Loss Aversion Score Calculation for Personalized Financial Advice

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Solution Overview

Problem

Existing financial advising mechanisms lack a scientifically-based, quantitative approach to measuring individuals' risk tolerance, particularly their loss aversion, leading to generic recommendations rather than personalized advice.

Innovation Solution

A computer-implemented method and system that determines a loss aversion score by presenting users with gamble pairs, analyzing their selections, and calculating a loss aversion coefficient to provide personalized financial advice tailored to their unique risk tolerance.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If traditional financial advising mechanisms are used, then financial advice is provided to users, but the advice is generic and does not accurately reflect individual risk tolerance

Engineering Contradiction:

Improverisk tolerance measurementVSAvoidassessment system complexity

Core Design Contradiction:

Measurement precisionVSDevice complexity

Solution Approach 1:

The patent transforms the abstract concept of risk tolerance into measurable parameters through loss aversion coefficients. By presenting users with structured gamble scenarios and quantifying their responses mathematically, the system converts subjective risk preferences into objective numerical values that can be precisely measured and used for personalized financial advice.

Inventive Principle:

Principle #35Parameter changes

Solution Approach 2:

The patent replaces traditional subjective questionnaires and expert judgment with an automated computational system. The assessment platform uses algorithms to present gamble pairs, track user selections, calculate loss aversion coefficients, and generate personalized recommendations automatically, eliminating the need for manual financial advisor assessment.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

2Reliability

If personalized financial advice is provided, then accuracy of investment recommendations improves, but the complexity of determining individual loss aversion increases

Engineering Contradiction:

Improvefinancial advice accuracyVSAvoidloss aversion assessment complexity

Core Design Contradiction:

ReliabilityVSDevice complexity

Solution Approach 1:

The patent breaks down the complex task of assessing risk tolerance into segmented gamble pairs with specific parameters. Each gamble pair presents controlled scenarios with defined outcomes, allowing the system to isolate and measure different aspects of loss aversion systematically. This segmentation makes the overall assessment manageable and computationally tractable.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The patent introduces loss aversion coefficients as an intermediary mathematical construct between user preferences and financial recommendations. These coefficients serve as a bridge that translates subjective gamble choices into quantifiable metrics that can be directly applied to portfolio optimization and investment advice generation.

Inventive Principle:

Principle #24Intermediary (Mediator)

3Adaptability or versatility

If quantitative loss aversion assessment is implemented, then personalized financial recommendations are enabled, but the time and computational resources required increase

Engineering Contradiction:

Improvepersonalization capabilityVSAvoidassessment time

Core Design Contradiction:

Adaptability or versatilityVSLoss of time

Solution Approach 1:

The patent presents users with a limited set of carefully selected gamble pairs rather than exhaustively assessing all possible risk scenarios. This partial action approach provides sufficient information to calculate meaningful loss aversion coefficients without requiring excessive time or computational resources, achieving practical personalization with reasonable efficiency.

Inventive Principle:

Principle #16Partial or excessive action

Data Source

PatentUS10818134B2Systems and methods for providing customized financial advice using loss aversion assessments

Publication Date: 2020.10.27 DIGITAL NUDGING TECH LLC

AI summary

A system, method, and non-transitory computer readable medium having instructions for determining a loss aversion score for a user. A gamble table comprises a plurality of gamble pairs. Each gamble pair includes a loss aversion gamble and a gain seeking gamble. A loss aversion coefficient for each gamble pair is determined. The gamble pairs are displayed in random order and user selections are received. The user selections include, for each gamble pair, one of the loss aversion gamble and the gain seeking gamble. The gamble pairs are arranged in an ascending order or a descending order based on the loss aversion coefficients and a transition among the user selections is identified. The transition is used to determine the loss aversion score. The loss aversion score depends at least in part on the loss aversion coefficient of the gamble pair associated with the identified transition.