Document Summarization for Risk Factor Investigation Dashboards

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Solution Overview

Problem

Conventional AI-based risk management tools are limited in aiding investigators in finding desired information, assessing its reliability, and presenting risk factor information effectively for risk mitigation in enterprise transactions, leading to inefficiencies in detecting and identifying risk factors related to money laundering and other financial crimes.

Innovation Solution

A document summarization model employing machine learning predictive modeling and graphical user interfaces is used to generate topic-focused summaries, categorize risk factors, and visualize them, enhancing the detection and identification of risk factors through improved information retrieval and analysis.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Productivity

If conventional AI-based risk management tools are used, then basic risk factor identification is possible, but information retrieval efficiency and analysis accuracy are insufficient

Engineering Contradiction:

Improveinvestigation productivityVSAvoidinformation retrieval effectiveness

Core Design Contradiction:

ProductivityVSLoss of information

Solution Approach 1:

The system segments documents into sentences and sentences into phrases, creating a hierarchical structure that enables granular analysis. This segmentation allows the summarization model to process and identify risk factors at multiple levels of detail, improving both productivity and information retrieval effectiveness simultaneously.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The patent introduces an intermediary summarization model that acts as a bridge between raw documents and investigators. This model generates condensed summaries that preserve critical risk information while reducing document volume, thereby improving both investigation productivity and information retrieval effectiveness without direct loss of key details.

Inventive Principle:

Principle #24Intermediary (Mediator)

2Measurement precision

If comprehensive risk factor analysis is performed, then detection accuracy improves, but time consumption increases

Engineering Contradiction:

Improverisk factor detection accuracyVSAvoidinvestigation time

Core Design Contradiction:

Measurement precisionVSLoss of time

Solution Approach 1:

The system performs preliminary summarization and risk factor identification automatically before investigator review. By pre-processing documents to extract and highlight potential risk factors, the system maintains high detection accuracy while significantly reducing the time investigators need to spend on manual analysis.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The patent creates condensed copies (summaries) of original documents that retain essential risk information. These summaries serve as efficient proxies for full document review, enabling accurate risk factor detection with minimal time investment from investigators.

Inventive Principle:

Principle #26Copying

3Reliability

If detailed risk factor information is presented, then analysis completeness improves, but information presentation effectiveness deteriorates

Engineering Contradiction:

Improverisk assessment completenessVSAvoidinformation presentation effectiveness

Core Design Contradiction:

ReliabilityVSEase of operation

Solution Approach 1:

The system applies local quality by presenting different levels of information detail in different interface areas. Summaries provide condensed overviews for quick assessment, while underlying detailed information remains accessible for comprehensive analysis. This hierarchical presentation maintains both completeness and effectiveness simultaneously.

Inventive Principle:

Principle #3Local quality

Solution Approach 2:

The patent implements dynamic information presentation where the level of detail displayed adapts based on user interaction. The system can transition between condensed summary views and detailed analysis views, allowing investigators to access comprehensive information when needed while maintaining ease of operation through default condensed presentations.

Inventive Principle:

Principle #15Dynamics

Data Source

PatentUS12493646B2Systems and methods for risk factor predictive modeling with document summarization

Publication Date: 2025.12.09 BANK OF MONTREAL

AI summary

A system and method for document summarization generates summarized articles and risk factor categorizations for display at a graphical user interface (GUI) dashboard. A transaction monitoring system includes an adverse media dashboard pipeline for processing risk factor alerts and generating document summarizations for display at a user device. Document summarization extracts several sentences from a source text and stacks the sentences to create a summary. The method creates a vector representation of each sentence using a machine learning word embedding model and generates a sentence similarity matrix by computing cosine similarity values. A sentence graph creation algorithm creates a graph corresponding to the sentence similarity matrix and calculates importance scores used in selecting sentences for the document summary. The GUI dashboard includes first, second, third and fourth dashboard regions for displaying alert report records, media records, and graphical user interface layouts of document summaries and risk factor visualizations.