Driver Recommendation System for Dynamic Insurance Pricing

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Solution Overview

Problem

The car rental and ride-sharing industries lack an efficient method to determine the best driver among a group of candidates and assign a car with discounted insurance rates, resulting in inefficient allocation and higher costs.

Innovation Solution

A method that builds a framework to evaluate driving candidates based on collected data, calculates a driving score, generates an aggregate ranking, computes vehicle rental and insurance costs, and recommends the highest-ranked candidate for optimal costs.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Adaptability or versatility

If traditional static insurance rates are used, then insurance coverage is provided, but costs remain high and flexibility is lost

Engineering Contradiction:

Improveinsurance rate flexibilityVSAvoidinsurance cost

Core Design Contradiction:

Adaptability or versatilityVSLoss of energy

Solution Approach 1:

The patent implements dynamic insurance pricing by continuously monitoring driver behavior data from mobile devices and adjusting insurance rates in real-time based on actual driving patterns, replacing static traditional pricing models with adaptive dynamic pricing that responds to changing driver behavior

Inventive Principle:

Principle #15Dynamics

Solution Approach 2:

The system changes the parameter of insurance rate calculation from fixed predetermined values to variable values based on multiple dynamic parameters including driving behavior metrics, location data, time of day, and risk assessments, enabling flexible cost adjustment

Inventive Principle:

Principle #35Parameter changes

2Productivity

If no efficient driver selection method is used, then car rental and ride-sharing services operate, but resource allocation is inefficient and costs increase

Engineering Contradiction:

Improvedriver allocation efficiencyVSAvoidoperational cost

Core Design Contradiction:

ProductivityVSLoss of energy

Solution Approach 1:

The system enables automatic driver evaluation and selection through algorithm-driven assessment of candidate drivers based on their behavioral data, eliminating the need for manual screening processes and enabling automated, efficient driver allocation to appropriate vehicles and routes

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The patent replaces manual driver evaluation mechanisms with automated computational systems that use machine learning algorithms and data analytics to assess driver candidates, substituting human judgment processes with efficient automated decision-making systems

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Data Source

PatentUS20240193697A1Intelligent best driver recommendation assistant for better rental and insurance rates

Publication Date: 2024.06.13 INTERNATIONAL BUSINESS MACHINE CORPORATION

AI summary

A computer-implemented method for recommending a best driver to get best vehicle rental and insurance costs. The method builds a framework of a group of multiple driving candidates to select from to be a driver of a rental vehicle. The method further determines a driving score based on the collected set of data and generates an aggregate ranking of each of the multiple driving candidates based on the driving score. The method further computes an insurance cost for each of the multiple driving candidates based on the driving score and calculates a vehicle rental and insurance cost for each of the multiple driving candidates, based on the driving score. The method further ranks each of the multiple driving candidates based on the respective calculated vehicle rental cost and insurance cost and recommends a highest ranked candidate as the best driver to receive the best vehicle rental and insurance costs.