliente con información de fuentes externas.
- Algoritmos de comparación de datos difusos.
Vivimos en la era de la tecnología de la información y nos enfrentamos constantemente a esquemas fraudulentos de un tipo u otro: tan pronto como un atacante logra engañar al sistema, difunde una falla entre los demás. Afortunadamente, los servicios de seguridad modernos pueden aprender y son cada día más productivos. Le ofrecemos solicitar una presentación para que vea por sí mismo cómo funciona la lucha contra el fraude de manera efectiva.