Ajay Ramchandran, Senior Director, Oracle Revenue Management and Billing
Broad-scale adoption of AI technologies could rapidly change how financial services organizations think about their revenue management and billing processes.
The opportunities to apply these emerging technologies are seemingly endless. There are, however, a few areas that are especially ready to yield immediate and lasting results. The first is bill readiness.With an ever-growing universe of billing scenarios, the fundamental challenge of billing accuracy persists. Many organizations continue to rely on manual error checks and reports for anomaly detection. These methods make it difficult to rapidly identify the root cause of an anomaly and are time and resource-intensive, raising operational overhead. In many cases, an anomaly is detected after a bill has been generated, resulting in billing disputes that are a leading cause of customer churn.
An ML model can help financial services organizations flip the narrative by proactively identifying anomalous patterns in billing. And, the model continuously learns over the time to drive more accurate billing moving forward. It also automates the process of detecting anomalies and notifying users and can hold billing for accounts where anomalies are detected without delaying billing for other accounts. AI can also accelerate root cause analysis, reducing investigation time and costs, and driving faster resolution.
Consider this example: A customer with a monthly billing cycle has a transaction volume variance that fluctuates 5 percent month over month, with a predictable spike in the holiday season. However, this year, the bank observed a sudden surge in the customer transaction volume in January. An AI-enabled solution could flag the invoice anomaly based on previous transaction history, identify the root cause, learn from this anomaly, and others to reduce false positives, as well as rapidly detect actual errors in the future.
Financial institutions can also leverage AI-enabled revenue management and billing systems to identify opportunities to grow relationships and their business. For example, models could detect behavior and transaction patterns that reveal upsell opportunities or the potential to reward a loyal customer with a better rate or increased line of credit. These same technologies enable deeper analysis that can accelerate the resolution of adverse events, such as consistently late payments or insufficient funds. If, for instance, the root cause for a customer’s intermittent late payments is volume spikes at certain times of the year, the ability to suggest a normalized billing plan could be an option to ensure timely payments and build stronger customer relationships.
Oracle understands the power of AI, and other emerging technologies to bring new levels of intelligence and efficiency to revenue management and billing operations while reducing risk. And we’ve built it into Oracle Revenue Management and Billing. Advanced capabilities help organizations to optimize deal pricing, identify billing anomalies and rapidly find their root cause, empower teams to identify ways to build stronger and more profitable customer relationships, and more. The possibilities are endless.