US-12619960-B2 - Optimizing ledger usage and liquidation operations thereon

US12619960B2US 12619960 B2US12619960 B2US 12619960B2US-12619960-B2

Abstract

A network-based computing system can implement a transaction service in which digital wallets of client transaction entities are dynamically monitored to maintain a balance within a liquidity tranche unique to each transaction entity. The computing system can further execute a smart liquidity model that parses transaction requests into smaller clips and execution timing intervals such that risk of transaction failure is minimized or eliminated.

Inventors

Chuan Sun
Hope Chapman
Piali Das
Jon Wedrogowski
Laurel Ruhlen
Bradley Chase

Assignees

RIPPLE LABS INC.

Dates

Publication Date: 20260505
Application Date: 20231003

Claims (16)

1 . A network-based computing system implementing a transaction execution service, comprising: a network communication interface to communicate, over one or more networks with computing devices of transaction entities and computing systems of multiple crypto exchanges; one or more processors; and a memory storing instructions that, when executed by the one or more processors, cause the network-based computing system to: receive, over the one or more networks, real-time exchange data from a computing system of a crypto exchange of the multiple crypto exchanges; based on the real-time exchange data, determine a set of constraints of the crypto exchange; in response to a low liquidity threshold being triggered for a digital wallet of a transaction entity at the crypto exchange, the low liquidity threshold being determined based on historical consumption patterns of the transaction entity and other liquidity signals to avert liquidity risk, generate an execution plan for the transaction entity in which a first asset is to be exchanged for a second asset using the crypto exchange, wherein generating the execution plan includes: determining, based on one or more machine learning or artificial intelligence models that utilize the real-time exchange data and the set of constraints as input signals, a set of parameters for transacting a transaction amount as a plurality of clips, the set of parameters being determined to optimize one or more objectives for transacting the transaction amount, the one or more objectives including an objective to reduce a load on a ledger of the crypto exchange where the plurality of clips are to be exchanged; wherein the optimized set of configuration parameters indicate each of a number of the plurality of clips, a size of each of the plurality of clips, and a timing or input signal for determining when each of the plurality of clips are to be executed on the crypto exchange; and responsive to transmission of a set of transaction commands from the computing system to the crypto exchange, executing the plurality of clips in accordance with the execution plan.
2 . The network-based computing system of claim 1 , wherein the real-time exchange data comprises an order depth at the crypto exchange.
3 . The network-based computing system of claim 2 , wherein the order depth corresponds to a current number of transaction requests and transaction amounts for a current number of transaction requests at the crypto exchange.
4 . The network-based computing system of claim 1 , wherein the execution plan is further optimized for completing one or more transactions of a transaction request while minimizing a transaction cost or risk.
5 . The network-based computing system of claim 1 , wherein generating the execution plan includes identifying one or more intermediate assets and transactions when exchanging the first asset for the second asset.
6 . The network-based computing system of claim 5 , wherein generating the execution plan includes identifying multiple sets of transactions that include the intermediate assets.
7 . The network-based computing system of claim 1 , wherein the execution plan is generated in response to a transaction request.
8 . A non-transitory computer-readable medium that stores instructions, which when executed by one or more processors of a computer system, cause the computer system to perform operations that comprise: receiving, over the one or more networks, real-time exchange data from a computing system of a crypto exchange; based on the real-time exchange data, determining a set of constraints of the crypto exchange; in response to a low liquidity threshold being triggered for a digital wallet of a transaction entity at the crypto exchange, the low liquidity threshold being determined based on historical consumption patterns of the transaction entity and other liquidity signals to avert liquidity risk, generating an execution plan for the transaction entity in which a first asset is to be exchanged for a second asset using the crypto exchange, wherein generating the execution plan includes: determining, based on one or more machine learning or artificial intelligence models that utilize the real-time exchange data and the set of constraints as input signals, a set of parameters for transacting a transaction amount as a plurality of clips, the set of parameters being determined to optimize one or more objectives for transacting the transaction amount, the one or more objectives including an objective to reduce a load on a ledger of the crypto exchange where the plurality of clips are to be exchanged; wherein the optimized set of configuration parameters indicate each of a number of the plurality of clips, a size of each of the plurality of clips, and a timing or input signal for determining when each of the plurality of clips are to be executed on the crypto exchange; and transmitting, over the one or more networks, a set of transaction commands to the respective computing systems of the crypto exchange, to execute the plurality of clips in accordance with the execution plan.
9 . The non-transitory computer-readable medium of claim 8 , wherein the real-time exchange data comprises an order depth at the crypto exchange.
10 . The non-transitory computer-readable medium of claim 9 , wherein the order depth corresponds to a current number of transaction requests and transaction amounts for a current number of transaction requests at the crypto exchange.
11 . The non-transitory computer-readable medium of claim 8 , wherein the set of constraints corresponds to a maximum transaction amount for each clip at the crypto exchange, and a timing interval or parameter for each clip at the crypto exchange.
12 . The non-transitory computer-readable medium of claim 8 , wherein generating the execution plan includes identifying one or more intermediate assets and transactions when exchanging the first asset for the second asset.
13 . The non-transitory computer-readable medium of claim 12 , wherein generating the execution plan includes identifying multiple sets of transactions that include the intermediate assets.
14 . The non-transitory computer-readable medium of claim 8 , wherein the execution plan is generated in response to a transaction request.
15 . A computer-implemented method comprising: receiving, over the one or more networks, real-time exchange data from a computing system of a crypto exchange; based on the real-time exchange data, determining a set of constraints of the crypto exchange; in response to a low liquidity threshold being triggered for a digital wallet of a transaction entity at the crypto exchange, the low liquidity threshold being determined based on historical consumption patterns of the transaction entity and other liquidity signals to avert liquidity risk, generating an execution plan for the transaction entity in which a first asset is to be exchanged for a second asset using the crypto exchange, wherein generating the execution plan includes: identifying a transaction amount for the transaction entity to exchange the first asset for the second asset based on historical consumption patterns of the transaction entity to automatically avert a liquidity risk of the transaction entity; determining, based on one or more machine learning or artificial intelligence models that utilize the real-time exchange data and the set of constraints as input signals, a set of parameters for transacting a transaction amount as a plurality of clips, the set of parameters being determined to optimize one or more objectives for transacting the transaction amount, the one or more objectives including an objective to reduce a load on a ledger of the crypto exchange where the plurality of clips are to be exchanged; wherein the optimized set of configuration parameters indicate each of a number of the plurality of clips, a size of each of the plurality of clips, and a timing or input signal for determining when each of the plurality of clips are to be executed on the exchange; and transmitting, over the one or more networks, a set of transaction commands to the respective computing system of the crypto exchange, to execute the plurality of clips in accordance with the execution plan.
16 . The method of claim 15 , wherein the real-time exchange data comprises an order depth at the crypto exchange.

