During a financial transaction such as invoicing, operational stakeholders expect accuracy and compliance per regulatory requirements. However, due to business process/policy inconsistencies, ever-changing customer requirements, underlying data challenges, and manual steps, companies run into invoicing inaccuracies and noncompliance challenges—affecting the customer and partner experience, potentially resulting in revenue loss.

Leveraging GenAI during invoice processing can help flag any potential anomalies and find discrepancies in the invoice by performing a multifaceted search based on a preselected set of criteria. Automating invoice validation through GenAI can also help check adherence to regulatory, tax, and other compliance-related requirements, flagging potential errors earlier in the billing process. It can also help generate a detailed summary of the errors or discrepancies along with recommended solutions.

Potential benefits include:

Operational efficiencies

• Reduced revenue leakage and more accurate financial reporting
• Expedited billing cycles, faster payments, and improved invoice accuracy
• Reduced risk of fraudulent activities and streamlined quote-to-invoice process

Elevated customer experience

• Increased accuracy of invoices, resulting in improved customer experience
• More timely delivery of invoices, leading to higher customer retention rates and improved customer satisfaction

Improved employee experience

• Automated identification and resolution of invoice-related issues
• Reduced time spent by customer success agents in applying credits due to invoicing inaccuracies

The ease of doing business between companies and customers is enabled not only based on business process and system capabilities but also based on customer-facing documents such as quotes, invoices, and notification emails. Customers and partners have different preferences and tend to request companies to generate tailored invoice documents. This increases operational overhead for the companies, and not generating invoices per customer preference can negatively affect experience.

GenAI can help create multi-format and multi-language invoices centered on customers’ preferences. By using a repository of invoice templates with defined standards for displaying billing details, GenAI can help customers tailor their invoice layout or roll up billing based on their specifications such as account hierarchy, geography, billing entity, business units, etc.

Potential benefits include:

Revenue growth

• Automated invoices improve cash flow through faster payments

Operational efficiencies

• Reduced operational overhead for additional invoice details requested by the customer

Elevated customer experience

• Tailored invoices based on customer preferences such as geography, customer account hierarchy, and billing entity

Improved employee experience

• Reduced manual effort in validating the invoice against the original transaction

One of the biggest pain points in revenue recognition processes is revenue loss. There are multiple factors that can contribute to revenue leakage, including incorrect data entry in upstream processes, poor data governance, and non-standardized business processes/policies. Revenue can also be impacted due to missed cross-sell and up-sell opportunities and customer churn.

GenAI can help address revenue loss by identifying areas of leakage in upstream processes (such as quoting, contracting, order management, and renewals) and proactively correcting data that could have caused the leakage. For example, GenAI can be leveraged to identify standard and non-standard terms across the customer contract and identify performance obligations. This, in turn, will help identify how and when revenue recognition occurs and any potential points of revenue leakage.

Potential benefits include:

Revenue growth

• Tap into more sales opportunities that could have been missed due to operational inefficiencies

Cost savings

• Accelerated and efficient identification of changes in end-to-end contract or financial terms
• Reduced operational overhead through identification of revenue leakage
• More accurate and timely revenue recognition

Improved employee experience

• Improved decision-making through visibility into the status of the deal, pipeline, and forecasts
• Reduced time and effort spent on identification of source of revenue leakage

Inconsistent or latent processes, coupled with deficient technology to aggregate and analyze data, result in inaccurate revenue forecasting for not only flat subscription but also consumption-based business models. This is often caused by poor data quality, fragmented data sources, and the inability to account for rapid market changes. Inaccurate revenue forecasting analysis can further lead to missed sales opportunities and suboptimal utilization of budget and resources.

Technology companies can leverage machine learning and AI to incorporate continuous data feeds of financial, operational, and third-party data for real-time variance analysis and driver analytics. GenAI-powered predictive models can review large sets of data in real time to identify primary drivers that can be influenced. GenAI chatbots can also be leveraged to create customizable insights and on-demand analytical models by product line, business, or customer segment. These data-fueled insights, combined with a conversational and visual interface, can help leaders make strategic decisions in real time with confidence and significantly improve financial forecasting.

Potential benefits include:

Revenue growth

• Accelerated business driver identification, transparency, and scenario modeling
• Reduced time to insights and decisions with the support of interactive and visual financials

Operational efficiencies

• More accurate revenue forecasting and improved risk mitigation
• Optimization of resources through better budget allocation

Improved employee experience

• Reduced time spent by employees on forecasting activities
• Greater transparency into drivers, assumptions, and strategic decisions that enable business leaders to drive earnings and reduce cost