Raw data arriving in PDF or text-based reports from clients and 3rd party systems can create confusion due to double-payments, cash or billing schemes, or other types of corporate fraud. Altair data preparation solutions can automate the extraction and transformation of data from these data formats and apply advanced fraud detection techniques such as Benford’s Law or the Gestalt tests. Easily generate and deploy business rules using Altair predictive analytics to trigger against probable fraudulent activities. Altair’s deep learning is very efficient at modeling complex relationships between inputs, outputs, and finding fraudulent patterns in large amounts of data.

Marketing teams are often challenged to predict how customers will respond to their campaigns. Several distinct and vastly different datasets are required to tailor a successful marketing campaign that may focus on product cross-sell and upsell or on new customer acquisition. Altair removes the complexity of developing a marketing analytics campaign by automating and repeating processes used in machine learning models designed to show the probability of success. Testing scenarios against changes in controllable and uncontrollable variables enables marketing campaigns to deploy a strategy that reaches the right audience, with the right message, using the right channel.