Podcast

Building a Domestic Risk Assessment Tool: Data Cleaning, Risk Scoring Models and Privacy Compliance

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Building a Domestic Risk Assessment Tool: Data Cleaning, Risk Scoring Models and Privacy Compliance

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Episode Overview

How do you build an accurate, privacy-compliant domestic risk assessment tool that frontline teams can actually use? In this episode Sabina Firtala — who leads Frontline’‘s AI product development and brings experience in data wrangling, model validation, and applied analytics from finance, SaaS, and mission-driven projects — walks through a practical roadmap.

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Sabina Firtala

Chapter Summary

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0:00 - Podcast Introduction
1:10 - Episode Overview: Building a Domestic Risk Assessment Tool
3:05 - Problem Framing: Identifying Risk in Domestic Contexts
6:30 - Project Scope: Objectives, Users, and Impact Goals
10:45 - Data Sources: Case Management, Public Records, and Surveys
14:20 - Data Preparation: Cleaning, Linking, and Feature Engineering
18:00 - Risk Scoring: Model Architecture and Algorithms
21:40 - Model Evaluation: Metrics, Validation, and Bias Assessment
25:15 - Privacy & Ethical Considerations in Risk Assessment
29:00 - Legal Compliance and Data Governance Practices
32:10 - Deployment: Integrating Risk Tools into Frontline Workflows
35:50 - User Interface & Decision Support Design
39:05 - Stakeholder Engagement: Training, Trust, and Adoption
42:20 - Monitoring: Model Maintenance, Drift Detection, and Alerts
45:40 - Case Examples: Impact on Triage and Resource Allocation
48:55 - Challenges: Data Gaps, Uncertainty, and Operational Constraints
52:10 - Collaboration & Partnerships with NGOs and Agencies
55:00 - Funding, Sustainability, and Scaling Strategies
57:20 - Open Resources: Documentation, Reproducibility, and Links
1:00:00 - Lessons Learned and Practical Recommendations
1:02:10 - Future Directions: Research, Policy, and Product Roadmap