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市场调查报告书
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1880414

流动性路由引擎市场预测至2032年：按组件、部署模式、应用、最终用户和地区分類的全球分析

Liquidity-Routing Engines Market Forecasts to 2032 - Global Analysis By Component, Deployment Mode, Application, End User, and By Geography.
出版日期: | 出版商: Stratistics Market Research Consulting | 英文 200+ Pages | 商品交期: 2-3个工作天内

价格

根据 Stratistics MRC 的一项研究，预计到 2025 年，全球流动性路由引擎市场规模将达到 195 亿美元，到 2032 年将达到 382 亿美元，预测期内复合年增长率为 10.1%。

流动性路由引擎是一种演算法系统，它透过在金融市场中将订单路由到多个流动性池来优化交易执行。这些引擎会分析市场深度、交易成本和延迟，以确保股票、货币和数位资产交易的最佳执行价格。它们会将交易动态路由到交易所、暗池和去中心化平台，从而提高效率并减少滑点。流动性路由引擎在演算法交易和金融科技领域广泛应用，帮助机构投资者和仲介实现收益最大化和风险最小化。

根据 CFA 协会的一项调查，机构投资者越来越多地采用流动性路由演算法来最大限度地减少滑点、优化执行并确保获得去中心化的全球流动性池。

加速向多场所交易的过渡

随着多场所交易模式的持续发展，流动性路由引擎市场对能够即时整合分散流动性池的系统需求强劲。在监管机构对最佳交易透明度的要求以及另类交易系统激增的推动下，机构投资者越来越依赖自适应路由框架来获得最佳价格优化。此外，暗池的激增和全球电子通讯网路的扩展也促使人们需要能够无缝整合不同流动性市场价格讯号的高精度路由工具。

高速路由中的延迟挑战

延迟导致的效能瓶颈仍然是一个重要的阻碍因素，即使是毫秒级的延迟也会扭曲价格发现，并在超低延迟环境下降低执行品质。基础设施不一致的公司往往难以同步地理位置分散的交易所之间的路由工作流程，从而加剧滑点风险。此外，订单流资料的激增增加了处理负载，迫使机构维护高成本的高效能运算堆迭。这些延迟限制了可扩展性，并阻碍了流动性路由引擎在市场波动的情况下保持确定性效能的能力。

人工智慧优化流动性聚合的兴起

人工智慧增强型流动性聚合技术的加速应用代表着一条重要的成长路径，使市场参与企业能够从基于规则的路由转向预测性和自主执行框架。这些引擎由机器学习讯号评分驱动，能够动态评估微观市场状况并优化订单排序。此外，人工智慧赋能的价格路径建模提高了跨多个交易所的分配精度，从而提升成交率并降低执行延迟。这种转变为提供可解释人工智慧模型、即时学习架构以及针对分散的流动性生态系统量身定制的自适应分析的供应商创造了机会。

市场波动阻碍订单执行

在高度动态的价格环境下，高频波动尖峰对交易执行流程的稳定性和路由准确性构成重大威胁。加剧的市场动盪会导致流动性枯竭，扩大价差，并降低交易所层级订单簿的可靠性。此外，日内价格的突然反转会迫使路由引擎即时重新计算路径，从而增加执行错误的机率。这些由波动引起的干扰会增加营运风险，并可能在压力测试市场场景下削弱使用者对自动化路由解决方案的信心。

新冠疫情的影响：

新冠疫情重塑了流动性路由的动态，在不不确定性加剧的情况下，各类资产的交易量激增，推动了数位化的加速和市场碎片化的加剧。疫情加速了电子交易基础设施的现代化，并增强了机构对即时路由智慧的需求。然而，极端波动时期考验了路由的准确性，并暴露了许多公司的基础设施漏洞。疫情后，市场参与企业采取了更具弹性的多场所策略，并投资于云端原生路由解决方案，从而持续推动了对先进的演算法自适应流动性路由引擎的需求。

预计在预测期内，路由演算法细分市场将占据最大的市场份额。

预计在预测期内，路由演算法细分市场将占据最大的市场份额，这主要得益于智慧路由框架的日益普及，这些框架能够提升分散式流动性交易所的订单执行品质。在即时价格优化需求和多资产电子交易扩张的推动下，演算法路由模组已成为机构交易的核心基础设施。这些系统能够评估交易所绩效、历史成交率和微观结构讯号，从而巩固其市场主导地位。智慧订单路由标准化的趋势进一步强化了其在该领域的统治地位。

