Tags: Microsoft, Insurance, Financial Reporting Modernization, agentic ai transformation, GenAI Automation, Conversational Analytics, Fabric Data Agents, Microsoft Fabric Case Study, Revenue Variance Analysis, Dialog with Data, Copilot for Finance, Finance AI, AI-Ready Semantic Model, Finance Ontology, Expense Analysis

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Microsoft Insurance Financial Reporting Modernization

Dialog with Data for Finance: AI-Powered Financial Investigation on Microsoft Fabric

Talk to an expert

Answers inside Teams, Power BI and Excel

Every answer cites its source evidence

Consolidated balance to source invoice in one conversation

See the seven-layer architecture and both Finance use cases inside

CUSTOMER CONTEXT

The Client

A global professional services firm needed Finance to explain any number without navigating several systems. KPI Partners built a layered Finance architecture on Microsoft Fabric, with an AI-enriched semantic layer, a Finance ontology and Fabric Data Agents, serving expense analysis and revenue variance analysis. The full case study walks through how Finance now answers "why has this expense category increased this period?" in a single conversation.

TECHNOLOGY STACK

Tools & platforms powering the solution

Microsoft Fabric (data pipelines, Lakehouse, Warehouse) Finance semantic models (P&L, balance, GL, AP, AR) AI-enriched semantic layer Finance ontology Fabric Data Agents (P&L, GL, AP, AR and Client Revenue) Orchestration Agent Copilot in Microsoft Teams and Excel Power BI Enterprise ERP and financial consolidation (sources)

Finance data engineering, semantic modelling and AI readiness from one team, so Fabric Data Agents speak the language of Finance.

Ready to Turn Financial Data into Answers?

Give Finance one conversational path from consolidated balances to source evidence with KPI Partners and Microsoft Fabric.

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Dialog with Data for Finance: AI-Powered Financial Investigation on Microsoft Fabric

See the seven-layer architecture and both Finance use cases inside

The Client

Tools & platforms powering the solution

Ready to Turn Financial Data into Answers?

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with your network: