RiskMonster is a comprehensive decentralized analytics platform designed for quantitative risk assessment of ERC-20 tokens, DEX liquidity pools, and wallet trading behavior in the DeFi ecosystem. The application provides institutional-grade risk metrics and advanced visualizations to help traders make informed decisions by identifying potential market manipulation, supply concentration risks, and trading anomalies.
The platform employs sophisticated mathematical models including Herfindahl-Hirschman Index (HHI), Gini coefficient, Nakamoto coefficient, and Concentration Ratio (CR8) to calculate composite risk scores. It features multiple analytical visualizations such as bubble maps for holder distribution analysis, Sankey diagrams for token flow patterns, temporal flow analysis for behavioral changes, and circular flow detection for wash trading identification.
This mathematical analysis checks if a few people own most of the coins. If too many coins are held by just a few "whales," it is risky. They can work together to change the price suddenly. A low score is safer for everyone.
| HHI Range | Risk Level | Market Condition |
|---|---|---|
| 1,500 | Low Risk | Competitive market |
| 1,500-2,500 | Moderate Risk | Moderate concentration |
| 2,500 | High Risk | Manipulation risk |
This number measures how fairly the coin is shared. A low score means many people own a similar amount, which is safe. A high score means a few people own almost everything. This is risky because those few people have all the power.
| Gini Range | Distribution Quality | Risk Assessment |
|---|---|---|
| 0.0-0.3 | Healthy distribution | Low risk |
| 0.3-0.5 | Moderate inequality | Monitor closely |
| 0.5 | Dangerous centralization | High risk |
This counts how many people control the majority of supply. The lower the number is, the riskier the token is to invest in. A bigger number is much safer, as it means the majority of the token is very well distributed. If the number is low it means that one or just a few people could drastically alter the price of the token, and that the token's price is not stable.
| Nakamoto Coefficient | Decentralization Level | Risk Level |
|---|---|---|
| 5 | Extremely vulnerable | Very High Risk |
| 5-20 | Moderate vulnerability | Medium Risk |
| 20 | Healthy decentralization | Low Risk |
This looks at the biggest holders and measures how concentrated supply is among them, similar to Nakamoto but based on different mathematical calculations. Typically measured as CR4 (top 4 holders) or CR8 (top 8 holders).
An aggregate metric combining Herfindahl-Hirschman Index (HHI), Gini Coefficient, Nakamoto Coefficient, and Concentration Ratio (CR) into a unified risk score ranging from 0-100.
A classic visual analysis method for crypto. Addresses are bubbles, connections represent transaction activity between them. Our map shows a mix of the top holders, as well as the most recently active holders. This visualization helps identify clustering patterns and potential manipulation networks.
This picture shows how people's behavior is changing over time. It lets you see how broadly and naturally a token has distributed itself among its holders. It also shows trends in holder count over time very effectively.
This analysis technique sorts people into groups: buyers, sellers, and those holding. If there are many more sellers than buyers, it is a sign of a negative trend in price and the price will probably drop, or continue to drop.
This looks for fake trading, volume spam bots, wash trading and collusion. It spots when multiple accounts trade the same tokens back and forth with each other to pretend there is more activity.
This analysis looks for strange activity. It recognizes normal trading and highlights anything that looks unusual. It specifically looks for anomalous activity that often happens right before a big price move.
Unlike any other, instead of overestimating future costs for the purposes of making sure transactions are processed, this gas cost analyzer gives you a moving average of historical transaction prices on a token, showing you the actual costs people are paying at a given time. Gas prices play a big role in the frequency of trades and trading volume cannot be used as an accurate metric without adjusting for gas cost.