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Development of an Automated Financial Planning and Analysis (FP&A) Platform with Excel Integration
  1. case
  2. Development of an Automated Financial Planning and Analysis (FP&A) Platform with Excel Integration

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Development of an Automated Financial Planning and Analysis (FP&A) Platform with Excel Integration

pynest.io
Financial services
Information technology

Challenges in Manual Financial Processes

Finance professionals rely heavily on Excel for FP&A tasks but face inefficiencies due to manual data collection, error-prone calculations, and limited automation capabilities. Existing tools fail to integrate seamlessly with Excel while providing advanced analytical functionality.

About the Client

A fintech company specializing in financial planning and analysis solutions that bridge traditional Excel workflows with automation technologies.

Key Project Goals

  • Create a platform that automates financial planning and analysis workflows within Excel
  • Reduce manual data entry and calculation errors through automation
  • Enable integration of Python-based analytics with Excel's familiar interface
  • Streamline financial reporting and scenario modeling processes

Core System Requirements

  • Excel add-in for seamless integration
  • Automated data collection from multiple sources
  • Python scripting engine for advanced financial modeling
  • Dynamic reporting dashboard with version control
  • Collaboration tools for team-based financial planning

Technology Stack

Python
Excel API
Cloud-based backend
React.js for UI components

System Integrations

  • Excel Online
  • Python libraries (Pandas, NumPy)
  • Cloud storage APIs
  • Single Sign-On (SSO)

Non-Functional Requirements

  • High-performance data processing for large financial datasets
  • Enterprise-grade security for sensitive financial data
  • Scalable architecture to support concurrent users
  • Cross-platform compatibility with Excel desktop and web versions
  • Intuitive user interface requiring minimal training

Expected Business Impact

The solution will reduce financial planning cycle times by 40-60%, decrease calculation errors by 90%, and enable finance teams to focus on strategic analysis rather than manual data management. Organizations will achieve faster decision-making through automated scenario modeling and real-time financial insights.

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