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市場調查報告書
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1880414

流動性路由引擎市場預測至2032年：按組件、部署模式、應用、最終用戶和地區分類的全球分析

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個工作天內

價格

根據 Stratistics MRC 的一項研究，預計到 2025 年，全球流動性路由引擎市場規模將達到 195 億美元，到 2032 年將達到 382 億美元，預測期內複合年成長率為 10.1%。

流動性路由引擎是一種演算法系統，它透過在金融市場中將訂單路由到多個流動性池來最佳化交易執行。這些引擎會分析市場深度、交易成本和延遲，以確保股票、貨幣和數位資產交易的最佳執行價格。它們會將交易動態路由到交易所、暗池和去中心化平台，從而提高效率並減少滑點。流動性路由引擎在演算法交易和金融科技領域廣泛應用，幫助機構投資者和仲介實現收益最大化和風險最小化。

根據 CFA 協會的一項調查，機構投資者擴大採用流動性路由演算法來最大限度地減少滑點、最佳化執行並確保獲得去中心化的全球流動性池。

加速向多場所交易的過渡

隨著多場所交易模式的持續發展，流動性路由引擎市場對能夠即時整合分散流動性池的系統需求強勁。在監管機構對最佳交易透明度的要求以及另類交易系統激增的推動下，機構投資者越來越依賴自適應路由框架來獲得最佳價格最佳化。此外，暗池的激增和全球電子通訊網路的擴展也促使人們需要能夠無縫整合不同流動性市場價格訊號的高精度路由工具。

高速路由中的延遲挑戰

延遲導致的效能瓶頸仍然是一個重要的阻礙因素，即使是毫秒級的延遲也會扭曲價格發現，並在超低延遲環境下降低執行品質。基礎設施不一致的公司往往難以同步地理位置分散的交易所之間的路由工作流程，從而加劇滑點風險。此外，訂單流資料的激增增加了處理負載，迫使機構維護高成本的高效能運算堆疊。這些延遲限制了可擴展性，並阻礙了流動性路由引擎在市場波動的情況下保持確定性效能的能力。

人工智慧最佳化流動性聚合的興起

人工智慧增強型流動性聚合技術的加速應用代表著一條重要的成長路徑，使市場參與企業能夠從基於規則的路由轉向預測性和自主執行框架。這些引擎由機器學習訊號評分驅動，能夠動態評估微觀市場狀況並最佳化訂單排序。此外，人工智慧賦能的價格路徑建模提高了跨多個交易所的分配精度，從而提升成交率並降低執行延遲。這種轉變為提供可解釋人工智慧模型、即時學習架構以及針對分散的流動性生態系統量身定做的自適應分析的供應商創造了機會。

市場波動阻礙訂單執行

在高度動態的價格環境下，高頻波動尖峰對交易執行流程的穩定性和路由準確性構成重大威脅。加劇的市場動盪會導致流動性枯竭，擴大價差，並降低交易所層級訂單簿的可靠性。此外，日內價格的突然反轉會迫使路由引擎即時重新計算路徑，從而增加執行錯誤的機率。這些由波動引起的干擾會增加營運風險，並可能在壓力測試市場場景下削弱使用者對自動化路由解決方案的信心。

新冠疫情的影響：

新冠疫情重塑了流動性路由的動態，在不不確定性加劇的情況下，各類資產的交易量激增，推動了數位化的加速和市場碎片化的加劇。疫情加速了電子交易基礎設施的現代化，並增強了機構對即時路由智慧的需求。然而，極端波動時期考驗了路由的準確性，並暴露了許多公司的基礎設施漏洞。疫情後，市場參與企業採取了更具彈性的多場所策略，並投資於雲端原生路由解決方案，從而持續推動了對先進的演算法自適應流動性路由引擎的需求。

預計在預測期內，路由演算法細分市場將佔據最大的市場佔有率。

預計在預測期內，路由演算法細分市場將佔據最大的市場佔有率，這主要得益於智慧路由框架的日益普及，這些框架能夠提升分散式流動性交易所的訂單執行品質。在即時價格最佳化需求和多資產電子交易擴張的推動下，演算法路由模組已成為機構交易的核心基礎設施。這些系統能夠評估交易所績效、歷史成交率和微觀結構訊號，從而鞏固其市場主導地位。智慧訂單路由標準化的趨勢進一步強化了其在該領域的統治地位。

