The problem PrivInsure solves

PrivInsure addresses key challenges in the insurance industry by prioritizing privacy, trust, and transparency. Here's how it solves common problems:

• User Privacy:
  Many individuals are hesitant to share sensitive health information with insurance providers. PrivInsure allows users to check their insurance eligibility without ever sharing private health data.

• Insurer Transparency:
  Insurance providers often hesitate to disclose detailed policy terms upfront. With PrivInsure, insurers can determine eligibility without sharing specific policy requirements.

• Risk of Data Breaches:
  Sharing health data with insurers opens users to potential data breaches and misuse. PrivInsure mitigates this risk by ensuring sensitive health information remains private and secure.

• Time-consuming Processes:
  Traditional insurance checks involve multiple steps and extensive information sharing. PrivInsure streamlines this with efficient 2-party computations, speeding up the eligibility-check process.

How It Makes Tasks Easier & Safer

PrivInsure uses advanced 2-party computation (MPC) to provide the following benefits:

• ✅ For Users:
  Users can securely check insurance eligibility without exposing their personal health data. They maintain complete control of their privacy while accessing necessary information.

• ✅ For Insurers:
  Insurance companies can determine a user's eligibility without revealing internal policy terms. This creates trust and transparency while maintaining confidentiality.

PrivInsure empowers individuals and insurance providers to securely navigate eligibility checks without unnecessary exposure, risk, or delays. It’s the future of safe, privacy-focused insurance processes.

Challenges we ran into

Building PrivInsure came with technical and operational challenges. Here’s a quick overview of the key hurdles we faced and how we overcame them:

1. Understanding 2-Party Computation (MPC) Complexity

Working with 2-party computation was conceptually challenging due to its cryptographic foundations and edge cases.

How We Overcame It:
We researched extensively, tested MPC frameworks - Typescript mpc-framework and Trinity MPC scheme, and collaborated with the mentors to simplify computations step by step.

2. Integrating Privacy with Usability

Balancing privacy and user experience was tough. We had to ensure users could check eligibility easily without compromising sensitive data privacy.

How We Overcame It:
We prioritized intuitive design and optimized computation workflows. User testing validated these improvements, ensuring a smooth and seamless user experience.

3. Framework Compatibility and Deployment Issues

Typescript MPC frameworks faced compatibility bugs, especially during cryptographic computation. Deployment across environments was inconsistent.

How We Overcame It:
We debugged these issues by isolating computations, improving testing workflows, and collaborating with the mpc-cli quick starter tool developers to ensure compatibility.

4. Data Synchronization During Computation

Misaligned data streams between user and insurer computations led to failed checks. Synchronization errors were a significant blocker.

How We Overcame It:
We added validation layers and synchronization logic to align data streams and ensure accurate computation. Detailed logging and thorough testing resolved these errors.

Key Takeaway

These challenges taught us valuable lessons about cryptography, MPC frameworks, and privacy-preserving technologies. Overcoming these hurdles required testing, collaboratio