The conventional process of credit document verification heavily relies on manual methods, making it tedious and time-consuming. The advent of self-sovereign identity (SSI) revolutionised the landscape of credit document verification. SSI empowers individuals with complete control over their identity, ensuring privacy, trust, and security. This paper presents an in-depth exploration of SSI's application in the credit processing domain. This paper highlights the implementation of SSI using the Trust over IP framework on Hyperledger Aries, empowering borrowers to own and control the sharing of their verifiable credentials. By integrating Hyperledger Aries and SSI, a robust and interoperable blockchain-based identity framework can be built. This allows individuals to store their verifiable credentials on a distributed ledger securely and selectively disclose them to lenders as needed. This model empowers borrowers to present accurate and tamper-proof credentials, enhancing data privacy, transparency, and trust, while promoting a borrower-centric approach to sharing credentials.
This paper introduces a novel framework for rate discovery in de-centralized finance (DeFi), focusing on the unique challenges andopportunities within decentralized lending platforms. We explorethe mechanisms of interest rate formation in a decentralized en-vironment, free from traditional banking institutions’ control. Byleveraging lending pool dynamics, we propose a method that inte-grates borrowers’ risk profiles with market liquidity conditions todetermine fair borrowing rates without third party involvment. Ourmodel aims to offer a transparent and reliable solution for rate dis-covery in DeFi. Through a series of simulations, we demonstratethe potential of our framework to improve lending practices in theDeFi ecosystem, making it a viable and competitive alternative toconventional financial systems. The findings suggest that our ap-proach not only enhances the transparency and fairness of the lend-ing process but also encourages a more informed participation oflenders and borrowers, ultimately contributing to the stability andgrowth of the DeFi market.
To understand the disruption and implications of distributed ledger technologies for financial reporting and auditing, we analyze firm misreporting, auditor monitoring and competition, and regulatory policy in a unified model. A federated blockchain for financial reporting and auditing can improve verification efficiency not only for transactions in private databases but also for cross-chain verifications through privacy-preserving computation protocols. Despite the potential benefit of blockchains, private incentives for firms and first-mover advantages for auditors can create inefficient under-adoption or partial adoption that favors larger auditors. Although a regulator can help coordinate the adoption of technology, endogenous choice of transaction partners by firms can still lead to adoption failure. Our model also provides an initial framework for further studies of the costs and implications of the use of distributed ledgers and secure multiparty computation in financial reporting, including the positive spillover to discretionary auditing and who should bear the cost of adoption. This paper was accepted by David Simchi-Levi, finance. Funding: The authors gratefully acknowledge research support from the FinTech Laboratory at J. Mack Robinson College of Business at Georgia State University, the Center for Research in Security Prices at the University of Chicago, the Ripple University Blockchain Research Initiative, and the Smith AI Initiative for Capital Market Research at the University of Maryland. Supplemental Material: The online appendix is available at https://doi.org/10.1287/mnsc.2023.02577 .
The long-lasting intermediated structure of international bond markets has come under scrutiny in recent times because of the risks it exposes final investors to, mostly in relation to the difficulties these investors face in enforcing their rights. Distributed ledger technologies (DLTs) have emerged as a strong contender in efforts to improve the position of final investors by shifting the market to a direct holding structure. In this context, it is necessary to ask if organising international bond markets under a DLT-based direct holding structure will effectively address the risks surrounding intermediated securities. Furthermore, it is important to assess the impact such a change is likely to have on other players in the market (including intermediaries and issuers), as well as on the financial system as a whole. With these questions in mind, this article begins with an explanation of the primary legal implication of holding intermediated securities, i.e., that final investors do not hold legal title over the bonds they have invested in because they are not engaged in a direct relationship with the issuer. The paper then proceeds to dissect the risks such arrangements expose investors to and contrast those risks with the benefits that intermediation afford to investors, issuers and the financial system in general. It is then argued that DLTs are not only inadequate to the task of addressing those risks, but would also eliminate most of the advantages of intermediation. The paper goes on to examine how investors and issuers are not incentivised to promote the development of a DLT-based bond market organised under a direct holding structure. It concludes with the suggestion that a better way to improve the position of final investors in bond markets is to explore how DLTs may enhance the benefits already created by intermediation, rather than relying on these technologies to eliminate intermediation altogether. In particular, it is submitted that DLTs may introduce efficiencies in the management of the bonds, the performance of obligations by issuers, the settlement process, the performance of securities financing transactions, and the provision of services by intermediaries.
