CutVac Risk Cleaner

challenge

Challenge 3

brief

CutVac Risk Cleaner implemented a Python‑based risk‑register processing and feedback pipeline that cleans, validates and analyses risk and mitigation data, then generates automated, insight‑driven email prompts to drive corrective action.

Please be aware that this content was generated follwing an automated review so may not be perfectly accurate; refer to the original challenge brief and team files for authoritative information

key outcomes

Expected to improve risk‑register data quality, reduce inconsistencies and duplicates, and accelerate corrective action by automatically notifying risk and mitigation owners when outcomes worsen or improve.

important files

• Solution/Python Code/cutvac_cleaner.py: Cleans and normalises risk and mitigation data, enforces consistency, and produces a master dataset for analysis.
• Solution/Python Code/mit_success.py: Evaluates mitigation effectiveness and generates insight‑driven email prompts highlighting changes in cost, probability and criticality.
• Solution/Python Code/auto_run_cleaner.py: Watches source files and automatically triggers the cleaning and analysis pipeline when data changes.

details

team: CutVac Risk Cleaner members: tbc topics: solution-centre, hack25, challenge3, python, pandas, watchdog, excel, email-automation, risk-management, risk-register, automation, data-quality, agentic-ai, email-nudges technologies: Python, Pandas, Watchdog, Excel, Email Automation