{"ID":2889470,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2507.20494","arxiv_id":"2507.20494","title":"Deep Reputation Scoring in DeFi: zScore-Based Wallet Ranking from Liquidity and Trading Signals","abstract":"As decentralized finance (DeFi) evolves, distinguishing between user behaviors - liquidity provision versus active trading - has become vital for risk modeling and on-chain reputation. We propose a behavioral scoring framework for Uniswap that assigns two complementary scores: a Liquidity Provision Score that assesses strategic liquidity contributions, and a Swap Behavior Score that reflects trading intent, volatility exposure, and discipline. The scores are constructed using rule-based blueprints that decompose behavior into volume, frequency, holding time, and withdrawal patterns. To handle edge cases and learn feature interactions, we introduce a deep residual neural network with densely connected skip blocks inspired by the U-Net architecture. We also incorporate pool-level context such as total value locked (TVL), fee tiers, and pool size, allowing the system to differentiate similar user behaviors across pools with varying characteristics. Our framework enables context-aware and scalable DeFi user scoring, supporting improved risk assessment and incentive design. Experiments on Uniswap v3 data show its usefulness for user segmentation and protocol-aligned reputation systems. Although we refer to our metric as zScore, it is independently developed and methodologically different from the cross-protocol system proposed by Udupi et al. Our focus is on role-specific behavioral modeling within Uniswap using blueprint logic and supervised learning.","short_abstract":"As decentralized finance (DeFi) evolves, distinguishing between user behaviors - liquidity provision versus active trading - has become vital for risk modeling and on-chain reputation. We propose a behavioral scoring framework for Uniswap that assigns two complementary scores: a Liquidity Provision Score that assesses...","url_abs":"https://arxiv.org/abs/2507.20494","url_pdf":"https://arxiv.org/pdf/2507.20494v1","authors":"[\"Dhanashekar Kandaswamy\",\"Ashutosh Sahoo\",\"Akshay SP\",\"Gurukiran S\",\"Parag Paul\",\"Girish G N\"]","published":"2025-07-28T03:12:27Z","proceeding":"q-fin.GN","tasks":"[\"q-fin.GN\",\"cs.LG\"]","methods":"[]","has_code":false}