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市场调查报告书
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BFSI 市场的机器人流程自动化 - 全球产业规模、份额、趋势、机会和预测，按类型、部署、组织、按应用、地区、竞争细分，2018-2028 年

Robotic Process Automation in BFSI Market - Global Industry Size, Share, Trends, Opportunity, and Forecast, Segmented By Type, By Deployment, By Organization, By Application, By Region, By Competition, 2018-2028
出版日期: | 出版商: TechSci Research | 英文 190 Pages | 商品交期: 2-3个工作天内

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简介目录

BFSI 市场的全球机器人流程自动化市场价值到 2022 年将达到 8.72 亿美元，预计在预测期内将强劲增长，到 2028 年CAGR为38%。银行、金融服务领域的全球机器人流程自动化(RPA ) 市场和保险（BFSI）产业正在经历深刻的转型。 RPA 技术透过自动执行基于规则的重复任务、提高效率、降低成本和提高准确性，正在彻底改变金融机构的运作方式。在资料准确性和合规性至关重要的行业中，RPA 在简化后台营运、客户服务和监管报告方面发挥关键作用。透过自动化资料输入、帐户对帐和诈欺侦测等流程，BFSI 组织可以将人力资源转向更具策略性、增值的活动。

此外，RPA 还可以提高营运敏捷性，这是快速发展的金融格局中的关键因素。它使机构能够迅速适应市场变化、客户需求和监管更新，从而获得竞争优势。此外，RPA 全天候工作的能力可确保服务不间断，促进即时交易处理和客户支援。

此外，BFSI 行业越来越多地采用 RPA 进行合规和风险管理。 RPA 机器人可以严格遵循监管协议，降低不合规和相关处罚的风险。总体而言，随着金融机构认识到自动化在简化营运、增强客户体验并确保日益动态和数据驱动的行业中遵守监管方面的变革潜力，BFSI 市场的全球 RPA 正在强劲增长。

市场概况
预测期 2024-2028
2022 年市场规模 8.72 亿美元
2028 年市场规模 60.769 亿美元
2023-2028 年CAGR 38%
成长最快的细分市场 云
最大的市场 北美洲

主要市场驱动因素

目录

第 1 章：产品概述

  • 市场定义
  • 市场范围
    • 涵盖的市场
    • 考虑学习的年份
    • 主要市场区隔

第 2 章：研究方法

  • 研究目的
  • 基线方法
  • 范围的製定
  • 假设和限制
  • 研究来源
    • 二次研究
    • 初步研究
  • 市场研究方法
    • 自下而上的方法
    • 自上而下的方法
  • 计算市场规模和市场份额所遵循的方法
  • 预测方法
    • 数据三角测量与验证

第 3 章：执行摘要

第 4 章：COVID-19 对 BFSI 市场全球机器人流程自动化的影响

第 5 章：客户之声

第 6 章：BFSI 市场中的全球机器人流程自动化概述

第 7 章：BFSI 市场展望中的全球机器人流程自动化

  • 市场规模及预测
    • 按价值
  • 市占率及预测
    • 按类型（软体、服务）
    • 按部署（云端、本机）
    • 按组织（中小企业、大型企业）
    • 按应用（银行、金融服务和保险）
    • 按地区（北美、欧洲、南美、中东和非洲、亚太地区）
  • 按公司划分 (2022)
  • 市场地图

第 8 章：北美机器人流程自动化 BFSI 市场展望

  • 市场规模及预测
    • 按价值
  • 市占率及预测
    • 按类型
    • 按部署
    • 按组织
    • 按应用
    • 按国家/地区
  • 北美：国家分析
    • 美国
    • 加拿大
    • 墨西哥

第 9 章：BFSI 中的欧洲机器人流程自动化市场展望

  • 市场规模及预测
    • 按价值
  • 市占率及预测
    • 按类型
    • 按部署
    • 按组织
    • 按应用
    • 按国家/地区
  • 欧洲：国家分析
    • 德国
    • 法国
    • 英国
    • 义大利
    • 西班牙
    • 比利时

第 10 章：BFSI 市场展望中的南美机器人流程自动化

  • 市场规模及预测
    • 按价值
  • 市占率及预测
    • 按类型
    • 按部署
    • 按组织
    • 按应用
    • 按国家/地区
  • 南美洲：国家分析
    • 巴西
    • 哥伦比亚
    • 阿根廷
    • 智利
    • 秘鲁

第 11 章：BFSI 市场展望中的中东和非洲机器人流程自动化

  • 市场规模及预测
    • 按价值
  • 市占率及预测
    • 按类型
    • 按部署
    • 按组织
    • 按应用
    • 按国家/地区
  • 中东和非洲：国家分析
    • 沙乌地阿拉伯
    • 阿联酋
    • 南非
    • 土耳其
    • 以色列

第 12 章：BFSI 市场展望中的亚太地区机器人流程自动化

  • 市场规模及预测
    • 按类型
    • 按部署
    • 按组织
    • 按应用
    • 按国家/地区
  • 亚太地区：国家分析
    • 中国机器人流程自动化亮相BFSI
    • 印度 BFSI 机器人流程自动化
    • 日本 BFSI 机器人流程自动化
    • 韩国机器人流程自动化参加 BFSI
    • 澳洲 BFSI 机器人流程自动化
    • 印尼BFSI 机器人流程自动化
    • 越南机器人流程自动化在BFSI

