Accelerating Financial Services Reporting with AI Chat Assistants
Financial controllers and finance directors in the financial services sector frequently face a reporting bottleneck. Generating custom transaction reports, income statements, or balance sheets across multiple entities often requires tedious manual configuration and continuous adjustments. Addressing this workflow bottleneck, software vendors are increasingly integrating conversational AI to automate ad-hoc report generation. For example, on November 4, 2026, it was announced that Campfire added a new reporting workflow to Ember, its AI assistant, allowing finance teams to describe and generate custom ERP reports directly through a chat interface.
According to the product update, users can enter a specific chat command in Ember to request a financial document. The AI assistant then configures the relevant reporting period, entity, and filters, returning a link to the newly generated report. This feature supports standard outputs—including balance sheets, income statements, and transaction reports—with options for formula rows and custom groups. Notably, users can refine the output through follow-up conversational requests, such as asking the assistant to add a monthly breakdown or group the results by a specific vendor. The resulting reports are saved directly in the ERP’s Custom Reports section for further adjustment or download.
Evaluation Questions for Finance Leaders
For financial services organizations considering conversational AI to speed up their ERP reporting, evaluating these tools requires looking beyond the chat interface itself. Decision-makers should evaluate how the AI integrates with existing financial workflows:
- Does the AI generate reports that remain fully editable within the native ERP environment, or are they static exports?
- Can the system accurately interpret complex, multi-entity hierarchies and custom formulas?
- Does the tool support drill-down capabilities into underlying transactions, a feature Campfire previously introduced to Ember in early 2026?
Data Prerequisites for AI-Assisted Reporting
Before implementing AI-driven financial reporting, a firm's foundational data must be clean and well-structured. Chat assistants rely on logical data relationships to process natural language requests accurately. Implementing this technology successfully requires a standardized chart of accounts, clear tagging rules for vendors and transactions, and established role-based permissions to ensure the AI only surfaces financial data authorized for that specific user.
Connecting conversational AI to financial reporting requires a strategic approach to data architecture and business process automation. If you are exploring how to bring AI and data intelligence into your operations, Decision Intelligent can help evaluate these capabilities. We work with financial services organizations to structure underlying ERP data and map out the necessary automation workflows for accurate financial analysis.
To explore how AI-assisted reporting and data intelligence could streamline your specific financial statement generation processes, please contact us to discuss your industry workflow.