Case Studies
A retailer’s Dilemma of Unlocking Data Potential in Wireless Retail
In the US, many retail dealers operate under various wireless carriers to drive device and service sales. These dealers sell using tools offered by the carrier and some third-party tools. Sprint was one such carrier whose dealers faced challenges due to underutilized data and recurring issues of chargebacks, lease frauds, and transactional discrepancies.
Navigating Transaction Complexities in Wireless Retail
Improving transaction processing in terms of time and accuracy
Flagging transactions with potential fraud or discrepancies
Making the analysis actionable for decision-making and recording
Providing holistic access to transactions across the organization
A 72-Hour Miracle- Transforming the Operations with AI-Driven Auditing
Created a robust data engineering pipeline using RPA
and Python scripts to fetch data from multiple sources and ingest it into a data warehouse.
Built data transformers to parse and process data for proper conversion between changing formats.
Implemented email bounce analysis and robocalling to verify fraudulent transactions.
Implemented a rule-based AI (GOFAI) engine to flag discrepancies, frauds, and assess refunds and chargebacks.
Developed a platform for auditors, management, and employees to track the transaction vetting process and actions taken based on insights.
Comprehensive Auditing & Actionable Insights Driving $1M in Savings
Data aggregation from multiple sources
Data quality enhancement with missing data handling
Robust process to handle changing requirements
Accurate commission reconciliation
Actionable insights and tracking for remedial actions
Measurable Results and Impact
Achieved client cost savings exceeding $1 million within 1.5 years
Enabled detection of both intentional and unintentional losses by employees
Reduced fraud and discrepancy detection time from 4 weeks to 72 hours
Key Achievements
Developed a robust data engineering pipeline and AI-powered auditing platform
Integrated multiple data sources and handled changing data formats
Provided actionable insights and enabled tracking of remedial actions
Achieved significant cost savings and reduced fraud detection time
Conclusion
Through our AI-driven sales auditing and transaction monitoring platform, we empowered retail dealers to streamline their operations, improve transaction processing accuracy, and detect frauds and discrepancies efficiently. The platform’s ability to aggregate data, enhance data quality, and generate actionable insights led to substantial cost savings, reduced fraud detection time, and improved overall operational efficiency.