第 13 章：市场动态

  • 司机
  • 挑战

第 14 章：市场趋势与发展

第 15 章：公司简介

  • 蚂蚁工场
    • Business Overview
    • Key Revenue and Financials
    • Recent Developments
    • Key Personnel/Key Contact Person
    • Key Product/Services Offered
  • 源讯公司
    • Business Overview
    • Key Revenue and Financials
    • Recent Developments
    • Key Personnel/Key Contact Person
    • Key Product/Services Offered
  • 自动化无所不在，公司
    • Business Overview
    • Key Revenue and Financials
    • Recent Developments
    • Key Personnel/Key Contact Person
    • Key Product/Services Offered
  • 蓝棱镜有限公司
    • Business Overview
    • Key Revenue and Financials
    • Recent Developments
    • Key Personnel/Key Contact Person
    • Key Product/Services Offered
  • EdgeVerve 系统有限公司
    • Business Overview
    • Key Revenue and Financials
    • Recent Developments
    • Key Personnel/Key Contact Person
    • Key Product/Services Offered
  • 菲亚特动力科技软体
    • Business Overview
    • Key Revenue and Financials
    • Recent Developments
    • Key Personnel/Key Contact Person
    • Key Product/Services Offered
  • 国际商业机器公司
    • Business Overview
    • Key Revenue and Financials
    • Recent Developments
    • Key Personnel/Key Contact Person
    • Key Product/Services Offered
  • 科法克斯公司
    • Business Overview
    • Key Revenue and Financials
    • Recent Developments
    • Key Personnel/Key Contact Person
    • Key Product/Services Offered
  • 微软（软体汽车）
    • Business Overview
    • Key Revenue and Financials
    • Recent Developments
    • Key Personnel/Key Contact Person
    • Key Product/Services Offered
  • 好的
    • Business Overview
    • Key Revenue and Financials
    • Recent Developments
    • Key Personnel/Key Contact Person
    • Key Product/Services Offered
  • Nintex 英国有限公司（Kryon Systems）
    • Business Overview
    • Key Revenue and Financials
    • Recent Developments
    • Key Personnel/Key Contact Person
    • Key Product/Services Offered
  • 佩加系统公司
    • Business Overview
    • Key Revenue and Financials
    • Recent Developments
    • Key Personnel/Key Contact Person
    • Key Product/Services Offered
  • 甫瀚咨询公司
    • Business Overview
    • Key Revenue and Financials
    • Recent Developments
    • Key Personnel/Key Contact Person
    • Key Product/Services Offered
  • UiPath
    • Business Overview
    • Key Revenue and Financials
    • Recent Developments
    • Key Personnel/Key Contact Person
    • Key Product/Services Offered

第 16 章：策略建议

第 17 章：关于我们与免责声明

简介目录
Product Code: 16853

Global Robotic Process Automation in BFSI Market has valued at USD 872 Million in 2022 and is anticipated to project robust growth in the forecast period with a CAGR of 38% through 2028. The Global Robotic Process Automation (RPA) market within the Banking, Financial Services, and Insurance (BFSI) sector is undergoing a profound transformation. RPA technology is revolutionizing how financial institutions operate by automating repetitive, rule-based tasks, enabling efficiency gains, cost reduction, and enhanced accuracy. In an industry where data accuracy and compliance are paramount, RPA plays a pivotal role in streamlining back-office operations, customer service, and regulatory reporting. By automating processes such as data entry, account reconciliation, and fraud detection, BFSI organizations can redirect human resources towards more strategic, value-added activities.

Moreover, RPA fosters operational agility, a critical factor in the rapidly evolving financial landscape. It empowers institutions to adapt swiftly to market changes, customer demands, and regulatory updates, thereby gaining a competitive edge. Additionally, RPA's ability to work around the clock ensures uninterrupted service, facilitating real-time transaction processing and customer support.

Furthermore, the BFSI sector is increasingly embracing RPA for compliance and risk management. RPA bots can meticulously follow regulatory protocols, reducing the risk of non-compliance and associated penalties. Overall, the Global RPA in BFSI market is witnessing robust growth as financial institutions recognize the transformative potential of automation to streamline operations, enhance customer experiences, and ensure regulatory adherence in an increasingly dynamic and data-driven industry.

Market Overview
Forecast Period2024-2028
Market Size 2022USD 872 Million
Market Size 2028USD 6076.9 million
CAGR 2023-202838%
Fastest Growing SegmentCloud
Largest MarketNorth America

Key Market Drivers

Enhanced Operational Efficiency

AI-driven Robotic Process Automation (RPA) is transforming the Banking, Financial Services, and Insurance (BFSI) sector by automating repetitive and time-consuming tasks, thereby enabling organizations to focus on more complex and critical areas. By leveraging AI algorithms, RPA systems can analyze large volumes of transaction data, identify patterns, and automate routine processes. This technological advancement brings about significant improvements in operational efficiency and accelerates workflows within the BFSI domain. One of the key benefits of AI-driven RPA in the BFSI sector is its ability to automate tasks such as data entry, account reconciliation, and fraud detection. By automating these processes, financial institutions can free up human resources to concentrate on more strategic tasks, while also reducing the potential for human error. This not only enhances productivity but also ensures greater accuracy in critical financial operations. Furthermore, AI-driven RPA systems continuously learn from their interactions, allowing them to adapt and improve over time. This means that as the technology interacts with various data sources and performs tasks, it becomes more proficient and effective. By constantly learning and updating its processes, AI-driven RPA ensures that organizations can stay up to date with the latest industry trends and regulations, thereby maintaining compliance and efficiency.

The ability of AI-driven RPA to analyze large volumes of transaction data is particularly valuable in the BFSI sector. By leveraging AI algorithms, RPA systems can identify patterns and anomalies in financial transactions, enabling organizations to detect potential fraud or suspicious activities in real-time. This proactive approach to fraud detection helps financial institutions mitigate risks and protect their customers' assets. In addition to fraud detection, AI-driven RPA can also assist in regulatory compliance. By automating processes related to compliance monitoring and reporting, financial institutions can ensure that they adhere to the ever-changing regulatory landscape. This not only saves time and effort but also reduces the risk of non-compliance and associated penalties.

Overall, AI-driven RPA is revolutionizing the BFSI sector by streamlining operations, improving efficiency, and reducing the potential for errors. By automating repetitive tasks and leveraging AI algorithms, financial institutions can allocate their resources more strategically, focus on critical areas, and provide better services to their customers. As technology continues to advance, AI-driven RPA is expected to play an increasingly vital role in shaping the future of the BFSI sector.

