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

Marketing teams are often challenged to predict how customers will respond to their campaigns. Several distinct and 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 success probability. 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.