Data Interpretation Analysis for Financial Risk Assessment

Resolve Bottlenecks,
Find Innovative SolutionsGenerate Solutions

Solution Overview

Problem

Underwriters' decisions in financial risk assessment are often justified in unstructured comments, making it difficult to evaluate the quality and accuracy of these decisions, which is problematic for quality assurance purposes.

Innovation Solution

A data interpretation analysis system that processes unstructured comments to identify attributes, perform sentiment analysis, and compare attribute values and sentiments with structured data to determine the accuracy and completeness of the interpretation, generating a quality score.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Ease of operation

If underwriters use unstructured comments to justify decisions, then flexibility and ease of operation are improved, but measurement precision and reliability of decision quality evaluation deteriorate

Engineering Contradiction:

Improveease of decision justificationVSAvoidprecision of decision quality evaluation

Core Design Contradiction:

Ease of operationVSMeasurement precision

Solution Approach 1:

The patent introduces an intermediary processing system that translates unstructured underwriter comments into structured, analyzable data. Natural language processing algorithms act as mediators between the free-form text input and the structured evaluation framework, extracting key attributes, sentiments, and decision rationale while preserving the flexibility of unstructured input.

Inventive Principle:

Principle #24Intermediary (Mediator)

Solution Approach 2:

The system transforms unstructured text parameters into structured parameters through automated attribute identification and sentiment analysis. By changing the state of the data from unstructured to structured with defined parameters (attributes, sentiments, confidence scores), the system enables precise measurement while maintaining the original flexibility of comment-based justification.

Inventive Principle:

Principle #35Parameter changes

2Adaptability or versatility

If unstructured comments are used for decision justification, then adaptability is improved, but difficulty of detecting and measuring decision quality increases

Engineering Contradiction:

Improveadaptability of decision documentationVSAvoiddifficulty of evaluating interpretation quality

Core Design Contradiction:

Adaptability or versatilityVSDifficulty of detecting and measuring

Solution Approach 1:

The system performs preliminary processing of unstructured comments by automatically identifying attributes, determining sentiments, and extracting key information before formal evaluation occurs. This preliminary structuring action makes subsequent detection and measurement of decision quality significantly easier while preserving adaptability in the original comment format.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The patent replaces manual mechanical review processes with automated computational systems. Natural language processing algorithms, sentiment analysis engines, and machine learning models substitute for manual reading and evaluation of unstructured comments, dramatically reducing the difficulty of detecting and measuring decision quality while maintaining adaptability.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

3Productivity

If automated processing of unstructured data is implemented, then productivity is improved, but device complexity increases

Engineering Contradiction:

Improvespeed of decision quality evaluationVSAvoidcomplexity of analysis system

Core Design Contradiction:

ProductivityVSDevice complexity

Solution Approach 1:

The complex analysis system is segmented into distinct functional modules: natural language processing component, attribute identification module, sentiment analysis engine, accuracy verification component, and scoring system. Each module handles a specific aspect of the analysis, making the overall complex system manageable and maintainable while achieving high productivity through parallel processing.

Inventive Principle:

Principle #1Segmentation

Data Source

PatentUS12299076B1Data interpretation analysis

Publication Date: 2025.05.13 WELLS FARGO BANK NA

AI summary

Quality associated with an interpretation of data captured as unstructured data can be determined. Attributes can be identified within the unstructured data automatically. Subsequently, sentiment associated with each of the attributes can be determined based on the unstructured data. Correctness of the unstructured data, and thus the interpretation, can be assessed based on a comparison of the attribute and associated sentiment with structured data. A quality score can be generated that captures the quality of the data interpretation in terms of correctness and as well as results of another analysis including completeness, among others. Comparison of the quality score to a threshold can dictate whether or not the interpretation is subject to further review.