Information reduces uncertainty and accurate, timely information on suppliers and customers serves to reduce the uncertainty associated with many business activities.
RAGEframeworks has built web based services which employ advanced semantic intelligence to trawl through over a million articles a day and deliver risk profiles on both customers and suppliers.
Businesses need to ensure that suppliers can meet their obligations and that customers can pay their bills. What was true a month ago may not be true today, and so the assimilation of a diverse set of near real-time data is the only way of making sure that risk assessments are fair and timely. To this end RAGEframeworks utilizes both structured and unstructured data in its risk analysis. Structured sources include financial data, credit rating scores, information from credit bureaus and broader industry information. This provides a quantitative assessment of risk, whereas information from unstructured sources such as Bloomberg, newspapers (both national and regional), and various data aggregators allow a qualitative risk assessment. Big data technologies are employed to handle the large volumes of highly diverse data.
The traditional market for this information has been wealth management and loan origination with numerous well known banks and credit providers using the service. However businesses in technology and manufacturing have also seen the value of supplier and credit risk information. In fact the management team behind RAGEframeworks has decades of experience in this industry and in the analytics sciences that make the service feasible.
The linguistic engine behind RAGEframeworks employs a ‘theme’ based approach and this generates an ontology for every business subject to risk analysis. The company claims greater than 90% accuracy in its risk assessments and often provides leading indicators of company performance.