預計在預測期內，雲端部署領域將實現最高的複合年成長率。

預計在預測期內，雲端部署領域將實現最高成長率，這主要得益於對彈性運算能力日益成長的需求，以支援複雜、高頻的路由工作流程。雲端原生路由引擎具有降低基礎設施成本和快速擴展的優勢，能夠幫助企業加速模型更新並降低延遲波動。此外，不斷增強的網路安全框架和託管服務架構也促使受監管企業將其執行工作負載遷移到雲端環境。持續分析和全球數據交換連接的需求進一步推動了這一遷移趨勢。

佔比最大的地區：

預計亞太地區將在預測期內佔據最大的市場佔有率。這主要得益於香港、新加坡、東京和雪梨等主要金融中心交易生態系統的快速現代化。在電子交易監管的不斷完善和跨境交易所互聯互通日益增強的推動下，該地區的金融機構正在加速採用先進的流動性路由平台。買方和賣方機構演算法交易活動的湧入進一步刺激了市場需求。此外，散戶參與度的提高和多資產平台的成長將在整個預測期內鞏固該地區的市場主導地位。

年複合成長率最高的地區：

在預測期內，北美預計將呈現最高的複合年成長率，這主要得益於機構對低延遲基礎設施的大力投資以及演算法執行技術的持續創新。在交易所之間激烈競爭以及人工智慧增強型路由模型日益普及的推動下，該地區擁有技術成熟的生態系統。此外，監管機構對執行透明度的重視也促進了先進路由解決方案的廣泛應用。美國股票、衍生性商品和數位資產的充足流動性也推動了下一代流動性路由引擎的擴張。

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目錄

第1章執行摘要

第2章 前言

  • 概述
  • 相關利益者
  • 調查範圍
  • 調查方法
    • 資料探勘
    • 數據分析
    • 數據檢驗
    • 研究途徑
  • 研究材料
    • 原始研究資料
    • 次級研究資訊來源
    • 先決條件

第3章 市場趨勢分析

  • 介紹
  • 促進要素
  • 抑制因素
  • 機會
  • 威脅
  • 應用分析
  • 終端用戶分析
  • 新興市場
  • 新冠疫情的影響

第4章 波特五力分析

  • 供應商的議價能力
  • 買方的議價能力
  • 替代品的威脅
  • 新進入者的威脅
  • 競爭對手之間的競爭

5. 全球流動性路由引擎市場（按組件分類）

  • 介紹
  • 路由演算法
  • 聚合引擎
  • 執行管理系統
  • 市場連接 API
  • 風險與合規模組
  • 報告和分析儀表板

6. 全球流動性路由引擎市場依部署模式分類

  • 介紹
  • 雲端部署
  • 本地部署系統
  • 混合部署
  • 共同部署的交易基礎設施

7. 全球流動性路由引擎市場（按應用分類）

  • 介紹
  • 數位銀行的流動性自動化
  • 外匯和加密貨幣市場執行
  • 支付最佳化
  • 精簡的財務管理
  • 高頻交易路由
  • 做市最佳化

8. 全球流動性路由引擎市場（依最終用戶分類）

  • 介紹
  • 新銀行
  • 金融科技交易員
  • 支付處理商
  • 證券公司
  • 財務團隊

9. 全球流動性路由引擎市場（按地區分類）

  • 介紹
  • 北美洲
    • 美國
    • 加拿大
    • 墨西哥
  • 歐洲
    • 德國
    • 英國
    • 義大利
    • 法國
    • 西班牙
    • 其他歐洲
  • 亞太地區
    • 日本
    • 中國
    • 印度
    • 澳洲
    • 紐西蘭
    • 韓國
    • 亞太其他地區
  • 南美洲
    • 阿根廷
    • 巴西
    • 智利
    • 南美洲其他地區
  • 中東和非洲
    • 沙烏地阿拉伯
    • 阿拉伯聯合大公國
    • 卡達
    • 南非
    • 其他中東和非洲地區

第10章：重大進展

  • 協議、夥伴關係、合作和合資企業
  • 收購與併購
  • 新產品上市
  • 業務拓展
  • 其他關鍵策略

第11章 企業概況

  • 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.