As one of the most popular blockchain platforms supporting smart contracts, Ethereum has caught the interest of both investors and criminals. Differently from traditional financial scenarios, executing Know Your Customer verification on Ethereum is rather difficult due to the pseudonymous nature of the blockchain. Fortunately, as the transaction records stored in the Ethereum blockchain are publicly accessible, we can understand the behavior of accounts or detect illicit activities via transaction mining. Existing risk control techniques have primarily been developed from the perspectives of de-anonymizing address clustering and illicit account classification. However, these techniques cannot be used to ascertain the potential risks for all accounts and are limited by specific heuristic strategies or insufficient label information. These constraints motivate us to seek an effective rating method for quantifying the spread of risk in a transaction network. To the best of our knowledge, we are the first to address the problem of account risk rating on Ethereum by proposing a novel model called RiskProp, which includes a de-anonymous score to measure transaction anonymity and a network propagation mechanism to formulate the relationships between accounts and transactions. We demonstrate the effectiveness of RiskProp in overcoming the limitations of existing models by conducting experiments on real-world datasets from Ethereum. Through case studies on the detected high-risk accounts, we demonstrate that the risk assessment by RiskProp can be used to provide warnings for investors and protect them from possible financial losses, and the superior performance of risk score-based account classification experiments further verifies the effectiveness of our rating method.
The collapse of FTX has underscored the critical importance of auditing, especially in the fast-growing decentralized finance (DeFi) markets. Due to the decentralized nature of DeFi platforms, which facilitate peer-to-peer transactions without intermediaries, and the rapid pace of innovation in the unregulated and highly asymmetric information environment of the DeFi market, traditional financial auditing methods face significant hurdles. This study explores the relevance of auditing in DeFi protocols and highlights its critical role in ensuring transparency, security, and trust within these decentralized systems. Through a comprehensive analysis of the unique characteristics of DeFi, including smart contracts and blockchain technology, we delve into the specific challenges and risks associated with auditing DeFi applications. Furthermore, the article discusses the demand for robust auditing practices, regulatory oversight, and industry standards to enhance resilience and stability in this fast-growing emerging market.
Nov 15, 2022·Zeitschrift für schweizerische Statistik und Volkswirtschaft/Schweizerische Zeitschrift für Volkswirtschaft und Statistik/Swiss journal of economics and statistics
Basil Guggenheim, Sébastien Kraenzlin, Christoph Meyer
Abstract We use unique individual bank-to-bank repo transaction data to empirically assess the efficiency of the existing Swiss financial market infrastructure (FMI) for executing delivery versus payment transactions. This approach enables us to identify its current benefits and drawbacks as well as where new technologies, such as distributed ledger technology, could provide a remedy. We find that the fastest settlement time for repo transactions is 12 s, but that settlements are often delayed by more than 10 min due to the lack of collateral availability. We conclude that the cross-border availability of securities needs to be addressed by either improving interoperability of existing infrastructures or using new technologies.
Michael Darlin, Georgios Palaiokrassas, Leandros Tassiulas
The rise of Decentralized Finance (“DeFi”) on the Ethereum blockchain has enabled the creation of lending platforms, which serve as marketplaces to lend and borrow digital currencies. Initially, we categorize the activity of lending platforms within a standard regulatory framework. We then propose an Ethereum address grouping algorithm using activity over DeFi protocols and employ a novel classification algorithm to calculate the percentage of fund flows into DeFi lending platforms that can be attributed to debt created elsewhere in the system (“debt-financed collateral”). Based on our results, we conclude that the wide-spread use of stablecoins as debt-financed collateral increases financial stability risks in the DeFi ecosystem.
