We build predictive behavioral and application scorecards to estimate propensity for:
Deploy scorecards in real time to drive informed decisions for origination, pricing and marketing recommendations throughout the customer journey.
Financial lenders now use advanced customer data enhancement to reduce lending risk. Using statistical and machine learning techniques, we analyze data and reduce it to a single value known as a credit score – which represents the lending risk for an individual.
Credit scoring is a form of artificial intelligence (AI) based on predictive modeling that assesses how likely a customer is to default on a credit obligation or become delinquent or insolvent; a high credit score indicates high creditworthiness. Once we’ve built a predictive model, the model “learns” from key inputs such as customer historical data alongside other data to predict the probability of that customer displaying a defined future behavior.
We design models for scorecards that describe propensity for pre-defined desirable or undesirable behaviors based on risk within an existing customer base. For example, a behavioral score on default propensity informs decisions related to account management such as credit limit, over-limit management, new products, and more.