Explainable AI Financial Decisioning via Neural Weightage
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Solution Overview
Problem
Conventional artificial intelligence systems used in financial transactions, such as underwriting and insurance claims, lack explainability, failing to provide clear reasoning behind decisions and are prone to internal biases, making it difficult to track and validate the impact of neural network nodes on final decisions.
Innovation Solution
An explainable artificial intelligence based decisioning management system that includes a neural network explainable module to reverse calculate importance weightage distribution across neural nodes, generating a case assessment report with explainable reasons for decisions, and allowing for real-time feedback and self-retraining to mitigate biases.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If neural networks based on artificial intelligence are used for decision-making, then decision accuracy is improved, but explainability deteriorates
Solution Approach 1:
The patent introduces an intermediary module that acts as a bridge between the neural network and the decision output. This intermediary captures and processes the reasoning path, node activations, and feature importances, transforming the opaque neural network output into explainable decisions without affecting the original decision accuracy
Solution Approach 2:
The decision-making process is segmented into distinct components: the neural network for decision accuracy, and a separate explanation generation module for interpretability. This segmentation allows each component to optimize for its specific function while working together as an integrated system
2Productivity
If conventional AI systems are used, then processing speed is improved, but reliability deteriorates due to internal biases
Solution Approach 1:
The patent implements feedback mechanisms where the explanation generation module provides information about node importances and reasoning paths back to the system. This feedback enables bias detection and validation, allowing the system to identify and correct unreliable decisions while maintaining processing speed through automated monitoring
Solution Approach 2:
The system performs preliminary validation of neural network decisions by generating explanations and checking for biases before finalizing decisions. This preliminary action ensures reliability is maintained without significantly impacting processing speed, as the validation occurs in parallel or as a quick post-processing step
3Reliability
If multiple cognitive and logical steps are implemented, then decision reliability is improved, but device complexity increases
Solution Approach 1:
The patent merges multiple cognitive and logical steps into an integrated explanation generation framework. Instead of separate modules for each validation step, the system combines feature importance calculation, node activation analysis, and reasoning path generation into a unified process that improves reliability without proportionally increasing complexity
Data Source
AI summary
An explainable artificial intelligence based decisioning management method and system for processing financial transaction is disclosed. The method includes receiving a request for performing a financial transaction from applicant and from data sources. The method further includes performing a data sufficiency check using one or more neural network on the request by validating the request of the applicant with one or more external data sources. Further, the method includes generating a decision for the received request using neural network model if the data sufficiency check is successful. Additionally, the method includes validating the decision by reverse calculating, through the neural layers of the neural network model, an importance weightage distribution across each of the neural nodes. Also, the method includes generating a case assessment report for the generated decision based on the validation. Furthermore, the method includes performing the financial transaction with the applicant in response to the received request based on the generated case assessment report.