The problem
Small merchants rarely notice unusual patterns, such as refund abuse or odd-hour transactions, until money is lost.
What to build
Build a lightweight monitor that learns a merchant's normal pattern and alerts on unusual activity with a reason.
Success looks like
High-value anomalies surfaced in a seeded dataset with few false alarms and alerts a shopkeeper can understand.
Suggested technologies
- Anomaly detection
- Streaming data
- Rule and ML hybrid
- Alerts
- Merchant dashboards
An original, independent statement. It is not an official Smart India Hackathon problem statement, and Arventiq Labs is not affiliated with or endorsed by that programme. The scenario is illustrative and does not describe any specific organisation. Free to use with credit.