Solutions by Use Cases
Fraud detection is becoming much more difficult in the technological age with a growing inability to distinguish suspect transactions or behaviour. Whether it be anti-money laundering or fraudulent transactions, it is of little comfort to find out after the fact! Ulysses by contrast monitors all data relevant to transactions, accounts, people, organisations, and a multitude of other entities and attributes, such that early capture and corrective action is enabled. Surprisingly low volumes of historical data relating to fraudulent transactions can provide profound insights when transformed and presented in Ulysses.
This then sets a benchmark against which data points reflecting potential fraud can be assessed. Aspects such as size of transaction compared to average; length of customer relationship; legal entity structure; country of incorporation; nature of transaction eg cash, whether in person or digitally; and many more, can be easily configured in Ulysses. The processing, linking, and rating of all these data aspects is then done continually and holistically by Ulysses to provide clear insight on the likelihood of any interaction being fraudulent.
Whether you are addressing customer enquiries, filling orders, processing Ministerial/Parliamentary questions, or merely searching for information, Ulysses pulls all the information together and presents it in actionable form with an emphasis on relevance.
The marketing managers dream is to be able to target products, services, and campaigns directly to the interests of every single customer and prospect. Whilst that may be unrealistic, Ulysses can provide the information that facilitates personalised marketing to key target groups. Using the “show similar” function provides confidence that actions taken will lead to the desired customer behaviour. By highlighting the drivers behind behaviour Ulysses predicts with a high degree of accuracy when compared to the probability theory methods underlying predictive analytics.
Every organisation would like the ability to be able to predict the future. In fact, it is now common for organisations of any substance to engage data analysts and data scientists to make sense of their big data. Those data scientists use complex algorithms in an attempt to predict where advantage may be gained or hurdles may be avoided. With Ulysses however, our semantic processing engine removes the need for data scientists by linking data points in a related manner highlighting the reasoning behind the connection.
Ulysses goes way beyond mere historical statistical analytics reporting so that business users can then make better business decisions with a high degree of confidence.