Cost Reduction and Compliance

The banking, financial services, and insurance (BFSI) industry is confronted with strict regulations and an increasing demand for cost control. In this context, AI-enabled Robotic Process Automation (RPA) plays a crucial role in achieving these objectives. By implementing AI-driven RPA, financial institutions can automate regulatory compliance checks and routine operational tasks, leading to significant reductions in operational costs while ensuring adherence to industry regulations. The utilization of AI algorithms enables efficient identification of discrepancies, continuous monitoring of transactions, and generation of compliance reports, thereby saving valuable time and resources. This dual advantage of cost reduction and compliance is fueling the widespread adoption of AI-driven RPA across the BFSI sector.

The BFSI industry operates in a highly regulated environment, with numerous compliance requirements imposed by regulatory bodies. These regulations are designed to safeguard the interests of customers, maintain the stability of financial systems, and prevent fraudulent activities. However, ensuring compliance with these regulations can be a complex and resource-intensive process. AI-enabled RPA offers a solution by automating the compliance checks, thereby reducing the burden on human resources and minimizing the risk of errors. By leveraging AI algorithms, financial institutions can efficiently analyze vast amounts of data, identify potential compliance issues, and take appropriate actions in a timely manner. This not only enhances the accuracy and effectiveness of compliance processes but also frees up human employees to focus on more strategic and value-added tasks.

In addition to compliance, cost control is a critical concern for the BFSI industry. Financial institutions are constantly seeking ways to optimize their operational expenses without compromising on the quality of services provided. AI-driven RPA provides a viable solution by automating routine operational tasks, such as data entry, reconciliation, and report generation. By automating these tasks, financial institutions can achieve significant cost savings by reducing the need for manual labor and minimizing the occurrence of errors. Moreover, AI algorithms can continuously learn and improve over time, leading to enhanced operational efficiency and further cost reductions.

The combination of cost reduction and compliance benefits offered by AI-driven RPA has led to its widespread adoption across the BFSI sector. Financial institutions are increasingly recognizing the potential of AI technologies to streamline their operations, improve efficiency, and ensure regulatory compliance. The implementation of AI-driven RPA not only enables financial institutions to achieve cost savings and regulatory compliance but also enhances their overall competitiveness in the market. As the BFSI industry continues to evolve, AI-enabled RPA is expected to play an increasingly pivotal role in driving operational excellence and meeting the evolving needs of customers and regulators alike.

Enhanced Customer Experience

AI-enabled Robotic Process Automation (RPA) has revolutionized the customer experience in the Banking, Financial Services, and Insurance (BFSI) sector by significantly expediting critical processes such as loan approvals, account management, and customer inquiries. By leveraging automated chatbots and virtual assistants, financial institutions can now provide customers with real-time support, streamline query resolution, and offer personalized services, leading to improved customer satisfaction, strengthened loyalty, and enhanced trust in the financial services industry. One of the key benefits of AI-enabled RPA in the BFSI sector is the ability to expedite loan approvals. Traditionally, loan approval processes have been time-consuming and cumbersome, often requiring customers to submit numerous documents and wait for extended periods for a decision. However, with the implementation of AI-powered automation, financial institutions can now analyze vast amounts of customer data, assess creditworthiness, and make informed decisions in a fraction of the time. This not only reduces the waiting time for customers but also improves the overall efficiency of the loan approval process.

Furthermore, AI-enabled RPA has transformed account management in the BFSI sector. By automating routine tasks such as balance inquiries, transaction history, and fund transfers, financial institutions can provide customers with instant access to their account information. This real-time availability of data empowers customers to manage their finances more effectively and make informed decisions. Additionally, AI-powered virtual assistants can proactively identify potential issues, such as unusual account activity or low balances, and notify customers, thereby enhancing security and preventing fraudulent activities. Moreover, AI-powered chatbots and virtual assistants have revolutionized customer inquiries in the BFSI sector. These intelligent systems can understand and respond to customer queries in real-time, providing accurate and personalized information. By leveraging natural language processing and machine learning algorithms, chatbots can handle a wide range of customer inquiries, from basic account information to complex financial advice. This not only reduces the burden on customer service representatives but also ensures consistent and efficient customer support, regardless of the time or day. Overall, the integration of AI-enabled RPA in the BFSI sector has significantly enhanced the customer experience. By expediting processes such as loan approvals, account management, and customer inquiries, financial institutions can provide customers with real-time support, streamline query resolution, and offer personalized services. These advancements not only improve customer satisfaction but also strengthen customer loyalty and trust in the financial services industry. As AI technology continues to evolve, we can expect further innovations that will revolutionize the way customers interact with financial institutions, ultimately leading to a more seamless and personalized banking experience.

Improved Risk Management

Risk assessment and management play a crucial role in the Banking, Financial Services, and Insurance (BFSI) sector, and the integration of AI-driven Robotic Process Automation (RPA) is revolutionizing these processes. RPA solutions leverage the power of artificial intelligence to analyze vast amounts of data and identify patterns that may indicate potential risks. This proactive approach enables BFSI institutions to mitigate risks before they escalate. By employing AI algorithms, RPA systems can detect anomalies and evaluate transactional data to identify fraudulent activities, thereby triggering alerts for further investigation. This proactive risk management approach empowers BFSI institutions to safeguard their assets, prevent fraud, and uphold the integrity of their financial operations. The BFSI sector deals with a wide range of risks, including credit risk, market risk, operational risk, and compliance risk. Traditionally, risk assessment and management in this sector have relied on manual processes, which are time-consuming and prone to human error. However, with the advent of AI-driven RPA, these processes have become more efficient and effective.