Description

RELATED APPLICATION(S) This application claims benefit of priority to provisional U.S. Patent Application No. 63/412,809, filed Oct. 3, 2022; the aforementioned priority application being hereby incorporated by reference in its entirety. TECHNOLOGICAL FIELD This application relates to ledgers, including block-chains and distributed ledgers, and more specifically, to optimizing ledger usage and liquidation operations that utilize ledgers. BACKGROUND Transaction entities may require cross-border payments and transactions involving foreign exchange and other asset conversions. Digital currencies or assets can facilitate instant, immutable conversions at crypto exchanges using distributed ledgers. Ledger-based exchanges (e.g., crypto-exchanges) utilize block chain ledgers to process transactions. Transactions on such exchanges typically move funds in the form of a fiat to a digital asset, a digital asset to a fiat, and/or a first digital asset to a second digital asset. Digital assets are typically in the form of data structures that are associated with accounts and values, and their existence is cryptographically secured on the block chain. When a transaction is executed, an immutable record of the transaction is stored on the block chain. In general, the block chain ledger stores, in immutable form, account identifiers, account balances (including digital assets and/or available fiat), and transfers, with each transfer being subject to validation processes of the ledger. Ledger-based exchanges face technical challenges that are not present with other types of exchanges and markets. Among them, the transaction count or volume can negatively affect the technological efficiency or throughput of the exchange, as each transaction requires its own set of computational resources to record and validate the transaction. Typically, when the amount of activity increases on a ledger-based exchange, the efficiency of the ledger-based exchange decreases, meaning transactions can take longer to execute simply because of availability and use computing/networking resources. These technological inefficiencies are distinct from market inefficiencies, such as market volatility due to changes in supply/demand. Technological inefficiencies directly relate to the ability of a ledger-based exchange to execute computing processes for a transaction, separate from, for example, market delays and conditions. Technological efficiencies in general, can relate to the availability of technological resources, including computing resources (e.g., amount and type of processing resources, location of processing resources, etc.), networking resources (e.g., available bandwidth), and availability of memory resources, including memory resources where a blockchain (or portion thereof) of the transaction is stored. As such, under conventional approaches, in periods of high transaction volume, the technological efficiency and throughput of a ledger-based exchange can drop, resulting in slower execution time for transactions. Conversely, in periods of low transaction volume, the abundance of computing resources can represent unwanted expenditure of resources, representing cost and/or an increased carbon footprint. BRIEF DESCRIPTION OF THE DRAWINGS The disclosure herein is illustrated by way of example, and not by way of limitation, in the figures of the accompanying drawings in which like reference numerals refer to similar elements, and in which: FIG. 1 is a block diagram illustrating a network-based computing system 100 implementing digital wallet management and liquidation strategy techniques, according to examples described herein; FIG. 2 is flow chart describing a method of digital wallet management for client transaction entities, according to various examples; FIG. 3 is a flow chart describing an example of executing a liquidation model for minimizing liquidation failure risk, according to examples described herein; FIG. 4 is a block diagram illustrating a client computing device of a client transaction entity for triggering transaction and/or liquidation requests, according to examples described herein; and FIG. 5 is a hardware diagram illustrating a computer system upon which examples described herein may be implemented. DETAILED DESCRIPTION A network-based computing system can implement machine learning techniques using the unique liquidity data from various client computing systems that are involved in transactions using digital assets as a transaction medium. The transaction entity can maintain a digital wallet at one or more crypto exchanges that facilitate transactions between different asset classes, such as the fiat money of a particular national entity and one or more digital currencies. The network-based computing system can provide the transaction entity with a trading platform for automating trade actions, provide liquidity and trade recommendations, and automatically fund (including prefund) the digital wallet of the transaction e