Fraud detection software identifies and alerts about risky online activities, like fraudulent transactions or access. It monitors user behavior to calculate risk and prevent illegitimate actions.
RBCH’s highly experienced fraud prevention software developers engineer custom-tailored solutions designed to detect & prevent fraudulent activities from occurring across entire business infrastructures while delivering a superior customer experience.
RBCH’s highly experienced developers program advanced fraud detection analytics for platforms with customized rule-based engines, machine learning, data analysis algorithms, and Continuous Controls Monitoring (CCM) technologies.
Protect your e-commerce business with end-to-end e-commerce fraud management solutions built with unique features for pattern recognition, data mining, real-time monitoring, and Knowledge Discovery in Databases (KDD).
Our custom fraud prevention solutions enables banks, processors, acquirers, and other financial networks to stay ahead of fraudsters, reducing fraud losses, improving detection rates, and preventing financial crime in real-time, at scale.
As a trusted software developer with experience in cutting-edge technologies, we can help you stay ahead of the curve in today’s rapidly evolving digital landscape. We leverage the power of AI to provide advanced fraud detection and mitigation
so that your business can operate with security and confidence.
With today’s interconnected world, at RBCH we understand how essential secure software development is. Our devoted team of software developers utilize AI-powered algorithms to make complex and strong solutions. By incorporating advanced fraud prevention strategies into our process, we’ll develop a shield for your business and safeguard you from potential threats through a solid foundation.
Being proactive against fraud is the best way to combat it. This is why RBCH offers innovative fraud prevention solutions
. By employing sophisticated algorithms through Artificial Intelligence
, our software will continuously analyze patterns, oddities, and other important data points to determine potentially fraudulent activity. Plus, with the capability to detect and tag suspicious activities or behaviors in real-time, you’ll be able to avoid financial losses and secure your reputation.
As a subset of AI, Machine Learning
is one of the fundamental tools to face fraudulent activity. Our expert engineers harness the versatility of machine learning algorithms to create a solution that can analyze large amounts of data, identify hidden patterns, and accurately detect the aforementioned fraudulent activity. This is done by the system continuously learning and adapting to the new patterns displayed and, over time, strengthens as a result.
With algorithms specifically crafted to locate intricate fraud schemes like account takeovers, identity theft, and simple transactional fraud, our developers can provide the solution for the insights you’re looking for. This is achieved through a combination of machine learning, data mining, and advanced statistical analysis. Consequently, enabling your company to take immediate action and prevent financial losses.
With RBCH’s expertise you can rest assured that your business will be guarded from malicious activities. The solution we’ll craft will allow you to detect and address fraud in real-time by providing actionable insights. This will give you peace of mind regardless of whether you are operating in finance
, retail
, or any other industry. With the ability to stop fraudulent activities in their tracks, you will be able to focus on core operations.
Prevent money laundering, tax evasion, forged bank checks, identity theft, cybersecurity threats, fraudulent insurance claims, terrorist financing, and other prevalent fraudulent activities that occur within organizations everywhere with RBCH’s custom fraud prevention software solutions.
RBCH’s team of highly experienced software developers has the required skills and resources to develop best-in-class fraud prevention software for desktop, web, and mobile devices, featuring key fraud prevention components including:
Anti-money laundering portal
Custom fraud parameters
Fraud data analysis programming
User access security management features
Payment transaction approval hierarchies
Risk assessment modules
Prevent internal fraud by eliminating hand-offs, unauthorized employee access, and other internal fraudulent activities with secure employee identity verification protocols and algorithms that monitor fraud signals detected in employee language & behaviors.
Protect your business from data breaches, account takeovers, remote access trojans, fraud bots, and other attacks by replacing your current one-time passcode-based account recovery systems with secure voice recognition/authentication.
Our fraud prevention software experts implement fraud data analytics modules that measure statistical parameter calculations (performance, quantiles, and averages), regression analysis, probability distributions & models, data matching, and time-series analysis.
We program a combination of technologies, including deep learning, natural language processing, robotic process automation (RPA), and computer vision/logo detection to identify fake domains, phishing & scam sites, cryptojacking sites, and other fraud sites in seconds.
Our custom payment fraud prevention solutions allow users to perform real-time payment fraud screening, apply real-time rules as part of a multi-layered fraud protection strategy, combat authorized push payment (APP) fraud, and so much more.