RPA solutions can analyze vast datasets in real-time, enabling them to identify potential risks and patterns that may go unnoticed by human analysts. By continuously monitoring transactions and financial activities, RPA systems can quickly detect any suspicious behavior or deviations from normal patterns. This allows BFSI institutions to take immediate action and prevent potential risks from materializing. One of the key advantages of AI-driven RPA in risk management is its ability to identify fraudulent activities. By analyzing transactional data and comparing it against historical patterns, RPA systems can identify anomalies that may indicate fraudulent behavior. This can include unusual transaction amounts, suspicious account activities, or patterns that deviate from the norm. When such anomalies are detected, the RPA system can automatically trigger alerts, prompting further investigation by human analysts. Furthermore, AI algorithms can continuously learn and adapt to new risks and fraud patterns, making RPA solutions even more effective over time. By leveraging machine learning techniques, RPA systems can improve their accuracy in detecting risks and fraud, thereby enhancing the overall risk management capabilities of BFSI institutions.

Key Market Challenges

Lack of Awareness and Understanding

A significant challenge confronting the Global Robotic Process Automation (RPA) in the BFSI market is the limited awareness and understanding among financial institutions regarding the transformative potential of RPA solutions. Many organizations, particularly smaller banks and financial firms, may not fully comprehend how RPA can optimize their operational processes, enhance compliance, and drive cost savings. This lack of awareness can hinder the adoption of RPA technology, leaving organizations with suboptimal operational efficiency and underutilized automation potential. To address this challenge, comprehensive awareness campaigns and educational initiatives are crucial. These initiatives should emphasize how RPA can streamline routine tasks, mitigate risks, and improve customer service within the BFSI sector. Real-world case studies and practical examples showcasing the tangible benefits of RPA can serve as compelling tools to deepen understanding and drive adoption.

Complexity and Integration Challenges

The implementation and management of RPA solutions can be intricate, especially for BFSI organizations with limited IT resources or experience in automation technologies. Configuring RPA systems effectively and integrating them with existing processes and legacy systems can present technical complexities. Compatibility issues during integration can lead to delays and hinder RPA's ability to deliver optimal performance. To overcome these challenges, it is imperative to simplify the deployment and management of RPA solutions. User-friendly interfaces and intuitive configuration options should be provided to streamline setup and customization. Additionally, BFSI organizations should have access to comprehensive support and guidance, including documentation, tutorials, and expert assistance to facilitate seamless integration and resolve any technical hurdles. Simplifying the implementation process ensures that RPA technology can augment BFSI operations without disruptions.

Mitigating False Positives and Performance Optimization

While RPA solutions excel in automating tasks, they face the challenge of false positives - instances where legitimate operations are mistakenly flagged as issues. These false positives can disrupt workflows and create inefficiencies in BFSI processes. Additionally, the performance of RPA systems can be a concern, especially when handling a high volume of transactions and tasks. Striking the right balance between rigorous automation and minimizing false positives while optimizing performance is paramount. To address this challenge, continuous refinement of RPA algorithms and technologies is essential. Enhanced algorithms can reduce false positives by accurately distinguishing between genuine anomalies and non-issues. The optimization of RPA systems can minimize processing delays and ensure the efficient execution of tasks, even during peak workloads. Ongoing improvements in these aspects empower BFSI organizations to harness the benefits of RPA while maintaining smooth and efficient operations, ultimately enhancing their overall efficiency and service quality.

Key Market Trends

Rise in Sophisticated Cyber Threats

The global market for Robotic Process Automation (RPA) in the BFSI sector is witnessing a surge in sophisticated cyber threats targeting financial institutions. Malicious actors are continually evolving their tactics to exploit vulnerabilities, infiltrate banking systems, and gain unauthorized access to sensitive financial data. Consequently, there is a growing demand for advanced RPA solutions that can effectively detect and counter these sophisticated threats. To address this demand, RPA solution providers are intensifying their efforts to develop intelligent and adaptive RPA systems equipped with the capability to analyze transaction patterns, identify anomalies, and provide real-time protection against emerging threats. These advanced RPA solutions leverage cutting-edge technologies such as artificial intelligence and machine learning to bolster their threat detection capabilities. By processing substantial volumes of financial data, these solutions can swiftly identify irregularities and deviations from expected behavior, enabling financial organizations to respond proactively to evolving threats. The objective is to equip financial institutions with proactive defense mechanisms that can adapt to the ever-changing threat landscape. As RPA technologies advance continuously, financial organizations can benefit from robust security measures that safeguard their operations, protect customer assets, and ensure compliance with stringent financial regulations. By investing in intelligent and adaptive RPA solutions, financial institutions can maintain a vigilant stance against cyber adversaries and safeguard the integrity and confidentiality of their financial operations.

Shift towards Cloud-based RPA Solutions

The global market is witnessing a notable shift towards cloud-based Robotic Process Automation (RPA) solutions within the BFSI sector. This shift is primarily driven by the increasing adoption of cloud computing and the migration of financial processes to cloud-based platforms. Financial institutions are actively seeking RPA solutions that seamlessly integrate with their cloud infrastructure to ensure comprehensive automation and security for their operations.

Cloud-based RPA solutions offer distinct advantages. Firstly, they provide scalability, enabling financial organizations to dynamically allocate resources in response to changing workloads. This scalability ensures that RPA systems can efficiently handle fluctuations in transaction volumes and automate financial processes during peak demand periods.

Moreover, cloud-based RPA solutions deliver flexibility. They can be readily deployed and managed across diverse cloud environments, allowing financial institutions the freedom to select the cloud platform that best aligns with their operational requirements. This flexibility ensures seamless integration with existing cloud infrastructure and accommodates the specific needs of each organization.

Integration of Artificial Intelligence and Machine Learning

The integration of artificial intelligence (AI) and machine learning (ML) technologies into RPA solutions is a prominent trend in the BFSI market. AI and ML algorithms possess the capacity to analyze vast datasets, discern patterns, and detect anomalies in real-time, enabling RPA systems to adapt and effectively respond to evolving challenges. These advanced technologies enhance the precision and efficiency of RPA solutions, reducing instances of false positives and false negatives. RPA solution providers are making substantial investments in AI and ML capabilities to elevate threat detection, automate financial operations, and proactively defend against emerging risks. By harnessing the potential of AI and ML, financial institutions can streamline processes, enhance compliance, and elevate customer service while effectively safeguarding against evolving threats.