预计在预测期内，云端部署领域将实现最高的复合年增长率。

预计在预测期内，云端部署领域将实现最高成长率，这主要得益于对弹性运算能力日益增长的需求，以支援复杂、高频的路由工作流程。云端原生路由引擎具有降低基础设施成本和快速扩展的优势，能够帮助企业加速模型更新并降低延迟波动。此外，不断增强的网路安全框架和託管服务架构也促使受监管企业将其执行工作负载迁移到云端环境。持续分析和全球数据交换连接的需求进一步推动了这一迁移趋势。

占比最大的地区：

预计亚太地区将在预测期内占据最大的市场份额。这主要得益于香港、新加坡、东京和雪梨等主要金融中心交易生态系统的快速现代化。在电子交易监管的不断完善和跨境交易所互联互通日益增强的推动下，该地区的金融机构正在加速采用先进的流动性路由平台。买方和卖方机构演算法交易活动的涌入进一步刺激了市场需求。此外，散户参与度的提高和多资产平台的成长将在整个预测期内巩固该地区的市场主导地位。

年复合成长率最高的地区：

在预测期内，北美预计将呈现最高的复合年增长率，这主要得益于机构对低延迟基础设施的大力投资以及演算法执行技术的持续创新。在交易所之间激烈竞争以及人工智慧增强型路由模型日益普及的推动下，该地区拥有技术成熟的生态系统。此外，监管机构对执行透明度的重视也促进了先进路由解决方案的广泛应用。美国股票、衍生性商品和数位资产的充足流动性也推动了下一代流动性路由引擎的扩张。

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目录

第一章执行摘要

第二章 前言

  • 概述
  • 相关利益者
  • 调查范围
  • 调查方法
    • 资料探勘
    • 数据分析
    • 数据检验
    • 研究途径
  • 研究材料
    • 原始研究资料
    • 次级研究资讯来源
    • 先决条件

第三章 市场趋势分析

  • 介绍
  • 司机
  • 抑制因素
  • 机会
  • 威胁
  • 应用分析
  • 终端用户分析
  • 新兴市场
  • 新冠疫情的影响

第四章 波特五力分析

  • 供应商的议价能力
  • 买方的议价能力
  • 替代品的威胁
  • 新进入者的威胁
  • 竞争对手之间的竞争

5. 全球流动性路由引擎市场（按组件划分）

  • 介绍
  • 路由演算法
  • 聚合引擎
  • 执行管理系统
  • 市场连接 API
  • 风险与合规模块
  • 报告和分析仪表板

6. 全球流动性路由引擎市场依部署模式划分

  • 介绍
  • 云端部署
  • 本地部署系统
  • 混合部署
  • 共同部署的交易基础设施

7. 全球流动性路由引擎市场（按应用划分）

  • 介绍
  • 数位银行的流动性自动化
  • 外汇和加密货币市场执行
  • 支付优化
  • 精简的财务管理
  • 高频交易路由
  • 做市优化

8. 全球流动性路由引擎市场（依最终用户划分）

  • 介绍
  • 新银行
  • 金融科技交易员
  • 支付处理商
  • 证券公司
  • 财务团队

9. 全球流动性路由引擎市场（按地区划分）

  • 介绍
  • 北美洲
    • 美国
    • 加拿大
    • 墨西哥
  • 欧洲
    • 德国
    • 英国
    • 义大利
    • 法国
    • 西班牙
    • 其他欧洲
  • 亚太地区
    • 日本
    • 中国
    • 印度
    • 澳洲
    • 纽西兰
    • 韩国
    • 亚太其他地区
  • 南美洲
    • 阿根廷
    • 巴西
    • 智利
    • 南美洲其他地区
  • 中东和非洲
    • 沙乌地阿拉伯
    • 阿拉伯聯合大公国
    • 卡达
    • 南非
    • 其他中东和非洲地区

第十章：重大进展

  • 协议、伙伴关係、合作和合资企业
  • 收购与併购
  • 新产品上市
  • 业务拓展
  • 其他关键策略

第十一章 企业概况

  • FlexTrade Systems
  • Broadridge Financial Solutions
  • OneZero Financial Systems
  • PrimeXM
  • B2BROKER
  • X Open Hub
  • smartTrade Technologies
  • 1inch
  • Matcha（0x）
  • ParaSwap
  • CoW Swap
  • ODOS
  • OpenOcean
  • Fennech Financial
  • NYFIX Order Routing Network
Product Code: SMRC32459

