🛑STOP building and deploying predictive and machine learning #ml models in isolation.
Predictive and Machine Learning models are generally built with carefully selected training data and will be deployed as part of #CreditScore #RiskManagement #CustomerSegmentation #Chrun prediction in industries such as #banking #finance #insurance in various processes and use cases. These models provide scores and probability in various situations based on the inputs.
🤔How should organizations act on them?
🌌There is a space between input, scores, probability, and what should be done. That's the “Decision Space”. #decisioncentric
🎳The best approach is to use the Decision-Centric Approach® in #banking #insurance #financialservices to make the actions prescriptive based on the situation using a decision model:
1️⃣ Create the decision model by decomposing a decision (e.g., credit score, fraud, churn, etc.) into smaller and more understandable decision units
2️⃣ Integrate the predictive and machine learning models in one (or more) of the decision units
3️⃣ Create your #businessrules for the other decision units to specify custom ratings, policies, and procedures
4️⃣ Use regulatory and compliance #businessrules and specify the guard rails on the relevant decision units
✨Now, you have a holistic model for business decisions that integrates the predictive model #pmml or your machine learning models #machinelearning and #businessrules. This model now prescribes actions based on all required decisions involved rather than on an individual score and probability value. This holistic and hierarchical decision model representing a business decision can create the outcomes or recommendations for the next best actions based on aggregated results of the predictive model machine learning and business rules.
💣The benefit of this approach using #decisionintelligence is to allow you to:
* Consistently prescribe across decision-making scenarios how the scores and probabilities influence the outcome
* Overcome the challenges of gray areas of decision-making based on organization risk appetite and internal policies
* Integrate regulatory, compliance, and policy rules in the decisions model along with scores and probability
🚀Integrated approach in predictive models, machine learning models, and business rules will enable #banking #insurance and #financialservices organizations to consistently make Quick ACT™ decisions – Quick, Accurate, Consistent, and Transparent outcomes for their precious business decisions.
Posted here.
Published August 28th, 2024 at 07:30 am
