Transaction Pattern Analysis for Proactive Reward Management

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Solution Overview

Problem

Financial institutions face challenges in providing personalized and timely rewards to customers experiencing life events, such as unemployment, as existing systems rely on passive customer notifications rather than analyzing transaction patterns to anticipate and address potential financial issues.

Innovation Solution

A method that analyzes transaction patterns to detect deviations, inferring life events and offering prescriptive rewards through a contextual metaphor approach, allowing financial institutions to proactively provide rewards that address anticipated consequences, such as modifying financial products or offering new products to mitigate adverse effects on other transaction types.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Device complexity

If financial institutions use passive customer notifications to award rewards, then system complexity is reduced, but responsiveness to customer life events deteriorates

Engineering Contradiction:

Improvesystem complexityVSAvoidresponsiveness to customer life events

Core Design Contradiction:

Device complexityVSLoss of time

Solution Approach 1:

The system performs preliminary analysis of transaction patterns to detect life events before customers need assistance. By continuously monitoring transaction data and identifying deviations from established patterns, the system proactively detects events such as unemployment, relocation, or health issues, enabling timely intervention and reward delivery without waiting for customer notifications.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system enables self-service by automatically detecting customer life events through transaction pattern analysis without requiring customer initiation. The computing system autonomously monitors transaction data, identifies deviations indicating life events, and triggers appropriate reward programs, eliminating the need for customers to actively notify the institution of their circumstances.

Inventive Principle:

Principle #25Self-service

2Adaptability or versatility

If financial institutions analyze transaction patterns to detect life events, then personalization of rewards is improved, but computational resources increase

Engineering Contradiction:

Improvepersonalization of rewardsVSAvoidcomputational resources

Core Design Contradiction:

Adaptability or versatilityVSUse of energy by moving object

Solution Approach 1:

The system applies local quality by focusing computational analysis on specific transaction patterns relevant to life event detection rather than processing all transaction data uniformly. The computing system identifies and monitors key transaction types (e.g., payroll deposits, rent payments, utility bills) that indicate particular life events, allocating computational resources efficiently to high-value analysis areas while reducing unnecessary processing.

Inventive Principle:

Principle #3Local quality

Solution Approach 2:

The system utilizes parameter changes by establishing baseline transaction patterns for each customer and detecting deviations from these parameters. By continuously comparing current transaction data against historical patterns and identifying significant deviations, the system efficiently detects life events without requiring exhaustive analysis of all transaction details, thus reducing computational overhead while maintaining high personalization accuracy.

Inventive Principle:

Principle #35Parameter changes

3Reliability

If financial institutions proactively offer prescriptive rewards based on transaction analysis, then customer relationship depth is improved, but system complexity increases

Engineering Contradiction:

Improvecustomer relationship depthVSAvoidsystem complexity

Core Design Contradiction:

ReliabilityVSDevice complexity

Solution Approach 1:

The system applies segmentation by dividing the complex task of life event detection and reward delivery into distinct functional modules: transaction data collection, pattern baseline establishment, deviation detection, life event classification, and reward program selection. This modular architecture manages system complexity by organizing functions into separate, manageable components that can operate independently yet coordinate effectively.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The system introduces an intermediary layer between transaction data and reward delivery, consisting of pattern analysis algorithms and life event detection logic. This intermediary processes raw transaction data, identifies meaningful patterns and deviations, and translates them into actionable insights that trigger appropriate reward programs, thereby managing system complexity while enabling sophisticated proactive customer engagement.

Inventive Principle:

Principle #24Intermediary (Mediator)

Data Source

PatentUS11995679B1Management of rewards using transaction listening

Publication Date: 2024.05.28 WELLS FARGO BANK NA

AI summary

Examples described herein relate to apparatus and methods for managing rewards for a customer of a financial institution, including but not limited to, determining a transaction pattern associated with transactions made by the customer, determining a deviation from the transaction pattern, determining an event associated with the customer based on the deviation, and determining rewards that correspond to the event for the customer.