Dynamic Billing System Adapting to Credit Risk
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Solution Overview
Problem
Existing billing methods between clients and providers are inflexible and do not adapt to changing conditions, leading to inconvenient and risky transactions for both parties, as they typically remain static and do not account for shifting credit risks.
Innovation Solution
A computer-implemented method and system that dynamically adjusts billing experiences based on periodic or event-driven credit risk evaluations, allowing for transitions between prepay, partial prepay/postpay, threshold, and end-of-term billing models, optimizing resource availability and risk management for both clients and providers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a static billing method is used between client and provider, then the billing process is simple to implement, but it does not adapt to changing conditions and credit risks
Solution Approach 1:
The billing system transitions from a static model to a dynamic one by continuously monitoring client credit risk and automatically adjusting billing parameters. The system evaluates credit risk periodically and modifies billing experiences in real-time, allowing billing terms to adapt to changing conditions while maintaining manageable complexity through automated decision-making algorithms.
Solution Approach 2:
The system changes billing parameters such as credit limits, payment terms, and billing frequency based on evaluated credit risk. By dynamically adjusting these parameters rather than maintaining fixed billing terms, the system achieves adaptability to changing client conditions without requiring complete restructuring of the billing framework.
2Reliability
If prepayment billing is used, then provider risk is minimized, but client resource availability is reduced
Solution Approach 1:
The system applies different billing qualities to different clients based on their individual credit risk profiles. Rather than imposing uniform prepayment requirements on all clients, the system tailors billing terms locally to each client's risk level, providing more flexible credit terms to low-risk clients while maintaining stricter terms for higher-risk clients, thus balancing provider risk management with client resource availability.
Solution Approach 2:
The billing system incorporates continuous credit risk evaluation that provides feedback to dynamically adjust billing terms. This feedback mechanism allows the system to respond to changing client creditworthiness, adjusting the balance between provider risk protection and client resource availability based on current risk assessments rather than static prepayment requirements.
3Ease of operation
If postpayment billing is used, then client resource availability is improved, but provider risk increases
Solution Approach 1:
The system replaces static postpayment billing with a dynamic model that continuously monitors credit risk and adjusts billing terms accordingly. This allows the system to grant more favorable postpayment terms to low-risk clients while automatically tightening credit conditions for higher-risk clients, thus improving client resource availability without unduly increasing provider risk.
Solution Approach 2:
The system dynamically changes billing parameters such as credit limits and payment deadlines based on evaluated credit risk. By adjusting these parameters in response to credit assessments, the system enables postpayment billing to benefit low-risk clients while protecting providers from excessive risk exposure through automated parameter modification.
4Ease of operation
If billing methods remain static over time, then implementation is straightforward, but the billing experience becomes inconvenient for changing conditions
Solution Approach 1:
The billing system performs self-adjustment by automatically evaluating credit risk and modifying billing terms without requiring manual intervention from providers or clients. This self-service capability allows the system to adapt to changing conditions and maintain billing convenience while managing complexity through automated decision-making rather than manual process adjustments.
Solution Approach 2:
The system transitions from static billing terms to dynamic billing experiences that automatically adapt to changing client conditions and credit risks. This dynamic approach maintains billing convenience by continuously optimizing terms based on current risk assessments while managing system complexity through automated evaluation and adjustment mechanisms.
Data Source
AI summary
A computer-implemented method of providing advertising to a client includes establishing a billing experience between a client and a provider, providing advertising opportunities to the client on at least one of a continual basis and a periodic basis, evaluating a credit risk associated with the client at least one of periodically and upon occurrence of an event, and modifying the billing experience automatically based on the credit risk associated with the client.