Segmental Insights

Application Insights

The banking segment holds the largest market share of more than 59.6% in 2022. Lack of skilled resources, high personnel costs, and the need to increase productivity are the key factors driving the adoption of RPA in the banking sector. Furthermore, the rising market pressure is impelling banks to seek different opportunities to reduce operational costs, maximize efficiency, and accelerate their productivity gains. In addition to enabling easy review of documents, owing to its accessibility, robotic process automation in banks has helped create transparency in an organization where every transaction can be recorded, categorized, and stored.

The financial services and insurance segment is expected to witness the fastest growth at a CAGR of 41.1%. Identifying and automating various processes in the financial services sector is becoming a key priority of robotic process automation vendors. RPA solutions have helped financial services providers to assign employees to value-added tasks to enhance organizational value. The structured legacy systems in BFSI organizations are hard to integrate with the advanced RPA solutions, and modernizing legacy systems becomes a challenge in terms of data accessibility and data migration. In such cases, RPA services, which enable seamless transition, are used. robotic process automation helps organizations automate a time-consuming task so that an employee can focus on customer services by realigning organizational resources.

Deployment Insights

The on-premise segment accounted for a market share of 54.4% in 2022. The BFSI industry handles extremely private and sensitive client information. To have better control over the security of sensitive data, some organizations prefer to maintain it on-premise. With on-premise RPA deployments, BFSI organizations can store data inside of their own infrastructure while still adhering to stringent industry standards and privacy legislation. For organizations with strict security standards and data governance procedures, this tendency is especially pertinent.

The cloud segment is expected to expand at the highest CAGR of 42.1%. RPA technologies in the cloud provide BFSI organizations with a cost-effective alternative. By utilizing the cloud, businesses can grow their RPA installations as necessary and avoid making large upfront infrastructure costs. Platforms for RPA in the cloud often include flexible price structures that let businesses only pay for the resources they use. With the help of this trend, BFSI companies may save expenses while increasing automation efficiency.

Type Insights

The service segment accounted for the largest market share of over 62.3% in 2022 and is likely to dominate the market over the forecast period. The services segment is further bifurcated into consulting, implementation, and training. To cope with the intense industrial competition, service providers are focusing on the enhancement of advisory, training, and consultancy services. These enhancements facilitate cost reduction of various BFSI processes by minimizing the efforts of a Full-Time Employee (FTE). The RPA services specifically focus on the identification of automation opportunities in different organizational processes. Moreover, the service providers also help in planning the development of a suitable solution, choosing the right vendors, and proofing concepts of the solutions to check their real-time usability. All such activities enable precise deployment of the RPA platform, thereby strengthening the core of automation within a BFSI organization. RPA solutions help reduce compliance costs and the overall risks occurring due to information deficits & other operational gaps.

Regional Insights

The North American regional market dominated the robotic process automation in BFSI market in 2022 and accounted for 37.2% market share and is anticipated to retain its position over the forecast period. It is estimated that a U.S. bank with USD 10+ billion assets spends an average of USD 50 million per year on KYC compliance, CDD, and onboarding. The increasing cost of KYC and AML compliance, steep fines, and regulatory scrutiny for non-compliance are necessitating banks and financial institutions to consider new technologies such as automation to identify & prevent theft, financial fraud, money laundering, and terrorist financing, as well as eliminate manual tasks, improve compliance with government regulations, and reduce costs of compliance. Moreover, the growing need for process management and automation solutions in the BFSI sector is anticipated to boost regional market growth.

Asia Pacific is anticipated to rise as the fastest-developing regional market at a CAGR of 42.0% over the forecast period. An increasing number of financial institutions in the Asia Pacific have identified processes suitable for RPA. Furthermore, BFSI organizations are using RPA and AI in areas such as back-office operations for compliance automation & process streamlining and front-end operations for customer service enhancement. Moreover, an increasing number of businesses in the Asia Pacific region are adopting robotic process automation solutions to increase production through faster execution of business processes, bolster overall financial performance, and maintain a competitive edge.

Key Market Players

Antworks

Atos SE

Automation Anywhere, Inc.

Blue Prism Limited

EdgeVerve Systems Ltd.

FPT Software

IBM

Kofax Inc.

Microsoft (Softomotive)

NICE

Nintex UK Ltd. (Kryon Systems)

Pegasystems Inc.

Protiviti Inc.

UiPath

Report Scope:

In this report, the Global Robotic Process Automation in BFSI Market has been segmented into the following categories, in addition to the industry trends which have also been detailed below:

Robotic Process Automation in BFSI Market, By Type:

  • Solution
  • Services

Robotic Process Automation in BFSI Market, By Deployment:

  • Cloud
  • On-premise

Robotic Process Automation in BFSI Market, By Organization:

  • SMEs
  • Large Enterprises

Robotic Process Automation in BFSI Market, By Application:

  • Banking
  • Financial Services & Insurance

Robotic Process Automation in BFSI Market, By Region:

  • North America
  • United States
  • Canada
  • Mexico
  • Europe
  • France
  • United Kingdom
  • Italy
  • Germany
  • Spain
  • Belgium
  • Asia-Pacific
  • China
  • India
  • Japan
  • Australia
  • South Korea
  • Indonesia
  • Vietnam
  • South America
  • Brazil
  • Argentina
  • Colombia
  • Chile
  • Peru
  • Middle East & Africa
  • South Africa
  • Saudi Arabia
  • UAE
  • Turkey
  • Israel

Competitive Landscape

  • Company Profiles: Detailed analysis of the major companies present in the Global Robotic Process Automation in BFSI Market.

Available Customizations:

  • Global Robotic Process Automation in BFSI market report with the given market data, Tech Sci Research offers customizations according to a company's specific needs. The following customization options are available for the report:

Company Information

  • Detailed analysis and profiling of additional market players (up to five).