According to Stratistics MRC, the Global Liquidity-Routing Engines Market is accounted for $19.5 billion in 2025 and is expected to reach $38.2 billion by 2032 growing at a CAGR of 10.1% during the forecast period. Liquidity-routing engines are algorithmic systems used in financial markets to optimize trade execution by directing orders across multiple liquidity pools. These engines analyze market depth, transaction costs, and latency to ensure best-price execution for equities, currencies, or digital assets. By dynamically routing trades to exchanges, dark pools, or decentralized platforms, they enhance efficiency and reduce slippage. Widely adopted in algorithmic trading and fintech, liquidity-routing engines support institutional investors and brokers in maximizing returns and minimizing risks.

According to CFA Institute research, liquidity-routing algorithms are increasingly adopted by institutional traders to minimize slippage, optimize execution, and ensure access to fragmented global liquidity pools.

Market Dynamics:

Driver:

Increasing shift to multi-venue trading

The ongoing migration toward multi-venue execution, the Liquidity-Routing Engines Market is experiencing robust demand for systems capable of orchestrating fragmented liquidity pools in real time. Spurred by regulatory pushes for best-execution transparency and the expansion of alternative trading systems, institutions are increasingly relying on adaptive routing frameworks to capture optimal price improvement. Moreover, the proliferation of dark pools and global electronic communication networks stimulates the need for high-precision routing tools that can seamlessly consolidate pricing signals across diverse liquidity venues.

Restraint:

Latency challenges in high-speed routing

Latency-driven performance bottlenecks remain a critical restraint, as even millisecond-scale delays can distort price discovery and degrade execution quality in ultra-low-latency environments. Burdened by infrastructure inconsistencies, firms often struggle to synchronize routing workflows across geographically dispersed venues, amplifying the risk of slippage. Additionally, the escalating volume of order-flow data increases processing pressure, forcing institutions to maintain costly high-performance computing stacks. These latency constraints limit scalability and hinder the ability of liquidity-routing engines to sustain deterministic performance under volatile market conditions.

Opportunity:

Rise of AI-optimized liquidity aggregation

The accelerating adoption of AI-enhanced liquidity aggregation presents a substantial growth avenue, enabling market participants to transition from rules-based routing toward predictive and autonomous execution frameworks. Powered by machine-learning-driven signal scoring, these engines dynamically evaluate micro-market conditions to optimize order sequencing. Moreover, AI-infused price-path modeling strengthens cross-venue allocation precision, improving fill rates and reducing execution drag. This shift opens opportunities for vendors offering explainable AI models, real-time learning architectures, and adaptive analytics tailored to fragmented liquidity ecosystems.

Threat:

Market volatility disrupting order execution

High-frequency volatility spikes pose a significant threat by destabilizing execution pipelines and impairing routing accuracy within highly dynamic price environments. Intensified market turbulence can trigger liquidity evaporation, widening spreads and reducing the reliability of venue-level order books. Furthermore, rapid intraday reversals pressure routing engines to recalculate paths instantly, increasing the probability of execution errors. These volatility-driven disruptions elevate operational risk, potentially reducing user confidence in automated routing solutions during stress-test market scenarios.

Covid-19 Impact:

COVID-19 reshaped liquidity-routing dynamics by accelerating digitization and increasing market fragmentation, as trading volumes surged across asset classes during heightened uncertainty. The pandemic catalyzed rapid modernization of electronic trading stacks, strengthening institutional demand for real-time routing intelligence. However, extreme volatility periods tested routing precision and exposed infrastructure gaps in many firms. Post-pandemic, market participants adopted more resilient multi-venue strategies and invested in cloud-native routing solutions, creating sustained momentum for advanced, algorithmically adaptive liquidity-routing engines.

The routing algorithms segment is expected to be the largest during the forecast period

The routing algorithms segment is expected to account for the largest market share during the forecast period, driven by rising adoption of intelligent path-selection frameworks that enhance order-execution quality across fragmented liquidity venues. Fueled by demand for real-time price optimization and the expansion of multi-asset electronic trading, algorithmic routing modules have become core infrastructure for institutional traders. These systems' ability to evaluate venue performance, historical fill rates, and micro-structure signals strengthens their market leadership. The push toward smart-order routing standardization further consolidates this segment's dominance.

