Traditional scoring techniques can only cope with a limited number of data elements
Next generation solutions can handle significantly more data to assess suitability on a specific granular basis
Risk will decrease, and processes can be more efficient if avoiding using outdated analyses and constantly havethe right “data driven decisioning basis” and insights about the future in the desired area. When using our models and software, our analyses may improve themselves and make use of time-related changes in data to ensure and secure that the method and model is continuously updated and correct. This is what we call Machine Learning.
NEWS & INSIGHTS
Traditional Data Warehousing is being challenged by systems that doesn't build more than metadataindexes and that offers more flexibilty and lower costs. Read more
Recent years' development has given businesses and organizations the opportunity to gather more and more data. Should companies choose to utilize these data, investments in traditional and labor-intensive data warehouses have often been required. [...]