Without real-time fraud monitoring software platforms, it is impossible to imagine the security of systems in the financial industry. Generated alerts can block and prevent fraudulent transactions: withdrawal of customer funds to third-party accounts, illegal currency transactions, falsification of loan applications and compromise of personal data of customers.
We have prepared an introductory material to use as an introduction to the basics of fraud monitoring and setting up alerts-both in the financial and other sectors. Here you will learn about modern developments in the domestic software market, about those forced compromises: between convenience, processing speed, fault tolerance and security.
Cybertonika has developed solutions for fraud monitoring that use a dynamic approach, self-learning algorithms, and minimize both missing suspicious actions and groundless locks, freezes, and failures in the client application.
According to global analysts ' estimates, during the pandemic, the volume of electronic fraud increased by 46%. A sharp increase in fraud cases was noted by three quarters of all existing online stores.
According to the Central Bank of the Russian Federation, spending on combating fraud increased by 10 billion rubles in one year. In general, according to estimates of the international agency "Crowe", fraud in its various manifestations costs the world economy more than $ 5.127 trillion. annually.
The antifraud platform continuously monitors, scores, and analyzes data. In addition, the platform is able to work with critical points in the process – events such as user registration and payments.
In an online store, such a system can track the behavior of each customer, as well as collect all available information about them, including those that they themselves provided. When someone creates a new account, logs in, and enters their payment card details at checkout – you can profile the user and their intentions at all these points.
Sources of this type of information include:
You can view detailed reports either manually or automatically set up new principles for the system's response based on them.
A specific action can trigger several triggers, each of which degrades the user's rating, putting the event at a higher risk level.
At the exit, the transaction will either be blocked or an alert will be sent out, which will require the intervention of a real person. An alert can be sent even for a client that seems trustworthy to the system.
If the user is using yandex. Mail "[email protected]" if it tries to make a payment, the system will block it and generate an alert.
You can create a certain blacklist of addresses, which will include all such suspicious email addresses. At the same time, other users will not experience any problems in using the software functionality.
Creating a blacklist is a convenient feature, but it requires too specific a comparison condition. For example, not every email address that includes trigger words like "fraudster" can actually belong to intruders. It is also worth noting that maintaining the relevance of black lists is expensive work, which, when expanding the scale of the business, turns into nonsense at all.
To identify and block various types of scammers and notify analysts about their activity with alerts, more general principles are needed. Rule sets are much more complex. Software platforms for fraud monitoring ensure their precise adjustment, and often even allow you to test new rules in a separate "sandbox".
An example of a working rule that is used by customers of such software solutions: "If more than 4 different accounts have logged in from the same IP address within 10 minutes, block the IP address for 1 hour and send an alert".
Here is a real-life example: a single pensioner who used an online bank or payment service for a whole year (she made a lot of typos during registration), usually entered it correctly only the second time when ordering food and household hygiene products. Suddenly, the system found that it began to fill in the data entry fields much faster, and then requested loan approval for a modern gadget. Suspicious? Of course!
For non-banks and non-bank fintech, we can offer more flexibility and lower customer churn, because we can provide a higher level of service to customers who so value freedom from traditional banks with their formalism.
In fact, the technology of dynamic adjustment from the company "Cybertonika" can help any business that is important to provide a loyal and comfortable service to the client-regardless of the field, to guarantee the approval of the actions of good customers, while minimizing failures. Only suspicious users will have to re-authenticate and / or perform additional verification.
Scoring provides a quick risk assessment for each user and / or action. Based on this assessment, a final decision is made: a pensioner manages the device, or fraudsters got access to her account.
A convenient dashboard is available for editing and updating rules at any stage.
Neobanks can implement fraud monitoring solutions that work covertly where possible. At the same time, the client will not even feel the transition to new standards. Such organizations can also use a dynamic approach: block the client session only in case of suspicions of various kinds: from KYC verification to online card transactions, and so on.
Risk ratings are a strategic basis for modern fraud monitoring. Hundreds of parameters of the observation array that characterize the client's intentions are taken into account, evaluated in a complex, and the analyst receives a numerical threat assessment at the output: "Is our client a likely fraudster?".