The cloud deployment segment is expected to have the highest CAGR during the forecast period

Over the forecast period, the cloud deployment segment is predicted to witness the highest growth rate, propelled by expanding demand for elastic compute capacity to support complex, high-frequency routing workflows. Spurred by lower infrastructure overheads and rapid scalability, cloud-native routing engines enable firms to accelerate model updates and reduce latency variability. Additionally, enhanced cybersecurity frameworks and managed-services architectures are encouraging regulated entities to shift execution workloads to cloud environments. This transition is further amplified by the need for continuous analytics and global venue connectivity.

Region with largest share:

During the forecast period, the Asia Pacific region is expected to hold the largest market share, attributed to the rapid modernization of trading ecosystems across major financial hubs such as Hong Kong, Singapore, Tokyo, and Sydney. Fueled by the expansion of electronic trading regulations and cross-border venue connectivity, regional institutions are accelerating adoption of advanced liquidity-routing platforms. The influx of algorithmic trading activity from buy-side and sell-side players further intensifies demand. Moreover, increasing retail participation and multi-asset platform growth strengthen the region's dominance throughout the forecast horizon.

Region with highest CAGR:

Over the forecast period, the North America region is anticipated to exhibit the highest CAGR associated with strong institutional investment in low-latency infrastructure and continuous innovation in algorithmic execution technologies. Motivated by aggressive competition among trading venues and rising adoption of AI-augmented routing models, the region benefits from a technologically mature ecosystem. Additionally, regulatory emphasis on execution transparency supports broader deployment of advanced routing solutions. High liquidity depth across U.S. equities, derivatives, and digital assets also accelerates the expansion of next-generation liquidity-routing engines.

Key players in the market

Some of the key players in Liquidity-Routing Engines Market include FlexTrade Systems, Broadridge Financial Solutions, OneZero Financial Systems, PrimeXM, B2BROKER, X Open Hub, smartTrade Technologies, 1inch, Matcha (0x), ParaSwap, CoW Swap, ODOS, OpenOcean, Fennech Financial, and NYFIX Order Routing Network.

Key Developments:

In October 2025, 1inch launched its "Fusion 2.0" upgrade, introducing a novel time-weighted order routing algorithm that dynamically splits large orders across decentralized exchanges (DEXs) to minimize price impact and maximize fill rates for institutional traders.

In September 2025, FlexTrade Systems expanded its multi-asset trading suite with the AI-Powered Liquidity Sense module, which uses real-time market microstructure data to predict liquidity shortfalls and automatically reroute orders to the most resilient venues, mitigating execution risk.

In March 2025, Broadridge Financial Solutions launched its new Distributed Ledger Repo (DLR) smart order router, designed to optimize the allocation of repurchase agreement transactions across both traditional and blockchain-based settlement networks for enhanced capital efficiency.

Components Covered:

  • Routing Algorithms
  • Aggregation Engines
  • Execution Management Systems
  • Market Connectivity APIs
  • Risk & Compliance Modules
  • Reporting & Analytics Dashboards

Deployment Modes Covered:

  • Cloud Deployment
  • On-Premise Systems
  • Hybrid Deployment
  • Co-Located Trading Infrastructure

Applications Covered:

  • Digital Banking Liquidity Automation
  • FX & Crypto Market Execution
  • Payment Settlement Optimization
  • Treasury Management Efficiency
  • High-Frequency Trade Routing
  • Market-Making Optimization

End Users Covered:

  • Neo-Banks
  • Fintech Traders
  • Payment Processors
  • Brokerages
  • Treasury Teams

Regions Covered:

  • North America
    • US
    • Canada
    • Mexico
  • Europe
    • Germany
    • UK
    • Italy
    • France
    • Spain
    • Rest of Europe
  • Asia Pacific
    • Japan
    • China
    • India
    • Australia
    • New Zealand
    • South Korea
    • Rest of Asia Pacific
  • South America
    • Argentina
    • Brazil
    • Chile
    • Rest of South America
  • Middle East & Africa
    • Saudi Arabia
    • UAE
    • Qatar
    • South Africa
    • Rest of Middle East & Africa

What our report offers:

