Retail | Financial Planning & Analysis
Financial Reporting
Objective
The client needed automated Financial Reports to improve productivity by focusing on anomaly investigation and strategizing.
Challenges
- The high volume of transactional data from multiple sources.
- Time-consuming manual data consolidation and reporting processes.
- Lack of real-time insights for prompt decision-making.
- Difficulty in identifying and analyzing anomalies in financial data.
Solution Proposed
- Implementation of Random Forest algorithms for automated anomaly detection in financial data.
- Tableau was used for real-time data visualization and reporting.
- Engineered a data pipeline to integrate and process data from various sources efficiently.
- Used XGBoost for predictive analytics to forecast financial trends and performance.
Outcome
- Reduction in report generation time by 50%, improving productivity.
- Improved accuracy of financial reports.
- Enabled faster strategic decisions through real-time financial insights.
- Enhanced ability to detect and analyze financial anomalies.
Design & Thinking Wins
- An automated anomaly detection framework integrated with BI dashboards.
- Real-time data visualization tools for comprehensive financial reporting.
- Predictive analytics for accurate financial forecasting.
- Efficient data pipeline for seamless data integration and processing.
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Disclaimer: The outline showcases the typical challenges, solutions, designs, and outcomes for industries and functions, in general, based on Affine’s prowess in the Industry. The outcomes would be much higher for specific clients as they would be based on their data and specific problems to be solved.