The failure probability and economic losses are astonishingly high in the cryptocurrency market. We perform a comparative analysis of a dynamic logit model and machine learning methods for the predictors for cryptocurrency failure and the pricing of crypto failure risk. We document different significant market- and characteristic-based predictors for coin and token failures. Moreover, we document a significantly positive relation between failure risk and returns, which cannot be explained by the common pricing factors and arbitrage costs in the cryptocurrency market. The high failure risk premium suggests that investors require extra returns for bearing high failure risk of crypto assets.
The Internet of Value (IOV) with its distributed ledger technology (DLT) underpinning has created new forms of lending markets. As an integral part of the decentralised finance (DeFi) ecosystem, lending protocols are gaining tremendous traction, holding an aggregate liquidity supply of over $40 billion at the time of writing. In this paper, we enumerate the challenges of traditional money markets led by banks and lending platforms, and present advantageous characteristics of DeFi lending protocols that might help resolve deep-rooted issues in the conventional lending environment. With the examples of Maker, Compound and Aave, we describe in detail the mechanism of DeFi lending protocols. We discuss the persisting reliance of DeFi lending on the traditional financial system, and conclude with the outlook of the lending market in the IOV era.
In this paper I discuss how blockchains potentially could affect the way credit risk is modeled, and how the improved trust and timing associated with blockchain-enabled real-time accounting could improve default prediction. To demonstrate the (quite substantial) effect the change would have on well-known credit risk measures, a simple case-study compares Z-scores and Merton distances to default computed using typical accounting data of today to the same risk measures computed under a hypothetical future blockchain regime.
The Holy Grail of a decentralised stablecoin is achieved on rigorous mathematical frameworks, obtaining multiple advantageous proofs: stability, convergence, truthfulness, faithfulness, and malicious-security. These properties could only be attained by the novel and interdisciplinary combination of previously unrelated fields: model predictive control, deep learning, alternating direction method of multipliers (consensus-ADMM), mechanism design, secure multi-party computation, and zero-knowledge proofs. For the first time, this paper proves: - the feasibility of decentralising the central bank while securely preserving its independence in a decentralised computation setting - the benefits for price stability of combining mechanism design, provable security, and control theory, unlike the heuristics of previous stablecoins - the implementation of complex monetary policies on a stablecoin, equivalent to the ones used by central banks and beyond the current fixed rules of cryptocurrencies that hinder their price stability - methods to circumvent the impossibilities of Guaranteed Output Delivery (G.O.D.) and fairness: standing on truthfulness and faithfulness, we reach G.O.D. and fairness under the assumption of rational parties As a corollary, a decentralised artificial intelligence is able to conduct the monetary policy of a stablecoin, minimising human intervention.
The thesis consists of three chapters and studies the role of corporate bond dealers as liquidity providers in decentralized over-the-counter markets. The first two empirical chapters explore the impact of dealers' inventory financing constraints on their ability to act as middlemen in corporate bond markets. Specifically, the first chapter provides empirical evidence that dealers' financing constraints are a crucial determinant of the costs of their liquidity provision. The second chapter demonstrates that bonds handled by dealers with higher financing constraints are associated with substantially larger and abrupt price declines and slower price reversals in case of a rating downgrade from investment to non-investment grades. The third theoretical chapter studies the effects of post-trade disclosure on a dealer's dynamic trading strategy in a two-period dealership market and shows that in terms of customer welfare neither a regime with full nor one without post-trade transparency is universally dominating.
Purpose This paper aims to present a methodology for constructing cointegrated portfolios consisting of different cryptocurrencies and examines the performance of a number of trading strategies for the cryptocurrency portfolios. Design/methodology/approach The authors apply a series of statistical methods, including the Johansen test and Engle–Granger test, to derive a linear combination of cryptocurrencies that form a mean-reverting portfolio. Trading systems are designed and different trading strategies with stop-loss constraints are tested and compared according to a set of performance metrics. Findings The paper finds cointegrated portfolios involving four cryptocurrencies: Bitcoin (BTC), Ethereum (ETH), Bitcoin Cash (BCH) and Litecoin (LTC), and the corresponding trading strategies are shown to be profitable under different configurations. Originality/value The main contributions of the study are the use of multiple altcoins in addition to bitcoin to construct a cointegrated portfolio, and the detailed comparison of the performance of different trading strategies with and without stop-loss constraints.