# Insure With ETH/USDT

Our DeFi protocol offers investors a second option to insure their trades against risks in the form of paying a direct premium (which goes towards the insurance fund) in ETH or USDT, with more chains added later

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### **Insurance Premium Structure**

The insurance premium is determined by our risk assessment engine which gives a **risk rating system** (1-100), where a higher score means lower risk.

| **Risk Rating** | **Premium Fee** | **Risk Level**      |
| --------------- | --------------- | ------------------- |
| 91 – 100        | 4%              | Very Low Risk       |
| 81 – 90         | 6%              | Low Risk            |
| 71 – 80         | 8%              | Moderate Risk       |
| 61 – 70         | 10%             | Slightly High Risk  |
| 51 – 60         | 12%             | High Risk           |
| 31 – 50         | 20%             | Very High Risk      |
| 1 – 30          | 30%             | Extremely High Risk |

#### **Example:**

* If a user wants to insure **$1,000** in a project with a **75 rating**, they pay an **8% premium ($80)**.
* If the project then rugs or scams, they are reimbursed the original **$1,000 via our Dapp.**&#x20;

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### **Risk Assessment Methodology (Automated Engine)**

The initial version of the DApp will **manually list projects**, but once we cruch the numbers we need and get a better understanding on how many insurance policies are paid out VS insurance policies taken out, future versions will use an **automated risk engine** based on:

#### **1. On-Chain Metrics**

* **Liquidity Pool Health** (lock duration, concentration)
* **Token Locks** (vesting schedules, team holdings)
* **Transaction Volume & Anomalies** (unusual large dumps)

#### **2. Audit Integration**

* **Audits from reputable firms**  increase safety scores.
* **Unaudited projects** could receive higher risk ratings.

#### **3. Social Sentiment Analysis**

* Aggregates data from **Twitter, Telegram, CoinGecko** to detect:
  * **Scam accusations**
  * **Community trust levels**
  * **Team reputation** (known vs. anonymous)

#### **4. Team & Project Transparency**

* **Doxxed teams** → Lower risk
* **Anonymous teams** → Higher risk

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### **Roadmap for automated engine**

#### **Phase 1: Manual Listing**

* Team manually vets and lists projects.
* Basic risk scoring based on audits and liquidity checks.

#### **Phase 2: Automated Risk Engine**

* AI-driven risk assessment using **on-chain + social data**.
* Dynamic premium adjustments based on real-time threats.

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