Table of Contents

1. Product Overview

  • 1.1. Market Definition
  • 1.2. Scope of the Market
    • 1.2.1. Markets Covered
    • 1.2.2. Years Considered for Study
    • 1.2.3. Key Market Segmentations

2. Research Methodology

  • 2.1. Objective of the Study
  • 2.2. Baseline Methodology
  • 2.3. Formulation of the Scope
  • 2.4. Assumptions and Limitations
  • 2.5. Sources of Research
    • 2.5.1. Secondary Research
    • 2.5.2. Primary Research
  • 2.6. Approach for the Market Study
    • 2.6.1. The Bottom-Up Approach
    • 2.6.2. The Top-Down Approach
  • 2.7. Methodology Followed for Calculation of Market Size & Market Shares
  • 2.8. Forecasting Methodology
    • 2.8.1. Data Triangulation & Validation

3. Executive Summary

4. Impact of COVID-19 on Global Robotic Process Automation in BFSI Market

5. Voice of Customer

6. Global Robotic Process Automation in BFSI Market Overview

7. Global Robotic Process Automation in BFSI Market Outlook

  • 7.1. Market Size & Forecast
    • 7.1.1. By Value
  • 7.2. Market Share & Forecast
    • 7.2.1. By Type (Software, Services)
    • 7.2.2. By Deployment (Cloud, On-Premise)
    • 7.2.3. By Organization (SMEs, Large Enterprises)
    • 7.2.4. By Application (Banking, Financial Services & Insurance)
    • 7.2.5. By Region (North America, Europe, South America, Middle East & Africa, Asia Pacific)
  • 7.3. By Company (2022)
  • 7.4. Market Map

8. North America Robotic Process Automation in BFSI Market Outlook

  • 8.1. Market Size & Forecast
    • 8.1.1. By Value
  • 8.2. Market Share & Forecast
    • 8.2.1. By Type
    • 8.2.2. By Deployment
    • 8.2.3. By Organization
    • 8.2.4. By Application
    • 8.2.5. By Country
  • 8.3. North America: Country Analysis
    • 8.3.1. United States Robotic Process Automation in BFSI Market Outlook
      • 8.3.1.1. Market Size & Forecast
        • 8.3.1.1.1. By Value
      • 8.3.1.2. Market Share & Forecast
        • 8.3.1.2.1. By Type
        • 8.3.1.2.2. By Deployment
        • 8.3.1.2.3. By Organization
        • 8.3.1.2.4. By Application
    • 8.3.2. Canada Robotic Process Automation in BFSI Market Outlook
      • 8.3.2.1. Market Size & Forecast
        • 8.3.2.1.1. By Value
      • 8.3.2.2. Market Share & Forecast
        • 8.3.2.2.1. By Type
        • 8.3.2.2.2. By Deployment
        • 8.3.2.2.3. By Organization
        • 8.3.2.2.4. By Application
    • 8.3.3. Mexico Robotic Process Automation in BFSI Market Outlook
      • 8.3.3.1. Market Size & Forecast
        • 8.3.3.1.1. By Value
      • 8.3.3.2. Market Share & Forecast
        • 8.3.3.2.1. By Type
        • 8.3.3.2.2. By Deployment
        • 8.3.3.2.3. By Organization
        • 8.3.3.2.4. By Application

9. Europe Robotic Process Automation in BFSI Market Outlook

  • 9.1. Market Size & Forecast
    • 9.1.1. By Value
  • 9.2. Market Share & Forecast
    • 9.2.1. By Type
    • 9.2.2. By Deployment
    • 9.2.3. By Organization
    • 9.2.4. By Application
    • 9.2.5. By Country
  • 9.3. Europe: Country Analysis
    • 9.3.1. Germany Robotic Process Automation in BFSI Market Outlook
      • 9.3.1.1. Market Size & Forecast
        • 9.3.1.1.1. By Value
      • 9.3.1.2. Market Share & Forecast
        • 9.3.1.2.1. By Type
        • 9.3.1.2.2. By Deployment
        • 9.3.1.2.3. By Organization
        • 9.3.1.2.4. By Application
    • 9.3.2. France Robotic Process Automation in BFSI Market Outlook
      • 9.3.2.1. Market Size & Forecast
        • 9.3.2.1.1. By Value
      • 9.3.2.2. Market Share & Forecast
        • 9.3.2.2.1. By Type
        • 9.3.2.2.2. By Deployment
        • 9.3.2.2.3. By Organization
        • 9.3.2.2.4. By Application
    • 9.3.3. United Kingdom Robotic Process Automation in BFSI Market Outlook
      • 9.3.3.1. Market Size & Forecast
        • 9.3.3.1.1. By Value
      • 9.3.3.2. Market Share & Forecast
        • 9.3.3.2.1. By Type
        • 9.3.3.2.2. By Deployment
        • 9.3.3.2.3. By Organization
        • 9.3.3.2.4. By Application
    • 9.3.4. Italy Robotic Process Automation in BFSI Market Outlook
      • 9.3.4.1. Market Size & Forecast
        • 9.3.4.1.1. By Value
      • 9.3.4.2. Market Share & Forecast
        • 9.3.4.2.1. By Type
        • 9.3.4.2.2. By Deployment
        • 9.3.4.2.3. By Organization
        • 9.3.4.2.4. By Application
    • 9.3.5. Spain Robotic Process Automation in BFSI Market Outlook
      • 9.3.5.1. Market Size & Forecast
        • 9.3.5.1.1. By Value
      • 9.3.5.2. Market Share & Forecast
        • 9.3.5.2.1. By Type
        • 9.3.5.2.2. By Deployment
        • 9.3.5.2.3. By Organization
        • 9.3.5.2.4. By Application
    • 9.3.6. Belgium Robotic Process Automation in BFSI Market Outlook
      • 9.3.6.1. Market Size & Forecast
        • 9.3.6.1.1. By Value
      • 9.3.6.2. Market Share & Forecast
        • 9.3.6.2.1. By Type
        • 9.3.6.2.2. By Deployment
        • 9.3.6.2.3. By Organization
        • 9.3.6.2.4. By Application

