Software Solutions for Fraud Detection and Prevention

software solutions for fraud prevention




Fraud Prevention and Detection Options [FULL GUIDE]

The increase in fraud poses a threat to the whole world. The growing number of online services and channels makes it easier for legitimate customers and fraudsters to access products and services. One of the essential tasks of any organization is protecting against fraud-related losses. An intro effective cybersecurity strategy requires businesses to cover every possible area that could be exploited by attackers.

We suggest you read an article about the best software engineering practices and why do you need them.

So, fraud detection and prevention require adopting a comprehensive set of tools and solutions that will keep your infrastructure secure.



SAS Detection and Investigation

SAS has developed a comprehensive SAS Fraud and Security Intelligence (SAS FSI) solution that provides a unified platform for addressing transaction, credit, internal, and other fraud prevention challenges. SAS FSI is a high-performance cross-channel platform capable of processing thousands of transactions per second. It combines fine-tuning of business rules with machine learning technologies to prevent fraud with a minimal response rate.

The investigation interface allows you to reveal hidden relationships between payment participants and is also fully customizable to users’ needs. The block for working with machine learning models in the SAS system allows an ordinary user, without programming skills, to create a model and apply it to the transaction flow. The system includes built-in mechanisms for integration with online and offline data sources.

sas detection

ThreatMark: Anti-Fraud Suite

This solution is considered innovative, feature-rich, and easy to use fraud detection means, based on resonant behavior profiling, including behavioral biometrics, transaction, and threat detection components. The unique combination of the above features allows the software to detect any potential risks. In addition to detecting traditional threats such as client-side malware or fingerprint information, it also focuses on collecting and analyzing data about deep user behavior such as mouse movements and finger movements on the screen, patterns typing, and interaction with the application, unique for each user.

Combining evidence-based cyber threat detection (such as financial malware and phishing), this solution is ideal for monitoring transactions, users and devices, and transaction risk analysis, even meeting the requirements for multi-factor authentication. All collected information is evaluated using a powerful machine learning engine.



Riskified

Hackers and fraudsters have access to millions of valid personal financial information from previous data breaches, allowing them to easily manipulate a business’s e-commerce channels, costing merchants billions of dollars worldwide. Solutions like Riskified offer comprehensive online fraud prevention tools throughout the entire online transaction.

Riskified uses machine learning to analyze every transaction and only allows legitimate orders to be processed. It also provides a dynamic validation feature that automatically adjusts based on the customer’s risk profile, providing customers with various means to validate their purchases. For example, a customer with a higher risk profile could be asked to complete additional verification steps without rejecting transactions directly.



HoxHunt

The human factor continues to be the most considerable vulnerability in the company’s cybersecurity chain. It has been found that over 90 percent of security breaches are caused by human error. This is why cybercriminals still actively use social engineering attacks such as phishing to hack into infrastructure. Such attacks force users to abandon their credentials or install malware on their systems.

HoxHunt solves this problem by educating users on how to check if an email phishing or malicious. Companies can inform users using simulated phishing attacks. HoxHunt’s AI engine even personalizes these attacks to replicate what real-world attacks look like. Users can report these attacks through a dedicated plugin, and they receive immediate feedback on how well they are performing.

ARIC White Label

The company Featurespace was founded to develop an adaptive behavioral analytics engine that enables anomaly-based fraud protection. Featurespace’s ARIC White Label system belongs to the class of general analytical platforms. The system uses machine learning technologies to protect fraudulent transactions for various types of payments (cards, e-wallets, etc.) in real-time.

In ARIC White Label, models of normal customer behavior are created, deviations in which are subsequently recorded by the system. Different analysis rules can be made for various clients. They can also be given access to the ARIC White Label to set up their own rules and models for work.



IBM Safer Payments

IBM Safer Payments from IBM is a common analytics platform. It is developed on the IRIS platform following the IBM acquisition of IRIS Analytics. The system is designed to detect fraud attempts in real-time. At the same time, security is ensured when making non-cash payments in many systems (automated clearinghouses, acquiring banks, the Single Euro Payments Area, Chip & Pin, and others), and through merchant terminals, ATMs, online and mobile banks.

Experian

Experian’s National Fraud Prevention Scheme is a data exchange system for combating fraud. Powered by Experian Hunter’s high-tech fraud detection software, the service compares claim data with a shared fraudulent data bank in real-time. This uses data from a closed group of organizations belonging to a specific industry or different sectors within the same country.

National Fraud Prevention Scheme is provided as a server-side solution or easily integrates with internal claims processing systems. The service maximizes the value of the information and analytics available to all fraud prevention program members, protects the industry from repeated fraud attacks, and avoids contact with untrustworthy customers.

Thus, an effective cybersecurity strategy requires businesses to cover every possible area exploited by attackers. This requires the adoption of efficient software solutions that will keep your IT infrastructure secure and productive.

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