Receivables Management System Using Account Tying and Scoring
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Solution Overview
Problem
The receivables management industry faces challenges in implementing and managing tailored debt collection strategies across various industries and debtors, as existing methods are costly, difficult to manage, and lack effective monitoring and updating of debtor information, leading to inactive accounts and failed collection processes.
Innovation Solution
A method and system for managing receivables that involves matching and tying accounts based on debtor information, calculating scores for collection strategies, and applying optimized strategies based on financial parameters, with optional account tying and conditional adjustments to ensure compliance with client contractual obligations and maximize returns.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If multiple tailored collection strategies are implemented for different types of debts, then collection effectiveness is improved, but implementation cost and management complexity increase
Solution Approach 1:
The patent segments the debt collection process by creating distinct collection strategies for different debt types (e.g., consumer debt, commercial debt, medical debt). Each strategy is customized with specific parameters such as contact frequency, communication channels, and escalation procedures tailored to the characteristics of each debt category, thereby improving collection effectiveness while maintaining manageable complexity through structured segmentation.
Solution Approach 2:
The system implements dynamic strategy adjustment capabilities that allow collection strategies to be modified in real-time based on performance metrics and changing debtor circumstances. This dynamic approach enables the system to adapt tailored strategies without requiring complete redesign, thus maintaining effectiveness while reducing long-term management complexity.
2Productivity
If collection strategies are customized for different debtors, then returns on collection efforts are maximized, but implementation cost increases
Solution Approach 1:
The patent applies local quality by customizing collection strategies at the individual debtor level rather than applying uniform approaches. Each debtor receives a tailored strategy based on their specific characteristics such as debt amount, payment history, and contact preferences. This localized customization maximizes returns by matching the right approach to each debtor while the system manages complexity through automated profiling and strategy selection.
3Reliability
If debtor information is continuously updated and monitored, then collection success rate improves, but data management complexity increases
Solution Approach 1:
The system implements comprehensive feedback mechanisms that continuously monitor debtor information including contact updates, payment behavior changes, and communication response patterns. This feedback loop enables real-time adjustments to collection strategies based on current debtor status, improving success rates while the automated feedback collection and analysis processes manage data complexity systematically.
Solution Approach 2:
The patent employs preliminary actions by proactively updating and validating debtor information before collection activities begin. The system performs advance data verification, contact information validation, and debtor profile completion to ensure accurate information is available beforehand, thereby improving collection success while reducing the need for complex ongoing data management during active collection processes.
4Productivity
If account party data is monitored and updated, then collection effectiveness improves, but system complexity increases
Solution Approach 1:
The system implements self-service capabilities that enable automatic monitoring and updating of account party data through integrated data sources and automated verification processes. The system autonomously tracks changes in debtor information, validates updates against multiple sources, and maintains current data without requiring complex manual intervention, thereby improving collection effectiveness while managing system complexity through automation.
Data Source
AI summary
A method, system, and computer-readable medium for managing and collecting receivables are disclosed. Such a method includes providing at least one pre-existing account with first account information, the first account information having first account party data and providing at least one new account, each new account comprising new account information, the new account information having new account party data. The method also includes determining whether the first account party data of the pre-existing account matches the new account party data of the at least one new account and if so, tying the at least one new account with the matching pre-existing account to create a tied account. The method further includes calculating a score for any unmatched new account and any tied account based on at least one financial parameter and applying one or more collection strategies.