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2022

Natural Language Processing in BFSI Market

Natural Language Processing in BFSI Market Size, Share, Competitive Landscape and Trend Analysis Report by Component, by Deployment Mode, by Type, by Organization Size, by Technology, by Application : Global Opportunity Analysis and Industry Forecast, 2021-2031

BI : IT in BFSI

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Author's: Kanhaiya Ramesh Kathoke| Sourabh Ekre | Onkar Sumant
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Natural Language Processing In BFSI Market Research, 2031

The global natural language processing in bfsi market was valued at $3.2 billion in 2021, and is projected to reach $20.3 billion by 2031, growing at a CAGR of 20.5% from 2022 to 2031.

Natural Language Processing in BFSI Market Insights

The natural language processing is a high-tech solution that enables computers to extract meaning from text. Moreover, natural language generation also serves as a natural interface for human to machine communication, and allowing the machine to understand and respond to natural language interactions. Furthermore, the integration of ML and deep learning (DL) with NLP AI automates all banking operations, which helps to handle more easily growing business concerns about cost, scalability, and security while protecting vital data, as well as enhance the economic infrastructure.

The adoption of NLP cuts operational costs and eliminates the costs of advertising, interviewing, and training new personnel to perform the jobs by simplifying corporate processes. In addition, rise in use of digital and intelligent technologies in the banking industry is primarily responsible for the rise of the natural language processing in BFSI market. These factors notably contribute toward the growth of the global natural language processing in BFSI market. However, high costs for systems & servers and high costs for experts for server maintenance are some of the factors that hamper the market growth. On the contrary, a gradual shift toward a digital economy of the banking sector across several countries is expected to fuel the growth of the market. In addition, surge in adoption of natural language processing in banking sector across emerging economies is expected to provide lucrative opportunities for the market growth in the coming years.

The report focuses on growth prospects, restraints, and trends of the natural language processing in BFSI market analysis. The study provides Porter’s five forces analysis to understand the impact of various factors such as bargaining power of suppliers, competitive intensity of competitors, threat of new entrants, threat of substitutes, and bargaining power of buyers on the natural language processing in BFSI market outlook.

The natural language processing in bfsi market is segmented into Component, Deployment Mode, Type, Organization Size, Technology and Application.

Segment Review

The natural language processing in BFSI market is segmented into component, deployment mode, type, organization size, technology, application, and region. By component, the market is differentiated into solution and services. The services in further segmented into professional services and managed services. The professional services is further differentiated into system implementation & integration, support & maintenance, and training & consulting. The deployment mode is segmented into on-premise and cloud. The cloud is further segmented into public cloud, private cloud, and hybrid cloud. By type, the market is segmented into rule-based NLP, statistical NLP   and hybrid NLP. Depending on organization size, it is fragmented into large enterprises and small and medium sized enterprises. By technology, it is differentiated into interactive voice response (IVR), optical character recognition (OCR), text analysis, pattern and image recognition, and others. The application segment is segregated into customer experience management, virtual assistants/chatbots, social media monitoring, sentiment analysis, risk and threat detection, claims processing, and others. Region-wise, the market is analyzed across North America, Europe, Asia-Pacific, and LAMEA.

Natural Language Processing in BFSI Market by Component

By component, the solution segment acquired the highest share of natural language processing in BFSI market size in 2021. This is attributed to the fact that NLP solutions offers the necessary tools to analyze both numerical and linguistic data, which is beneficial for the BFSI industry.

Natural Language Processing in BFSI Market by Region

Region-wise, North America dominated the natural language processing in BFSI market share in 2021. This is attributed to the fact that presence of major industry players in the region fosters the growth of the market. Furthermore, rise in technological support and developed R&D sector in the region fuel the growth of the market. In addition, increase in adoption NLP in the banking industry of the region owing to increased competition among the prominent players boost the growth of the market.

The key players operating in the global natural language processing in BFSI market include, Accenture, ACCERN CORPORATION, Alphabet Inc., Amazon.com, Inc., Artificial Solutions, CSS Corp., eGain Corporation, Gnani Innovations Private Limited, IBM, InData Labs, Microsoft, MindMeld, Inc., Nexocode, Oracle, Verint Systems Inc., Infinia ML, Inc., and ThirdEye Data Inc. These players have adopted various strategies to increase their market penetration and strengthen their position in the natural language processing in BFSI industry.

