ReadiSCORE “Self-Learning” Predictive Scoring System is designed for new generation BFSI applications that require self-learning predictive scoring, namely:
- “Predictive” Credit Scoring [for loan applications/loan origination etc]
- “Predictive” Risk Scoring [for risk management]
- Customer Behavior Profiling/Scoring for cross / up-sell etc
ReadiSCORE is also targeted for progressive institutions upgrading their traditional static scoring and rule engine based systems to incorporate new generation artificial intelligence techniques.
ReadiSCORE: Self-Learning Predictive Scoring System: Key Features
- Based on new generation artificial intelligence techniques.
- ReadiSCORE generates predictive scoring model by automatically learning from combination of historical contextual data and expert domain knowledge inputs specified by business analysts. This model is then applied to current/new evidence to generate unique score in real-time that predicts or indicates probability of the future outcome. Basically, it determines the score that is predictive of the likelihood of the scenario/outcome happening. (e.g.risk, opportunity, profiling, defaulting in repayment etc).
- Requires smaller set of historical information to learn from and gives higher degree of accuracy in prediction.
- Self-learns continuously in real-time reflecting latest enterprise knowledge and to further improve the accuracy of suggested outcomes.
- Learning is fast and finite unlike neural network based scoring systems.
- Provides intuitive and business analyst friendly visual modeling workbench to configure, manage and deploy application specific scoring models, its parameters of interest and the relationships between them.
- Resolution Rule Engine is used to respond as per the predictive score; thereby increasing the effectiveness of decision making across the enterprise.
To see how you can use ReadiSCORE, please visit