When evaluating,the system collects all the described parameters, and also takes into account every fact, even if it is slightly significant. Based on the results of scoring, the system determines whether to send an alert.
Often, users with a high scoring score are automatically blocked by the system, while those with a low risk score are skipped. Users with an average level of risk are sent for verification manually, or they are asked to pass additional verification.
Platforms with custom rules can adapt to any needs, and the customer determines the actions of the system in each general case.
For companies using fraud monitoring solutions, usability is important, so the platform should be as simple as possible, have a demo version available for testing, free support, fast deployment, and, finally, transparency in operation.
Some key features that you should pay attention to when selecting software for fraud monitoring:
Real-time fraud monitoring will help you catch fraudsters in hot pursuit, and properly configured alerts will allow you to keep your finger on the pulse and provide a consistently high level of protection.
We have prepared an introductory material to use as an introduction to the basics of fraud monitoring and setting up alerts-both in the financial and other sectors. Here you will learn about modern developments in the domestic software market, about those forced compromises: between convenience, processing speed, fault tolerance and security.
Cybertonika has developed solutions for fraud monitoring that use a dynamic approach, self-learning algorithms, and minimize both missing suspicious actions and groundless locks, freezes, and failures in the client application.
Scope of the problem
Scammers are becoming more sophisticated every second. Fraudsters and scammers are no longer targeted exclusively at tech giants, who have now learned to deal with these inconveniences more easily. Fraud is now a real threat to organizations of all types, sizes, and countries.According to global analysts ' estimates, during the pandemic, the volume of electronic fraud increased by 46%. A sharp increase in fraud cases was noted by three quarters of all existing online stores.
According to the Central Bank of the Russian Federation, spending on combating fraud increased by 10 billion rubles in one year. In general, according to estimates of the international agency "Crowe", fraud in its various manifestations costs the world economy more than $ 5.127 trillion. annually.
How the fraud monitoring software platform works
Modern solutions for fraud monitoring are comprehensive software that is implemented at all customer service points for products and services. As a rule, work takes place via the API on the backend. Additionally, a frontend component is used to transmit digital fingerprints of the user's device.The antifraud platform continuously monitors, scores, and analyzes data. In addition, the platform is able to work with critical points in the process – events such as user registration and payments.
In an online store, such a system can track the behavior of each customer, as well as collect all available information about them, including those that they themselves provided. When someone creates a new account, logs in, and enters their payment card details at checkout – you can profile the user and their intentions at all these points.
Sources of this type of information include:
- IP analysis;
- digital device fingerprints;
- digital browser fingerprints;
- User activity history (digital footprint) and social profile;
- behavioral analysis and speed measurements of user actions;
- biometrics.
You can view detailed reports either manually or automatically set up new principles for the system's response based on them.
Configuring Alerts
Rule sets define the necessary actions of the system in the event of an emergency situation. There may be hundreds of such rules. However, they should not be mutually exclusive!A specific action can trigger several triggers, each of which degrades the user's rating, putting the event at a higher risk level.
At the exit, the transaction will either be blocked or an alert will be sent out, which will require the intervention of a real person. An alert can be sent even for a client that seems trustworthy to the system.
Alerts and locks: a simple and "working" way
Sets of security principles for fraud monitoring can be simple or as complex as you like. Here is an example of how one of the simple rules works.If the user is using yandex. Mail "[email protected]" if it tries to make a payment, the system will block it and generate an alert.
You can create a certain blacklist of addresses, which will include all such suspicious email addresses. At the same time, other users will not experience any problems in using the software functionality.
Creating a blacklist is a convenient feature, but it requires too specific a comparison condition. For example, not every email address that includes trigger words like "fraudster" can actually belong to intruders. It is also worth noting that maintaining the relevance of black lists is expensive work, which, when expanding the scale of the business, turns into nonsense at all.
To identify and block various types of scammers and notify analysts about their activity with alerts, more general principles are needed. Rule sets are much more complex. Software platforms for fraud monitoring ensure their precise adjustment, and often even allow you to test new rules in a separate "sandbox".
An example of a working rule that is used by customers of such software solutions: "If more than 4 different accounts have logged in from the same IP address within 10 minutes, block the IP address for 1 hour and send an alert".
