Bossa Nova Data Solutions predictive analytics encompasses a variety of statistical techniques from data mining, predictive modelling, and machine learning, that analyze current and historical facts to make predictions about the future.
Our predictive models exploit patterns found in historical and transactional data to identify risks and opportunities. Our clients utilize our models to identify relationships among many factors and to assess the probability of a risk or an opportunity, guiding decision-making for optimizing limited capacity.
In predictive modeling, data is collected, a statistical model is formulated, predictions are made, and the model is validated, and possibly revised, as additional data becomes available. Predictive models analyze past performance to assess how likely a customer is to exhibit a specific behavior in the future.
Our models are customized to provide a predictive score (probability) for each individual according to the specific requirements and unique characteristics of each portfolio. Our clients utilize our scores to determine, inform, or influence organizational processes in marketing, credit risk assessment, fraud detection, manufacturing, and healthcare.
Step 1: Define the Model objectives an understand what we want to predict
Step 2: Data mining and manipulation
Step 3: Model development and validation
Step 4: Implementation, Measurement and Optimization
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