COVID-19 Impact Analysis

The COVID-19 pandemic has a significant impact on the natural language processing (NLP) in BFSI industry, owing to increase in usage and adoption of online & digitalized banking methods among consumers globally. The natural language processing (NLP) in BFSI market is experiencing massive growth as consumers are getting familiar with the digital technologies in the market. Moreover, banks and fintech industries are increasingly developing AI and ML technologies to provide precise information to the customers. This, has become one of the major growth factors for the natural language processing in BFSI industry during the global health crisis.

Top Impacting Factors

Increasing Automation in Banking Processes as a Result of Integration of NLP with Deep Learning (DL) and Machine Learning (ML)

There was a surge in NLP technology adoption as artificial intelligence (AI) and machine learning (ML) technologies became more widely used in the BFSI industry. The AI-driven NLP empowers banks to keep up-to-date with the latest data, automate repetitive task, and internal processes, and improve productivity. In addition, it improves customer experience through predictive analytics and automate function where manual processes were previously required, and personalize user-interface capabilities. As AI provides personalization solutions through the use of technologies, such as natural language processing (NLP), which can be engaged by human speech and voice commands.

Moreover, artificial intelligence (AI) accelerates numerous operations across the BFSI industry and internal processes to achieve faster responses, produce quick projections, and provide rapid responsiveness. Furthermore, for improved security, artificial intelligence (AI) uses its unique capability of machine learning (ML) to recognize patterns, the ability to quickly identify and remediate possible risks with built-in self-recovery improves NLP security. Furthermore, the integration of ML and deep learning (DL) with NLP automates all banking operations, which helps to handle more easily growing concerns about cost, scalability, and security while protecting vital data, as well as enhance the operational efficiency. Thus, this factor is driving the natural language processing in BFSI market growth.

Growth in use of Internet and Connected Devices in BFSI Industry

Setting up connection between various devices is implemented owing to the development of IoT and communication technologies in BFSI industry. In addition, the emergence of new technologies and the digital revolution have altered how banks operate and interact with their clients. Moreover, the growing demand for voice-based solutions that interface with NLP-based applications for providing better customer service in BFSI industry is propelling the growth of natural language processing in BFSI market.  

Rising Demand for Predictive Analytics to Reduce Risks in BFSI Industry

Numerous advantages of NLP, such as increasing volumes & data types, using data to produce valuable insights, tougher economic conditions, and requirement for competitive differentiation & easy to use software, create the demand for NLP in BFSI industry. In addition, it improves customer experience through predictive analytics and automate banking operations where manual processes were previously required, and personalize user-interface capabilities. Furthermore, it helps in detecting fraud, optimizing marketing campaigns, improving operations and reducing risk which is expected to fuel the growth of the market.

Key Benefits for Stakeholders

  • This report provides a quantitative analysis of the market segments, current trends, estimations, and dynamics of the natural language processing in BFSI market forecast from 2021 to 2031 to identify the prevailing market opportunities.
  • The market research is offered along with information related to key drivers, restraints, and opportunities of natural language processing in BFSI market overview.
  • Porter's five forces analysis highlights the potency of buyers and suppliers to enable stakeholders make profit-oriented business decisions and strengthen their supplier-buyer network.
  •  In-depth analysis of the natural language processing in BFSI market segmentation assists to determine the prevailing natural language processing in BFSI market opportunity.
  • Major countries in each region are mapped according to their revenue contribution to the global market.
  • Market player positioning facilitates benchmarking and provides a clear understanding of the present position of the market players.

The report includes the analysis of the regional as well as global natural language processing in BFSI market trends, key players, market segments, application areas, and market growth strategies.

