Predictive Modeling & Dashboard for Haven

Haven Servicing is a digital relationship platform for mortgage servicers, subservicers, and lenders. It helps engage homeowners, predict borrower intent, and drive cross-sell opportunities while integrating seamlessly into existing servicing systems.

Core Features:

Borrower Intent & Prediction Modules — Predict prepayment and understand borrower intentions.

Personalized Offers & Cross-sell / Recapture — Deliver tailored offers in servicing portals to maximize revenue.

Engagement / Educational Content — Educate homeowners about financial decisions and homeownership planning.

White‑Label / Brandable Experience — Support custom branding and multiple brand portals.

Integration / Seamless Stack — Integrates directly into existing servicing systems with minimal disruption.

Leads / High Intent Lead Generation — Metrics: 1.4 M+ homeowners, 11% high-intent leads, 11+ offer types.

Interfaces for Servicers / Subservicers / Lenders — Tailored use cases and modules for different stakeholders.

My Contributions:

Designed dashboards to show homeowner behavior, engagement, and risk signals.

Built predictive models for borrower intent (refinance, default, cross-sell receptivity).

Created workflows for personalized offers and nudges across digital channels.

Integrated with servicing systems via APIs to sync data and enable seamless actions.

Developed white‑label frontend components for customizable client branding.

Implemented strict security, privacy, and compliance frameworks.

Optimized infrastructure for performance and scale to support millions of homeowners.

Challenges & Solutions:

Data Quality & Silos — Solved with ETL pipelines, harmonized schemas, and abstraction layers.

Predictive Accuracy — Addressed with ensemble models, retraining, and domain-specific features.

Conversion / Activation — Solved with embedded CTA workflows, A/B testing, and optimized timing.

Adoption by Servicers / Lenders — Solved with modular integration, white labeling, and pilots.

Regulatory / Privacy / Compliance — Addressed with encryption, governance, and audit trails.

Scalability & Performance — Solved with cloud scaling, caching, and efficient data stores.

Success Metrics & Signals:

Backed by Y Combinator and notable venture investors.

Onboarded 1.4 M+ homeowners.

Generated 11% high-intent leads and supported 11+ offer types.

Featured in fintech and mortgage press including HousingWire and Bloomberg.

Claims of enabling servicers to improve recapture and cross-sell strategies.

Tech Stack:

Frontend: React (homeowner portals, dashboards, white-label components).

Backend: Node.js / Python with REST/GraphQL APIs.

ML / Prediction Models: Python (scikit‑learn, XGBoost, PyTorch/TensorFlow).

Data: PostgreSQL/MySQL, Snowflake/BigQuery, S3 for storage.

Real-Time: Kafka / PubSub for engagement triggers.

Integrations: Loan-servicing systems, CRM, payment gateways, APIs.

Security: Encryption, IAM, compliance frameworks.

Infrastructure: AWS/GCP/Azure, Docker/Kubernetes, CI/CD pipelines.

Monitoring: Grafana, Prometheus, ELK stack.

Development Environment: Replit (collaborative cloud IDE for full-stack development, real-time testing, and deployment).