Here is a real-life example: a single pensioner who used an online bank or payment service for a whole year (she made a lot of typos during registration), usually entered it correctly only the second time when ordering food and household hygiene products. Suddenly, the system found that it began to fill in the data entry fields much faster, and then requested loan approval for a modern gadget. Suspicious? Of course!
Cybertonica's approach to fraud monitoring and customization
Cybertonica's mission is to fight fraud. But for each decision maker and fraud analyst, the optimal level of automation is determined independently. Fulfilling its mission, the Cybertonics solution precisely adapts the offered tools to the needs of each customer, in accordance with their convenience, as well as with their field of activity and the nature of threats.For non-banks and non-bank fintech, we can offer more flexibility and lower customer churn, because we can provide a higher level of service to customers who so value freedom from traditional banks with their formalism.
In fact, the technology of dynamic adjustment from the company "Cybertonika" can help any business that is important to provide a loyal and comfortable service to the client-regardless of the field, to guarantee the approval of the actions of good customers, while minimizing failures. Only suspicious users will have to re-authenticate and / or perform additional verification.
How the scoring system works
The unified Cybertonica platform supports real-time monitoring of more than 100 individual parameters of data collected using advanced technologies, including digital footprint analysis, digital device fingerprints, behavior analysis, and more. The metrics are then combined using the data aggregation module into easy-to-read profiles for subsequent risk scoring evaluation.Scoring provides a quick risk assessment for each user and / or action. Based on this assessment, a final decision is made: a pensioner manages the device, or fraudsters got access to her account.
Cybertonica is easy to set up
Our solution Fraud Suite – sets of rules that can be generated in several ways:- generate rules using the whitebox machine learning algorithm based on historical data
- choose from ready-made industry-specific default rule settings that are tailored to the most common threats in each industry.;
- scores;
- written manually in an explicit combination of the above.
A convenient dashboard is available for editing and updating rules at any stage.
Fraud monitoring and neobanks
Fraud monitoring platforms are also necessary for non-banks. Although fraud monitoring is important for all banks – a dilemma arises for non-banking organizations and non-banks: is it acceptable for them to sacrifice the convenience of the service to protect customers from fraud? Fortunately, this is a false dilemma. Despite the fact that banks face many challenges in complying with local anti-money laundering laws, the topic of our discussion equalizes all banks.Neobanks can implement fraud monitoring solutions that work covertly where possible. At the same time, the client will not even feel the transition to new standards. Such organizations can also use a dynamic approach: block the client session only in case of suspicions of various kinds: from KYC verification to online card transactions, and so on.
Risk management-the basis of fraud monitoring
If the purpose of the anti-fraud platform is considered to be fraud prevention, then fraud monitoring based on risk scoring is the main means to achieve it.Risk ratings are a strategic basis for modern fraud monitoring. Hundreds of parameters of the observation array that characterize the client's intentions are taken into account, evaluated in a complex, and the analyst receives a numerical threat assessment at the output: "Is our client a likely fraudster?".
When evaluating,the system collects all the described parameters, and also takes into account every fact, even if it is slightly significant. Based on the results of scoring, the system determines whether to send an alert.
Often, users with a high scoring score are automatically blocked by the system, while those with a low risk score are skipped. Users with an average level of risk are sent for verification manually, or they are asked to pass additional verification.
Platforms with custom rules can adapt to any needs, and the customer determines the actions of the system in each general case.
How to choose an anti-fraud platform
Fraud monitoring platforms should be flexible to adapt to customer needs, scalable and constantly evolving to respond to constantly changing fraudulent schemes.For companies using fraud monitoring solutions, usability is important, so the platform should be as simple as possible, have a demo version available for testing, free support, fast deployment, and, finally, transparency in operation.
Some key features that you should pay attention to when selecting software for fraud monitoring:
- real-time monitoring;
- data integration with email and telephony;
- machine learning;
- custom rules;
- behavioral analytics ;
- simplified authentication of service users depending on the risk assessment;
- fraud scoring model;
- custom queries;
- visualization, graphs;
- space for the sandbox;
- reports and alerts.
Real-time fraud monitoring will help you catch fraudsters in hot pursuit, and properly configured alerts will allow you to keep your finger on the pulse and provide a consistently high level of protection.