10. South America Robotic Process Automation in BFSI Market Outlook

  • 10.1. Market Size & Forecast
    • 10.1.1. By Value
  • 10.2. Market Share & Forecast
    • 10.2.1. By Type
    • 10.2.2. By Deployment
    • 10.2.3. By Organization
    • 10.2.4. By Application
    • 10.2.5. By Country
  • 10.3. South America: Country Analysis
    • 10.3.1. Brazil Robotic Process Automation in BFSI Market Outlook
      • 10.3.1.1. Market Size & Forecast
        • 10.3.1.1.1. By Value
      • 10.3.1.2. Market Share & Forecast
        • 10.3.1.2.1. By Type
        • 10.3.1.2.2. By Deployment
        • 10.3.1.2.3. By Organization
        • 10.3.1.2.4. By Application
    • 10.3.2. Colombia Robotic Process Automation in BFSI Market Outlook
      • 10.3.2.1. Market Size & Forecast
        • 10.3.2.1.1. By Value
      • 10.3.2.2. Market Share & Forecast
        • 10.3.2.2.1. By Type
        • 10.3.2.2.2. By Deployment
        • 10.3.2.2.3. By Organization
        • 10.3.2.2.4. By Application
    • 10.3.3. Argentina Robotic Process Automation in BFSI Market Outlook
      • 10.3.3.1. Market Size & Forecast
        • 10.3.3.1.1. By Value
      • 10.3.3.2. Market Share & Forecast
        • 10.3.3.2.1. By Type
        • 10.3.3.2.2. By Deployment
        • 10.3.3.2.3. By Organization
        • 10.3.3.2.4. By Application
    • 10.3.4. Chile Robotic Process Automation in BFSI Market Outlook
      • 10.3.4.1. Market Size & Forecast
        • 10.3.4.1.1. By Value
      • 10.3.4.2. Market Share & Forecast
        • 10.3.4.2.1. By Type
        • 10.3.4.2.2. By Deployment
        • 10.3.4.2.3. By Organization
        • 10.3.4.2.4. By Application
    • 10.3.5. Peru Robotic Process Automation in BFSI Market Outlook
      • 10.3.5.1. Market Size & Forecast
        • 10.3.5.1.1. By Value
      • 10.3.5.2. Market Share & Forecast
        • 10.3.5.2.1. By Type
        • 10.3.5.2.2. By Deployment
        • 10.3.5.2.3. By Organization
        • 10.3.5.2.4. By Application

11. Middle East & Africa Robotic Process Automation in BFSI Market Outlook

  • 11.1. Market Size & Forecast
    • 11.1.1. By Value
  • 11.2. Market Share & Forecast
    • 11.2.1. By Type
    • 11.2.2. By Deployment
    • 11.2.3. By Organization
    • 11.2.4. By Application
    • 11.2.5. By Country
  • 11.3. Middle East & Africa: Country Analysis
    • 11.3.1. Saudi Arabia Robotic Process Automation in BFSI Market Outlook
      • 11.3.1.1. Market Size & Forecast
        • 11.3.1.1.1. By Value
      • 11.3.1.2. Market Share & Forecast
        • 11.3.1.2.1. By Type
        • 11.3.1.2.2. By Deployment
        • 11.3.1.2.3. By Organization
        • 11.3.1.2.4. By Application
    • 11.3.2. UAE Robotic Process Automation in BFSI Market Outlook
      • 11.3.2.1. Market Size & Forecast
        • 11.3.2.1.1. By Value
      • 11.3.2.2. Market Share & Forecast
        • 11.3.2.2.1. By Type
        • 11.3.2.2.2. By Deployment
        • 11.3.2.2.3. By Organization
        • 11.3.2.2.4. By Application
    • 11.3.3. South Africa Robotic Process Automation in BFSI Market Outlook
      • 11.3.3.1. Market Size & Forecast
        • 11.3.3.1.1. By Value
      • 11.3.3.2. Market Share & Forecast
        • 11.3.3.2.1. By Type
        • 11.3.3.2.2. By Deployment
        • 11.3.3.2.3. By Organization
        • 11.3.3.2.4. By Application
    • 11.3.4. Turkey Robotic Process Automation in BFSI Market Outlook
      • 11.3.4.1. Market Size & Forecast
        • 11.3.4.1.1. By Value
      • 11.3.4.2. Market Share & Forecast
        • 11.3.4.2.1. By Type
        • 11.3.4.2.2. By Deployment
        • 11.3.4.2.3. By Organization
        • 11.3.4.2.4. By Application
    • 11.3.5. Israel Robotic Process Automation in BFSI Market Outlook
      • 11.3.5.1. Market Size & Forecast
        • 11.3.5.1.1. By Value
      • 11.3.5.2. Market Share & Forecast
        • 11.3.5.2.1. By Type
        • 11.3.5.2.2. By Deployment
        • 11.3.5.2.3. By Organization
        • 11.3.5.2.4. By Application

