Unlocking Decentralized Lending Protocols: Semantic Unification and Risk Spillover Assessment

Tianze Zhang; Haolin Ren; Qian'Ang Mao; Cong Ma; Shuxi Liang; Daning Hu; Xiao Fan Liu

doi:10.1109/ICDMW60847.2023.00095

Unlocking Decentralized Lending Protocols: Semantic Unification and Risk Spillover Assessment

Tianze Zhang
, Haolin Ren
, Qian'Ang Mao
, Cong Ma
, Shuxi Liang
, Daning Hu^*
, Xiao Fan Liu^*

^*Corresponding author for this work

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

Abstract

In recent years, the decentralized finance (DeFi) sector has witnessed exponential growth, fundamentally altering financial transactions through the innovative application of blockchain technology, which facilitates decentralized operations such as borrowing, lending, and trading on autonomous protocols. Our study seeks to deepen the understanding of lending protocols, a cornerstone in the DeFi ecosystem, by unraveling their complexities and identifying potential risks, alongside proposing mitigation strategies. We introduce a method to obtain and manage on-chain data from decentralized lending protocols, enhancing the transparency and facilitating intuitive data analysis for users. Furthermore, we propose two novel metrics to calculate the leverage of lending protocols, aiming to equip users with critical insights for informed decision-making, thereby fostering a safer and more efficient DeFi ecosystem. © 2023 IEEE.

Original language	English
Title of host publication	Proceedings - 23rd IEEE International Conference on Data Mining Workshops
Subtitle of host publication	ICDMW 2023
Editors	Jihe Wang, Yi He, Thang N. Dinh
Publisher	IEEE
Pages	691-697
ISBN (Electronic)	9798350381641
ISBN (Print)	979-8-3503-8165-8
DOIs	https://doi.org/10.1109/ICDMW60847.2023.00095
Publication status	Published - Dec 2023
Event	23rd IEEE International Conference on Data Mining (ICDM 2023) - Shanghai, China Duration: 1 Dec 2023 → 4 Dec 2023 https://www.cloud-conf.net/icdm2023/

Publication series

Name	IEEE International Conference on Data Mining Workshops, ICDMW
ISSN (Print)	2375-9232
ISSN (Electronic)	2375-9259

Conference

Conference	23rd IEEE International Conference on Data Mining (ICDM 2023)
Place	China
City	Shanghai
Period	1/12/23 → 4/12/23
Internet address	https://www.cloud-conf.net/icdm2023/

Research Keywords

data mining
DeFi
lending protocols
leverage
risk

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10.1109/ICDMW60847.2023.00095

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Zhang, T., Ren, H., Mao, QA., Ma, C., Liang, S., Hu, D., & Liu, X. F. (2023). Unlocking Decentralized Lending Protocols: Semantic Unification and Risk Spillover Assessment. In J. Wang, Y. He, & T. N. Dinh (Eds.), Proceedings - 23rd IEEE International Conference on Data Mining Workshops: ICDMW 2023 (pp. 691-697). (IEEE International Conference on Data Mining Workshops, ICDMW). IEEE. https://doi.org/10.1109/ICDMW60847.2023.00095

@inproceedings{e91f2a874b6c4c26b1b44d92bac26402,

title = "Unlocking Decentralized Lending Protocols: Semantic Unification and Risk Spillover Assessment",

abstract = "In recent years, the decentralized finance (DeFi) sector has witnessed exponential growth, fundamentally altering financial transactions through the innovative application of blockchain technology, which facilitates decentralized operations such as borrowing, lending, and trading on autonomous protocols. Our study seeks to deepen the understanding of lending protocols, a cornerstone in the DeFi ecosystem, by unraveling their complexities and identifying potential risks, alongside proposing mitigation strategies. We introduce a method to obtain and manage on-chain data from decentralized lending protocols, enhancing the transparency and facilitating intuitive data analysis for users. Furthermore, we propose two novel metrics to calculate the leverage of lending protocols, aiming to equip users with critical insights for informed decision-making, thereby fostering a safer and more efficient DeFi ecosystem. {\textcopyright} 2023 IEEE.",

keywords = "data mining, DeFi, lending protocols, leverage, risk",

author = "Tianze Zhang and Haolin Ren and Qian'Ang Mao and Cong Ma and Shuxi Liang and Daning Hu and Liu, \{Xiao Fan\}",

year = "2023",

month = dec,

doi = "10.1109/ICDMW60847.2023.00095",

language = "English",

isbn = "979-8-3503-8165-8",

series = "IEEE International Conference on Data Mining Workshops, ICDMW",

publisher = "IEEE",

pages = "691--697",

editor = "Jihe Wang and Yi He and Dinh, \{Thang N.\}",

booktitle = "Proceedings - 23rd IEEE International Conference on Data Mining Workshops",