  • Market share assessments for the regional and country-level segments
  • Strategic recommendations for the new entrants
  • Covers Market data for the years 2024, 2025, 2026, 2028, and 2032
  • Market Trends (Drivers, Constraints, Opportunities, Threats, Challenges, Investment Opportunities, and recommendations)
  • Strategic recommendations in key business segments based on the market estimations
  • Competitive landscaping mapping the key common trends
  • Company profiling with detailed strategies, financials, and recent developments
  • Supply chain trends mapping the latest technological advancements

Free Customization Offerings:

All the customers of this report will be entitled to receive one of the following free customization options:

  • Company Profiling
    • Comprehensive profiling of additional market players (up to 3)
    • SWOT Analysis of key players (up to 3)
  • Regional Segmentation
    • Market estimations, Forecasts and CAGR of any prominent country as per the client's interest (Note: Depends on feasibility check)
  • Competitive Benchmarking
    • Benchmarking of key players based on product portfolio, geographical presence, and strategic alliances

Table of Contents

1 Executive Summary

2 Preface

  • 2.1 Abstract
  • 2.2 Stake Holders
  • 2.3 Research Scope
  • 2.4 Research Methodology
    • 2.4.1 Data Mining
    • 2.4.2 Data Analysis
    • 2.4.3 Data Validation
    • 2.4.4 Research Approach
  • 2.5 Research Sources
    • 2.5.1 Primary Research Sources
    • 2.5.2 Secondary Research Sources
    • 2.5.3 Assumptions

3 Market Trend Analysis

  • 3.1 Introduction
  • 3.2 Drivers
  • 3.3 Restraints
  • 3.4 Opportunities
  • 3.5 Threats
  • 3.6 Application Analysis
  • 3.7 End User Analysis
  • 3.8 Emerging Markets
  • 3.9 Impact of Covid-19

4 Porters Five Force Analysis

  • 4.1 Bargaining power of suppliers
  • 4.2 Bargaining power of buyers
  • 4.3 Threat of substitutes
  • 4.4 Threat of new entrants
  • 4.5 Competitive rivalry

5 Global Liquidity-Routing Engines Market, By Component

  • 5.1 Introduction
  • 5.2 Routing Algorithms
  • 5.3 Aggregation Engines
  • 5.4 Execution Management Systems
  • 5.5 Market Connectivity APIs
  • 5.6 Risk & Compliance Modules
  • 5.7 Reporting & Analytics Dashboards

6 Global Liquidity-Routing Engines Market, By Deployment Mode

  • 6.1 Introduction
  • 6.2 Cloud Deployment
  • 6.3 On-Premise Systems
  • 6.4 Hybrid Deployment
  • 6.5 Co-Located Trading Infrastructure

7 Global Liquidity-Routing Engines Market, By Application

  • 7.1 Introduction
  • 7.2 Digital Banking Liquidity Automation
  • 7.3 FX & Crypto Market Execution
  • 7.4 Payment Settlement Optimization
  • 7.5 Treasury Management Efficiency
  • 7.6 High-Frequency Trade Routing
  • 7.7 Market-Making Optimization

8 Global Liquidity-Routing Engines Market, By End User

  • 8.1 Introduction
  • 8.2 Neo-Banks
  • 8.3 Fintech Traders
  • 8.4 Payment Processors
  • 8.5 Brokerages
  • 8.6 Treasury Teams

9 Global Liquidity-Routing Engines Market, By Geography

  • 9.1 Introduction
  • 9.2 North America
    • 9.2.1 US
    • 9.2.2 Canada
    • 9.2.3 Mexico
  • 9.3 Europe
    • 9.3.1 Germany
    • 9.3.2 UK
    • 9.3.3 Italy
    • 9.3.4 France
    • 9.3.5 Spain
    • 9.3.6 Rest of Europe
  • 9.4 Asia Pacific
    • 9.4.1 Japan
    • 9.4.2 China
    • 9.4.3 India
    • 9.4.4 Australia
    • 9.4.5 New Zealand
    • 9.4.6 South Korea
    • 9.4.7 Rest of Asia Pacific
  • 9.5 South America
    • 9.5.1 Argentina
    • 9.5.2 Brazil
    • 9.5.3 Chile
    • 9.5.4 Rest of South America
  • 9.6 Middle East & Africa
    • 9.6.1 Saudi Arabia
    • 9.6.2 UAE
    • 9.6.3 Qatar
    • 9.6.4 South Africa
    • 9.6.5 Rest of Middle East & Africa