12. Asia Pacific Robotic Process Automation in BFSI Market Outlook

  • 12.1. Market Size & Forecast
    • 12.1.1. By Type
    • 12.1.2. By Deployment
    • 12.1.3. By Organization
    • 12.1.4. By Application
    • 12.1.5. By Country
  • 12.2. Asia-Pacific: Country Analysis
    • 12.2.1. China Robotic Process Automation in BFSI Market Outlook
      • 12.2.1.1. Market Size & Forecast
        • 12.2.1.1.1. By Value
      • 12.2.1.2. Market Share & Forecast
        • 12.2.1.2.1. By Type
        • 12.2.1.2.2. By Deployment
        • 12.2.1.2.3. By Organization
        • 12.2.1.2.4. By Application
    • 12.2.2. India Robotic Process Automation in BFSI Market Outlook
      • 12.2.2.1. Market Size & Forecast
        • 12.2.2.1.1. By Value
      • 12.2.2.2. Market Share & Forecast
        • 12.2.2.2.1. By Type
        • 12.2.2.2.2. By Deployment
        • 12.2.2.2.3. By Organization
        • 12.2.2.2.4. By Application
    • 12.2.3. Japan Robotic Process Automation in BFSI Market Outlook
      • 12.2.3.1. Market Size & Forecast
        • 12.2.3.1.1. By Value
      • 12.2.3.2. Market Share & Forecast
        • 12.2.3.2.1. By Type
        • 12.2.3.2.2. By Deployment
        • 12.2.3.2.3. By Organization
        • 12.2.3.2.4. By Application
    • 12.2.4. South Korea Robotic Process Automation in BFSI Market Outlook
      • 12.2.4.1. Market Size & Forecast
        • 12.2.4.1.1. By Value
      • 12.2.4.2. Market Share & Forecast
        • 12.2.4.2.1. By Type
        • 12.2.4.2.2. By Deployment
        • 12.2.4.2.3. By Organization
        • 12.2.4.2.4. By Application
    • 12.2.5. Australia Robotic Process Automation in BFSI Market Outlook
      • 12.2.5.1. Market Size & Forecast
        • 12.2.5.1.1. By Value
      • 12.2.5.2. Market Share & Forecast
        • 12.2.5.2.1. By Type
        • 12.2.5.2.2. By Deployment
        • 12.2.5.2.3. By Organization
        • 12.2.5.2.4. By Application
    • 12.2.6. Indonesia Robotic Process Automation in BFSI Market Outlook
      • 12.2.6.1. Market Size & Forecast
        • 12.2.6.1.1. By Value
      • 12.2.6.2. Market Share & Forecast
        • 12.2.6.2.1. By Type
        • 12.2.6.2.2. By Deployment
        • 12.2.6.2.3. By Organization
        • 12.2.6.2.4. By Application
    • 12.2.7. Vietnam Robotic Process Automation in BFSI Market Outlook
      • 12.2.7.1. Market Size & Forecast
        • 12.2.7.1.1. By Value
      • 12.2.7.2. Market Share & Forecast
        • 12.2.7.2.1. By Type
        • 12.2.7.2.2. By Deployment
        • 12.2.7.2.3. By Organization
        • 12.2.7.2.4. By Application

13. Market Dynamics

  • 13.1. Drivers
  • 13.2. Challenges

14. Market Trends and Developments

15. Company Profiles

  • 15.1. Antworks
    • 15.1.1. Business Overview
    • 15.1.2. Key Revenue and Financials
    • 15.1.3. Recent Developments
    • 15.1.4. Key Personnel/Key Contact Person
    • 15.1.5. Key Product/Services Offered
  • 15.2. Atos SE
    • 15.2.1. Business Overview
    • 15.2.2. Key Revenue and Financials
    • 15.2.3. Recent Developments
    • 15.2.4. Key Personnel/Key Contact Person
    • 15.2.5. Key Product/Services Offered
  • 15.3. Automation Anywhere, Inc.
    • 15.3.1. Business Overview
    • 15.3.2. Key Revenue and Financials
    • 15.3.3. Recent Developments
    • 15.3.4. Key Personnel/Key Contact Person
    • 15.3.5. Key Product/Services Offered
  • 15.4. Blue Prism Limited
    • 15.4.1. Business Overview
    • 15.4.2. Key Revenue and Financials
    • 15.4.3. Recent Developments
    • 15.4.4. Key Personnel/Key Contact Person
    • 15.4.5. Key Product/Services Offered
  • 15.5. EdgeVerve Systems Ltd.
    • 15.5.1. Business Overview
    • 15.5.2. Key Revenue and Financials
    • 15.5.3. Recent Developments
    • 15.5.4. Key Personnel/Key Contact Person
    • 15.5.5. Key Product/Services Offered
  • 15.6. FPT Software
    • 15.6.1. Business Overview
    • 15.6.2. Key Revenue and Financials
    • 15.6.3. Recent Developments
    • 15.6.4. Key Personnel/Key Contact Person
    • 15.6.5. Key Product/Services Offered
  • 15.7. IBM
    • 15.7.1. Business Overview
    • 15.7.2. Key Revenue and Financials
    • 15.7.3. Recent Developments
    • 15.7.4. Key Personnel/Key Contact Person
    • 15.7.5. Key Product/Services Offered
  • 15.8. Kofax Inc.
    • 15.8.1. Business Overview
    • 15.8.2. Key Revenue and Financials
    • 15.8.3. Recent Developments
    • 15.8.4. Key Personnel/Key Contact Person
    • 15.8.5. Key Product/Services Offered
  • 15.9. Microsoft (Softomotive)
    • 15.9.1. Business Overview
    • 15.9.2. Key Revenue and Financials
    • 15.9.3. Recent Developments
    • 15.9.4. Key Personnel/Key Contact Person
    • 15.9.5. Key Product/Services Offered
  • 15.10. NICE
    • 15.10.1. Business Overview
    • 15.10.2. Key Revenue and Financials
    • 15.10.3. Recent Developments
    • 15.10.4. Key Personnel/Key Contact Person
    • 15.10.5. Key Product/Services Offered
  • 15.11. Nintex UK Ltd. (Kryon Systems)
    • 15.11.1. Business Overview
    • 15.11.2. Key Revenue and Financials
    • 15.11.3. Recent Developments
    • 15.11.4. Key Personnel/Key Contact Person
    • 15.11.5. Key Product/Services Offered
  • 15.12. Pegasystems Inc.
    • 15.12.1. Business Overview
    • 15.12.2. Key Revenue and Financials
    • 15.12.3. Recent Developments
    • 15.12.4. Key Personnel/Key Contact Person
    • 15.12.5. Key Product/Services Offered
  • 15.13. Protiviti Inc.
    • 15.13.1. Business Overview
    • 15.13.2. Key Revenue and Financials
    • 15.13.3. Recent Developments
    • 15.13.4. Key Personnel/Key Contact Person
    • 15.13.5. Key Product/Services Offered
  • 15.14. UiPath
    • 15.14.1. Business Overview
    • 15.14.2. Key Revenue and Financials
    • 15.14.3. Recent Developments
    • 15.14.4. Key Personnel/Key Contact Person
    • 15.14.5. Key Product/Services Offered

16. Strategic Recommendations

17. About Us & Disclaimer