HAI Group don launch CORE.3 wit PoL — quantitative Probability of Loss risk metric for Web3
HAI Group don launch CORE.3, updated risk-intelligence platform for Web3 wey bring new metric wey dem call Probability of Loss (PoL). CORE.3 dey convert on-chain data, historical exploit records and economic-feasibility signals into one quantitative PoL score wey estimate how likely person fit loss money when dem interact with protocol or smart contract. The framework dey take over 100 data points wey dem organize into Conditions (raw facts like audit status and admin key controls), Metrics (grouped assessments like smart-contract risk and reserve transparency) and Categories (domain weighting wey dey emphasize critical factors). Dem get separate Proof-of-Opinion layer wey capture subjective inputs (ecosystem relevance, adoption) but dem no include am for PoL calculation. Initial rollout cover about 50 projects, HAI plan to expand coverage to 1,000+ projects within three months. CORE.3 get dashboards for quick manual review and API access for integration into trading workflows and risk systems, make e fit enable automated pre-trade checks, exposure sizing and due diligence. HAI dey position CORE.3 as independent analytics tool inside Hacken ecosystem (Hacken, HackenProof, CER.live), no be investment advice or ratings agency. For traders, main takeaways na new quantitative risk score (PoL) to use with existing indicators, API-based automation for risk checks, and faster on-chain protocol risk assessments wey aim to reduce information asymmetry and help manage counterparty and protocol risk.
Neutral
CORE.3 na mainly na upgrade for infrastructure and analytics, no be protocol launch or financial instrument wey go directly move token prices. For traders, PoL score and APIs dey improve risk visibility and fit reduce information asymmetry, wey fit make dem take better position sizes, deleverage quick, or reduce exposure to high-risk protocols. Short-term market price impact on individual tokens wey dem cover likely small and mixed: some assets fit see short selling if PoL flag high risk, while clearer risk signals fit restore confidence for other assets. For medium to long term, standardized quantitative risk metrics dey tend to stabilize markets by enabling better risk management and institutional participation. Because CORE.3 no change on-chain fundamentals or bring new liquidity, the net directional price effect overall neutral but fit cause idiosyncratic moves for projects wey get newly revealed high or low PoL scores.