Complaint Prioritization Server Using Risk Indicia

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Solution Overview

Problem

Traditional complaint management methods fail to efficiently compile and prioritize internal and external complaints, leading to delayed or overlooked issues, improper handling, and inadequate protection of internal users from potential retaliation.

Innovation Solution

A risk prioritization server that receives and compiles internal and external complaints, identifying risk indicia such as response timing requirements, regulatory identifiers, and retaliation attributes to rank and prioritize complaints efficiently, ensuring proper administration and protection of internal users.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Productivity

If traditional complaint management methods are used, then complaint handling follows conventional processes, but complaints are delayed, overlooked, and improperly handled due to inefficiency

Engineering Contradiction:

Improvecomplaint handling efficiencyVSAvoidcomplaint response delay

Core Design Contradiction:

ProductivityVSLoss of time

Solution Approach 1:

The patent replaces manual complaint management processes with an automated computing system that uses machine learning models and algorithms to receive, analyze, prioritize, and route complaints. This substitution of mechanical/manual operations with automated computational processes directly improves productivity while reducing response delays.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The system enables self-service through automated complaint intake, analysis, and initial processing without requiring manual intervention at each stage. The computing device automatically receives complaints from multiple sources, analyzes them using trained models, prioritizes them based on risk assessment, and routes them to appropriate handlers, allowing the system to serve itself in the complaint management workflow.

Inventive Principle:

Principle #25Self-service

2Reliability

If traditional complaint management methods are used, then complaint processing follows standard procedures, but complaints with similar risks are overlooked and directed to improper parties

Engineering Contradiction:

Improvecomplaint routing accuracyVSAvoidrisk indication loss

Core Design Contradiction:

ReliabilityVSLoss of information

Solution Approach 1:

The patent replaces manual complaint assessment and routing decisions with automated machine learning models that analyze complaint data and identify risk indicia. This substitution ensures consistent, accurate risk assessment and proper routing based on objective analysis rather than subjective judgment, improving reliability while capturing all relevant risk information.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The system implements feedback loops where complaint outcomes and handling results are fed back into the machine learning models to continuously improve risk assessment accuracy. The models learn from historical complaint data and outcomes, refining their ability to identify risk indicia and route complaints appropriately, thereby improving reliability while preserving critical risk information.

Inventive Principle:

Principle #23Feedback

3Object-affected harmful factors

If traditional complaint management methods are used, then internal users are not specifically protected, but internal users face potential retaliation from their complaints

Engineering Contradiction:

Improveretaliation risk to internal usersVSAvoiduser protection reliability

Core Design Contradiction:

Object-affected harmful factorsVSReliability

Solution Approach 1:

The patent introduces an automated computing system as an intermediary between internal users and the complaint handling process. This intermediary anonymizes and processes complaints objectively, preventing direct identification and potential retaliation against internal users while ensuring their complaints are properly handled. The system mediates the interaction to protect user safety.

Inventive Principle:

Principle #24Intermediary (Mediator)

Solution Approach 2:

The system takes preliminary protective action by automatically detecting and flagging complaints from internal users before they enter the standard handling process. Special protocols are activated in advance to protect these complainants, including enhanced anonymity measures and direct routing to protected channels, preventing retaliation before it can occur.

Inventive Principle:

Principle #9Preliminary anti-action

Data Source

PatentUS11373128B1Apparatuses and methods for complaint prioritization

Publication Date: 2022.06.28 WELLS FARGO BANK NA

AI summary

A method, apparatus, and computer program product for complaint risk identification and prioritization are provided. An example method includes receiving, by a computing device, one or more internal complaints each associated with an internal user and one or more external complaints each associated with an external user. An internal user has access to one or more internal applications of the computing device while an external user lacks access to said internal applications. The method further includes determining, via risk evaluation circuitry, one or more risk indicia for each internal complaint and each external complaint. The method includes generating, via integration circuitry, a compiled complaint dataset of the one or more internal complaints and the one or more external complaints. The method may subsequently include ranking, by risk prioritization circuitry, the compiled complaint dataset based upon the risk indicia for each internal complaint and each external complaint.