10 Key Developments

  • 10.1 Agreements, Partnerships, Collaborations and Joint Ventures
  • 10.2 Acquisitions & Mergers
  • 10.3 New Product Launch
  • 10.4 Expansions
  • 10.5 Other Key Strategies

11 Company Profiling

  • 11.1 FlexTrade Systems
  • 11.2 Broadridge Financial Solutions
  • 11.3 OneZero Financial Systems
  • 11.4 PrimeXM
  • 11.5 B2BROKER
  • 11.6 X Open Hub
  • 11.7 smartTrade Technologies
  • 11.8 1inch
  • 11.9 Matcha (0x)
  • 11.10 ParaSwap
  • 11.11 CoW Swap
  • 11.12 ODOS
  • 11.13 OpenOcean
  • 11.14 Fennech Financial
  • 11.15 NYFIX Order Routing Network

List of Tables

  • Table 1 Global Liquidity-Routing Engines Market Outlook, By Region (2024-2032) ($MN)
  • Table 2 Global Liquidity-Routing Engines Market Outlook, By Component (2024-2032) ($MN)
  • Table 3 Global Liquidity-Routing Engines Market Outlook, By Routing Algorithms (2024-2032) ($MN)
  • Table 4 Global Liquidity-Routing Engines Market Outlook, By Aggregation Engines (2024-2032) ($MN)
  • Table 5 Global Liquidity-Routing Engines Market Outlook, By Execution Management Systems (2024-2032) ($MN)
  • Table 6 Global Liquidity-Routing Engines Market Outlook, By Market Connectivity APIs (2024-2032) ($MN)
  • Table 7 Global Liquidity-Routing Engines Market Outlook, By Risk & Compliance Modules (2024-2032) ($MN)
  • Table 8 Global Liquidity-Routing Engines Market Outlook, By Reporting & Analytics Dashboards (2024-2032) ($MN)
  • Table 9 Global Liquidity-Routing Engines Market Outlook, By Deployment Mode (2024-2032) ($MN)
  • Table 10 Global Liquidity-Routing Engines Market Outlook, By Cloud Deployment (2024-2032) ($MN)
  • Table 11 Global Liquidity-Routing Engines Market Outlook, By On-Premise Systems (2024-2032) ($MN)
  • Table 12 Global Liquidity-Routing Engines Market Outlook, By Hybrid Deployment (2024-2032) ($MN)
  • Table 13 Global Liquidity-Routing Engines Market Outlook, By Co-Located Trading Infrastructure (2024-2032) ($MN)
  • Table 14 Global Liquidity-Routing Engines Market Outlook, By Application (2024-2032) ($MN)
  • Table 15 Global Liquidity-Routing Engines Market Outlook, By Digital Banking Liquidity Automation (2024-2032) ($MN)
  • Table 16 Global Liquidity-Routing Engines Market Outlook, By FX & Crypto Market Execution (2024-2032) ($MN)
  • Table 17 Global Liquidity-Routing Engines Market Outlook, By Payment Settlement Optimization (2024-2032) ($MN)
  • Table 18 Global Liquidity-Routing Engines Market Outlook, By Treasury Management Efficiency (2024-2032) ($MN)
  • Table 19 Global Liquidity-Routing Engines Market Outlook, By High-Frequency Trade Routing (2024-2032) ($MN)
  • Table 20 Global Liquidity-Routing Engines Market Outlook, By Market-Making Optimization (2024-2032) ($MN)
  • Table 21 Global Liquidity-Routing Engines Market Outlook, By End User (2024-2032) ($MN)
  • Table 22 Global Liquidity-Routing Engines Market Outlook, By Neo-Banks (2024-2032) ($MN)
  • Table 23 Global Liquidity-Routing Engines Market Outlook, By Fintech Traders (2024-2032) ($MN)
  • Table 24 Global Liquidity-Routing Engines Market Outlook, By Payment Processors (2024-2032) ($MN)
  • Table 25 Global Liquidity-Routing Engines Market Outlook, By Brokerages (2024-2032) ($MN)
  • Table 26 Global Liquidity-Routing Engines Market Outlook, By Treasury Teams (2024-2032) ($MN)

Note: Tables for North America, Europe, APAC, South America, and Middle East & Africa Regions are also represented in the same manner as above.