Natural Language Processing in BFSI Market Report Highlights

Aspects Details
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By Component
  • Solution
  • Services
    • Services
      • Professional Services
      • Managed Services
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By Deployment Mode
  • On-Premise
  • Cloud
    • Cloud
      • Public Cloud
      • Private Cloud
      • Hybrid Cloud
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By Type
  • Rule-based NLP
  • Statistical NLP
  • Hybrid NLP
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By Organization Size
  • Large Enterprises
  • Small and Medium Sized Enterprises
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By Technology
  • Interactive Voice Response (IVR)
  • Optical Character Recognition (OCR)
  • Text Analysis
  • Pattern and Image Recognition
  • Others
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By Application
  • Customer Experience Management
  • Virtual Assistants/Chatbots
  • Social Media Monitoring
  • Sentiment Analysis
  • Risk and Threat Detection
  • Claims Processing
  • Others
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By Region
  • North America  (U.S., Canada)
  • Europe  (UK, Germany, France, Italy, Spain, Netherlands, Rest Of Europe)
  • Asia-Pacific  (China, Japan, India, Australia, South Korea, Singapore, Rest Of Asia-Pacific)
  • LAMEA  (Latin America, Middle East, Africa)
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Key Market Players

Artificial Solutions, InData Labs, Oracle, Nexocode, Infinia ML, Inc., Verint Systems Inc., ThirdEye Data Inc., eGain Corporation, MindMeld, Inc., Microsoft, Alphabet Inc., IBM, Amazon.com, Inc., ACCERN CORPORATION, Accenture, Gnani Innovations Private Limited, CSS Corp.

Analyst Review

BFSI industry has experienced various changes in the business processes, operations, and industrial automation. Moreover, banks are shifting towards the digital platform and increasing implementation of the industry 4.0 to cope with ongoing tough business competition, which creates the need for seamless solution and platform to meet these requirements. This increases the adoption of NLP platform in the banking industry rapidly. Furthermore, NLP has boomed as artificial intelligence (AI) and machine learning (ML) technologies become more widely used in the banking sector. The AI-driven NLP empowers businesses to keep up-to-date with the latest data, automate repetitive task, internal processes, and improve productivity. In addition, it improves customer experience through predictive analytics and automate function where manual processes were previously required, and personalize user-interface capabilities. Such advantages are expected to provide lucrative growth opportunities for the market growth in the upcoming years.

The COVID-19 outbreak has a significant impact on the natural language processing in BFSI market, and has accelerated the adoption of cloud computing owing to the trend of digital banking. Moreover, during this global health crisis, adoption of natural language processing in banking technology increased among all the banks and financial institutions. This promoted the demand for natural language processing in BFSI, thereby accelerating revenue growth.

The natural language processing in BFSI market is segmented with the presence of regional vendors, such as Accenture, ACCERN CORPORATION, Alphabet Inc., Amazon.com, Inc., Artificial Solutions, CSS Corp., eGain Corporation, Gnani Innovations Private Limited, IBM, InData Labs, Microsoft, MindMeld, Inc., Nexocode, Oracle, Verint Systems Inc., Infinia ML, Inc., and ThirdEye Data Inc. Major players operating in this market have witnessed significant adoption of strategies that include business expansion and partnerships to reduce supply and demand gaps. With increase in awareness and rise in demand for natural language processing in BFSI across the globe, major players are collaborating on their product portfolio to provide differentiated and innovative products.

Author Name(s) : Kanhaiya Ramesh Kathoke| Sourabh Ekre | Onkar Sumant
Frequently Asked Questions?

The natural language processing in BFSI market is estimated to grow at a CAGR of 20.5% from 2022 to 2031.

The natural language processing in BFSI market is projected to reach $20.29 billion by 2031.

Increasing automation in banking processes as a result of integration of NLP with deep learning (DL) and machine learning (ML), growth in use of internet and connected devices in BFSI industry and rising demand for predictive analytics to reduce risks in BFSI industry majorly contribute toward the growth of the market.

The key players profiled in the report include Accenture, ACCERN CORPORATION, Alphabet Inc., Amazon.com, Inc., Artificial Solutions, CSS Corp., eGain Corporation, Gnani Innovations Private Limited, IBM, InData Labs, Microsoft, MindMeld, Inc., Nexocode, Oracle, Verint Systems Inc., Infinia ML, Inc., and ThirdEye Data Inc.

The key growth strategies of natural language processing in BFSI market players include product portfolio expansion, mergers & acquisitions, agreements, geographical expansion, and collaborations.

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Natural Language Processing in BFSI Market

Global Opportunity Analysis and Industry Forecast, 2021-2031