Electronic Communications Data Mining for Brokerage Relationship Analysis

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Solution Overview

Problem

Large brokerage companies face challenges in identifying and analyzing relevant information from vast electronic communications data to effectively prospect and maintain relationships with clients and partners, due to the sheer volume and complexity of the data.

Innovation Solution

The implementation of a system that preprocesses and filters electronic communications data by converting it into a consistent format, removing redundant information, and applying machine learning models to identify business-related content, thereby extracting useful metrics and relationship analyses.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Loss of information

If electronic communications data is collected and stored for analysis, then relationship insights and marketing intelligence can be obtained, but data volume and storage complexity increase significantly

Engineering Contradiction:

Improverelationship insightsVSAvoiddata volume

Core Design Contradiction:

Loss of informationVSQuantity of substance

Solution Approach 1:

The system extracts only the essential and relevant information from electronic communications data, such as communication frequency, relationship strength indicators, and key interaction patterns. This extraction process separates valuable relationship insights from the overwhelming volume of raw communication data, allowing the system to maintain comprehensive analysis capabilities while managing data volume efficiently.

Inventive Principle:

Principle #2Taking out (Extraction)

Solution Approach 2:

The patent segments the large volume of electronic communications data into manageable units organized by communication pairs, time periods, and relationship types. This segmentation allows the system to process and analyze relationships in discrete, organized chunks rather than attempting to handle all data simultaneously, reducing storage complexity while preserving relationship insights.

Inventive Principle:

Principle #1Segmentation

2Measurement precision

If all electronic communications data is analyzed, then comprehensive relationship insights are obtained, but processing time and computational resources increase

Engineering Contradiction:

Improverelationship analysis accuracyVSAvoidprocessing time

Core Design Contradiction:

Measurement precisionVSLoss of time

Solution Approach 1:

The system applies partial action by focusing analysis on the most significant communication patterns and relationships rather than processing every single communication event with equal depth. It identifies and prioritizes key communication pairs and interaction types that provide the most valuable relationship insights, thereby reducing processing time while maintaining analysis accuracy for the most important relationships.

Inventive Principle:

Principle #16Partial or excessive action

Solution Approach 2:

The patent implements preliminary filtering and preprocessing of electronic communications data before full analysis. This includes initial sorting by communication frequency, identification of key communication pairs, and pre-categorization by relationship type. These preliminary actions prepare the data in advance, enabling faster and more efficient subsequent analysis while preserving comprehensive relationship insights.

Inventive Principle:

Principle #10Preliminary action

3Productivity

If data filtering and preprocessing are applied, then analysis efficiency improves, but risk of losing relevant information increases

Engineering Contradiction:

Improveanalysis efficiencyVSAvoidrelevant communication data

Core Design Contradiction:

ProductivityVSLoss of information

Solution Approach 1:

The system incorporates feedback mechanisms in its filtering and preprocessing operations. It continuously monitors analysis results and adjusts filtering criteria based on the importance and relevance of identified communication patterns. This feedback loop ensures that filtering operations remove only truly redundant data while preserving relevant communication information, thereby improving analysis efficiency without losing important relationship insights.

Inventive Principle:

Principle #23Feedback

Solution Approach 2:

The patent dynamically adjusts filtering parameters and thresholds based on the specific analysis context and relationship importance. Rather than applying fixed filtering rules, the system modifies parameters such as communication frequency thresholds and relationship strength criteria to optimize both filtering efficiency and information retention. This adaptive parameter adjustment ensures relevant communication data is preserved while maintaining high analysis efficiency.

Inventive Principle:

Principle #35Parameter changes

Data Source

PatentUS10769159B2Systems and methods for data mining of historic electronic communication exchanges to identify relationships, patterns, and correlations to deal outcomes

Publication Date: 2020.09.08 AON GLOBAL OPERATIONS LTD (SINGAPORE BRANCH)

AI summary

In an illustrative embodiment, systems and methods for generating data metrics and relationship analysis from an organization's electronic communications archives include pre-processing the electronic communications into a consistent, workable format, including filtering the data to remove irrelevant messages. Machine learning models may be applied to support automatic identification of relevant message content for data analytics. The systems and methods may link the electronic communications with transaction records of a transactional platform and analyze the communications traffic in view of transactional patterns and outcomes. Communications between parties may be analyzed to identify timings and patterns, plus correlations between electronic communication patterns and business outcomes.