Fraud detection that intelligently assesses the risks and adapts accordingly using good judgement throughout the process. Empowers your entire organisation in actively fighting fraud on all fronts. Provides a safer cyber environment, allowing your employees to work with more confidence.
Assesses the likelihood and impact of the content of any messages or emails received and provides a simple fraud risk score (0-250) to help employees to be able to act decisively. Simplifies the entire process as opposed to more complicated analysis that might confuse employees.
Provides the facility to quickly identify and scan any suspicious text messages/emails that might seem to even be originating from someone within your organisation or a trusted customer. SenseText as an extra layer of security helps to detect any potential risks and advises on the best course of action.
Going beyond just detection and promoting a proactive approach fraud prevention strategy by creating lists of action points and providing employees with input when fraud is suspected. When there seems to be something wrong, SenseText is not content with just leaving the matter completely in the hands of the employee but provides additional assistance by indicating what the employee should do next.
Dives deep into any data provided, analysing thousands of data points along the way when running fraud detection algorithms. Compares data points to provide a unique insight and accurately predicts the likelihood of fraud.
Fraud detection that keeps getting better with time. The model learns, unlearns, adjusts and adapts rules of fraud detection based on feedback and operational experience. SenseText actively uses a combination of supervised and unsupervised learning when detecting fraud.
Uses natural language processing technology to analyse and understand the contents of messages. Product architecture based on Platform 2 which enables a deeper
understanding of the parts of speech used in the potentially fraudulent text. As the type of nouns, verbs and adjectives used may likely indicate the likelihood of fraud.
Takes advantage of our database which can sufficiently detect numerous types of fraud and allows the end-user to push the boundaries of fraud detection by building their own database using the custom model. The pairing of a custom database with our database significantly plugs any gaps in the detection grid.
Automated fraud threshold which when enabled applies the principles of risk appetite lowering or increasing the fraud detection threshold accordingly. Uses statistics to decide when to be more cautious and when to be more risk-averse. In the future, after learning from the end-user SenseText will provide the full ability to be more risk-averse when an important transaction is coming up, during a company takeover or when a breach is predicted.
To clearly present the results of occasionally complex fraud data, SenseText uses fraud graphs that can be further manipulated and easy to understand gauges to present data in a clear, easy-to-understand manner. Data can be further sorted, filtered and edited.