Natural Language Processing in BFSI Market By Component (Solution, Services), By Deployment Mode (On-Premise, Cloud), By Type (Rule-based NLP, Statistical NLP, Hybrid NLP), By Organization Size (Large Enterprises, Small and Medium Sized Enterprises), By Technology (Interactive Voice Response (IVR), Optical Character Recognition (OCR), Text Analysis, Pattern and Image Recognition, Others), By Application (Customer Experience Management, Virtual Assistants/Chatbots, Social Media Monitoring, Sentiment Analysis, Risk and Threat Detection, Claims Processing, Others): Global Opportunity Analysis and Industry Forecast, 2021-2031
The natural language processing (NLP) is a part of artificial intelligence (AI) that enables the computer to interpret human language, obtain meaning, and make communication more convenient by using voice enabled artificial intelligence (AI) and conversational intelligence technologies. In addition, the NLP features such as autocorrect and autocomplete tool help to analyze personal language patterns and identify the most appropriate suggestions for the individual users or public. Furthermore, natural language processing automates much of the physical process, and provides analytics and business intelligence for growth and helps to order and organize the processes. In addition, growing data and increasing complexities in the BFSI industry are expected to open numerous opportunities for the natural language processing (NLP) in the market.
Factors such as rising usage of smart devices to facilitate smart environments in the banking industry, drive the natural language processing in BFSI market growth. In addition, increasing demand for advanced text analytics and the growing use of internet and connected devices, fuel the growth of the natural language processing in BFSI market. However, complexities due to the usage of code-mixed language while implementing NLP solutions and limitations in the development of NLP technology using neural networks are restricting the usage of cloud-based services, which can hamper the market growth. On the contrary, increasing investments of the BFSI sector to develop and improve NLP technology is expected to boost the growth of the market in future. Moreover, increasing demand for better customer service in the banking sector is expected to provide lucrative opportunities for the market to grow in upcoming years.
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.
The natural language processing in BFSI market analysis includes top companies operating in the market, 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. These players have adopted various strategies to increase their market penetration and strengthen their position in the natural language processing in banking industry.
KEY BENEFITS FOR STAKEHOLDERS
The study provides an in-depth analysis of the global natural language processing in BFSI market along with the current trends and future estimations to illustrate the imminent investment pockets.
Information about key drivers, restrains, & opportunities and their impact analysis on the global natural language processing in BFSI market size are provided in the report.
The Porter’s five forces analysis illustrates the potency of buyers and suppliers operating in the industry.
The quantitative analysis of the global natural language processing in BFSI market from 2021 to 2031 is provided to determine the market potential.
Key Market Segments
By Component
Solution
Services
Services
Professional Services
Managed Services
By Deployment Mode
On-Premise
Cloud
Cloud
Public Cloud
Private Cloud
Hybrid Cloud
By Type
Rule-based NLP
Statistical NLP
Hybrid NLP
By Organization Size
Large Enterprises
Small and Medium Sized Enterprises
By Technology
Interactive Voice Response (IVR)
Optical Character Recognition (OCR)
Text Analysis
Pattern and Image Recognition
Others
By Application
Customer Experience Management
Virtual Assistants/Chatbots
Social Media Monitoring
Sentiment Analysis
Risk and Threat Detection
Claims Processing
Others
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
Key Market Players
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.
ThirdEye Data Inc.
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