address = "United States",

note = "23rd IEEE International Conference on Data Mining (ICDM 2023) ; Conference date: 01-12-2023 Through 04-12-2023",

url = "https://www.cloud-conf.net/icdm2023/",

}

Zhang, T, Ren, H, Mao, QA, Ma, C , Liang, S, Hu, D & Liu, XF 2023, Unlocking Decentralized Lending Protocols: Semantic Unification and Risk Spillover Assessment. in J Wang, Y He & TN Dinh (eds), Proceedings - 23rd IEEE International Conference on Data Mining Workshops: ICDMW 2023. IEEE International Conference on Data Mining Workshops, ICDMW, IEEE, pp. 691-697, 23rd IEEE International Conference on Data Mining (ICDM 2023), Shanghai, China, 1/12/23. https://doi.org/10.1109/ICDMW60847.2023.00095

Unlocking Decentralized Lending Protocols: Semantic Unification and Risk Spillover Assessment. / Zhang, Tianze; Ren, Haolin; Mao, Qian'Ang et al.
Proceedings - 23rd IEEE International Conference on Data Mining Workshops: ICDMW 2023. ed. / Jihe Wang; Yi He; Thang N. Dinh. IEEE, 2023. p. 691-697 (IEEE International Conference on Data Mining Workshops, ICDMW).

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

TY - GEN

T1 - Unlocking Decentralized Lending Protocols

T2 - 23rd IEEE International Conference on Data Mining (ICDM 2023)

AU - Zhang, Tianze

AU - Ren, Haolin

AU - Mao, Qian'Ang

AU - Ma, Cong

AU - Liang, Shuxi

AU - Hu, Daning

AU - Liu, Xiao Fan

PY - 2023/12

Y1 - 2023/12

N2 - In recent years, the decentralized finance (DeFi) sector has witnessed exponential growth, fundamentally altering financial transactions through the innovative application of blockchain technology, which facilitates decentralized operations such as borrowing, lending, and trading on autonomous protocols. Our study seeks to deepen the understanding of lending protocols, a cornerstone in the DeFi ecosystem, by unraveling their complexities and identifying potential risks, alongside proposing mitigation strategies. We introduce a method to obtain and manage on-chain data from decentralized lending protocols, enhancing the transparency and facilitating intuitive data analysis for users. Furthermore, we propose two novel metrics to calculate the leverage of lending protocols, aiming to equip users with critical insights for informed decision-making, thereby fostering a safer and more efficient DeFi ecosystem. © 2023 IEEE.

AB - In recent years, the decentralized finance (DeFi) sector has witnessed exponential growth, fundamentally altering financial transactions through the innovative application of blockchain technology, which facilitates decentralized operations such as borrowing, lending, and trading on autonomous protocols. Our study seeks to deepen the understanding of lending protocols, a cornerstone in the DeFi ecosystem, by unraveling their complexities and identifying potential risks, alongside proposing mitigation strategies. We introduce a method to obtain and manage on-chain data from decentralized lending protocols, enhancing the transparency and facilitating intuitive data analysis for users. Furthermore, we propose two novel metrics to calculate the leverage of lending protocols, aiming to equip users with critical insights for informed decision-making, thereby fostering a safer and more efficient DeFi ecosystem. © 2023 IEEE.

KW - data mining

KW - DeFi

KW - lending protocols

KW - leverage

KW - risk

UR - https://www.scopus.com/pages/publications/85186145177

UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-85186145177&origin=recordpage

U2 - 10.1109/ICDMW60847.2023.00095

DO - 10.1109/ICDMW60847.2023.00095

M3 - RGC 32 - Refereed conference paper (with host publication)

SN - 979-8-3503-8165-8

T3 - IEEE International Conference on Data Mining Workshops, ICDMW

SP - 691

EP - 697

BT - Proceedings - 23rd IEEE International Conference on Data Mining Workshops

A2 - Wang, Jihe

A2 - He, Yi

A2 - Dinh, Thang N.

PB - IEEE

Y2 - 1 December 2023 through 4 December 2023

ER -

Zhang T, Ren H, Mao QA, Ma C , Liang S, Hu D et al. Unlocking Decentralized Lending Protocols: Semantic Unification and Risk Spillover Assessment. In Wang J, He Y, Dinh TN, editors, Proceedings - 23rd IEEE International Conference on Data Mining Workshops: ICDMW 2023. IEEE. 2023. p. 691-697. (IEEE International Conference on Data Mining Workshops, ICDMW). doi: 10.1109/ICDMW60847.2023.00095

Unlocking Decentralized Lending Protocols: Semantic Unification and Risk Spillover Assessment

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