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ReadiScore:Self Learning Predictive Scoring System

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 targetted 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.

Solutions

To see how you can use ReadiScore, please visit “Solutions” page.