Whether your e-commerce storefront runs on Magento, Shopify, BigCommerce, WooCommerce, or ZenCart, RBCH will develop a custom fraud prevention solution and integrate it within your current e-commerce platform.
RBCH ensures that your custom fraud prevention solution is within full compliance of federal payment data security regulations, including PCI-DSS, HIPAA, GDPR, FISMA, FFIEC, CMMC, ISO-27001/ISO-27002, NERC, GLBA, NIST 800-171, NIST 800-53, SSAE 18, and all other federal and/or state-mandated consumer & payment data security regulations.
Our custom AI solutions
for fraud detection combines machine learning/deep learning, rule-based decision engines, artificial intelligence, and streaming analytics to detect fraudulent activity fast.
We leverage AI and machine learning models to improve the speed and accuracy of your fraud detection platform, enabling users to track accounts, logins, transactions, human visitors’ sessions, emails, and deposits (cash, checks, ACH, cards, etc.).
In order to effectively detect and validate control systems against fraudulent activities, we employ customized fraud data mining techniques designed to classify, cluster, and segment data, leveraging discoverable “meaningful” patterns that relate to fraud.
Our custom software solutions incorporate predictive analytics technologies, allowing you to instantly detect potential security threats and determine which claims may or may not qualify for approval using past data trends and variables.
We implement time series, bloom filters, and pattern recognition data structures within our custom-tailored enterprise fraud detection software solutions, allowing users to check transactions against known patterns and detect inconsistencies.
Using advanced AI & machine learning tools, we program robust chargeback management software designed to quickly identify anomalies based on a customer’s past behavior to help businesses prevent potential chargeback fraud and lost revenue.
RBCH jam-packs your custom fraud prevention solutions with powerful features that are guaranteed to catch fraudsters before they’re able to cause any serious damage, keeping your business systems safe and secured.
We’ll integrate industry-leading fraud prevention & detection software solutions with your current business workflows and processes to create an all-in-one, unified solution that allows you to boost your revenue by minimizing friction, fraud, and financial crime.
Simplify your fraud and risk management by integrating Redis with your existing workflows, defending against hundreds of fraud types through one unified system.
We seamlessly integrate Fraud.net with your current business processes to help you manage your entire fraud prevention program in a single software solution.
By integrating Forter with your current e-commerce platform, you can inspire more customer loyalty by eliminating false declines across all major touchpoints.
Our developers seamlessly integrate Riskified with your e-commerce storefront, enabling guaranteed chargebacks, policy protection, and account security.
We will seamlessly integrate Kount with your current business systems to prevent an account takeover, digital fraud, and protect the entire customer journey from start to finish.
Enhance your customer experiences, prevent fraud, and protect your enterprise business by integrating your internal business infrastructure with CyberSource.
Fraud detection software identifies and alerts about risky online activities, like fraudulent transactions or access. It monitors user behavior to calculate risk and prevent illegitimate actions.
The three common fraud schemes include identity theft leading to credit fraud, advance fee fraud, and cashier’s check fraud. Other notable types are tax refund fraud, fraudulent charities, credit card fraud, and financial account takeovers.
Data mining categorizes, clusters, and partitions data to comb through countless transactions in order to discover patterns and identify deception. Neural networks acquire knowledge of dubious patterns and utilize said patterns to further enhance their detection abilities. Machine learning automatically recognizes attributes present in fraudulent activities.
AI, including machine learning (ML), enables efficient analysis of large data volumes to detect patterns and anomalies indicative of fraud. AI-powered systems combat various fraud types like payment fraud, identity theft, and phishing attacks, offering robust prevention measures.
Explainable AI plays a crucial role in fraud detection by providing transparency and insight into the AI system’s decision-making process. It not only explains why a conversation is flagged as suspicious but can also proactively identify potential fraud by analyzing real-time conversations for behavioral patterns.
Fraud detection machine learning algorithms with logistic regression is a supervised learning method used for categorical decision-making. It determines whether a transaction is classified as ‘fraudulent’ or ‘non-fraudulent’.
Drop us a line or give us a ring with any inquiries on Fraud Prevention and Detection Software
, machine learning implementation, or any security concern. We love to hear from you and are happy to answer any questions.
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