NLP in Finance Market Overview
NLP in Finance Market Size was valued at USD 4.2 Billion in 2022. The NLP in Finance market industry is projected to grow from USD 5.4 Billion in 2023 to USD 39.3 Billion by 2032, exhibiting a compound annual growth rate (CAGR) of 28.20% during the forecast period (2023 - 2032). Global demand for automated, effective financial services is expanding, as is the desire for precise, real-time analysis of intricate financial data, are the key market drivers enhancing the market growth
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Due to the rising demand for automated and effective financial services, the NLP in finance market is anticipated to have considerable growth during the forecast period. Major growth factors include the expanding demand for accurate and timely processing of complicated financial data as well as the advent of Al and ML models that enable improved NLP capabilities in the banking industry. The demand for automated and effective financial services across the globe has fueled the development of NLP in the finance sector. Financial institutions are increasingly turning to NLP technology as they work to offer clients personalised financial solutions that are affordable, effective, and simple to access.
The improvement of customer service is one of the important components of providing increased financial services. Financial institutions are deploying chatbots that are NLP-powered to offer immediate support to their clients, which has resulted in significant cost savings and increased client satisfaction. These chatbots can aid with money transfers, answer frequently asked inquiries, and provide account balance details. For instance, Erica, a chatbot developed by Bank of America, has helped over 15 million customers with their banking needs, lowering customer care expenses by 19%.
Due to the increasing use of AI in the creation of smart assistants, which have become a common occurrence in people's daily lives, the global natural language processing (NLP) industry is expected to expand. Smart assistants like Amazon's Alexa or Apple's Siri are excellent examples of how NLP is now being used by technology firms to enhance the user experience for their customers. Getting relevant search results without having to write your complete search query into the browser's search box is another excellent illustration of how NLP is used in every task.
Once a user writes a few words that are close to the inquiry, Google can now anticipate and automatically type the complete query in its search interface. The present search options are quite effective since with just a few logical words, a user may automatically guess their complete question and receive the best answers. Additionally, throughout the projection period, the increasing use of NLP in data analysis workflows may serve as the global market driver. Thus, driving the NLP in Finance market revenue.
The NLP in Finance Market segmentation, based on offering, includes Software, Rule-based NLP Software, Regular Expression (Regex), Finite State Expression (FSMs), Named Entity Recognition (NER), Part-of-Speech (POS) Tagging, Statistical NLP Software, Naibe Bayes, Logistic Regression, Support Vector Machines (SVMs), Recurrent Neural Networks (RNNs), Hybrid NLP Software, Latent Dirichlet Allocation (LDA), Hidden Markov Models (HMMs), Conditional Random Fields (CRFs), Services, Professional Services, Training and Consulting, System Integration and Implementation, Support and Maintenance and Managed Services. Software segment dominated the global market in 2022. Due to the increased need for NLP tools in the finance sector, the market is anticipated to continue expanding quickly. The accuracy and effectiveness of NLP solutions in the banking sector have greatly increased with the deployment of machine learning algorithms.
The NLP in Finance Market segmentation, based on technology, includes machine learning, deep learning, natural language generation, text classification, topic modeling, emotion detection, and other technologies (named entity recognition, event extraction). Deep learning segment dominated the global market in 2022. NLP innovations in the finance industry have advanced significantly thanks to deep learning. One of deep learning's key benefits is its capacity to learn from massive, complicated datasets, which is crucial in the banking industry because of the abundance of data.
The NLP in Finance Market segmentation, based on application, includes sentiment analysis, risk management and fraud detection, compliance monitoring, investment analysis, financial news and market analysis, customer service and support, document and contract analysis, speech recognition and transcription, language translation, and other applications (CRM optimization, underwriting assistance). Investment analysis segment dominated the global market in 2022. The market is being driven by machine learning-based NLP tools because they can analyse vast amounts of data and give more precise and individualised insights for investment analysis.
The NLP in Finance Market segmentation, based on vertical, includes banking financial services insurance, retail and e-commerce, manufacturing, healthcare and life sciences, energy and utilities, and transportation and logistics. Banking financial services insurance segment dominated the NLP in Finance Market in 2022. This is because more and more industries are using AI and its supporting infrastructure to connect digital revolutions. Technology businesses have expanded their investment in utilising the advantages of AI and machine learning, demonstrating a consistent growing interest in the potential of these technologies.
Figure 1: NLP in Finance Market, by Vertical, 2022 & 2032 (USD Billion)
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By region, the study provides the market insights into North America, Europe, Asia-Pacific and Rest of the World. The North America NLP in Finance Market dominated this market in 2022 (45.80%). The large, established consumer and provider databases in the US and Canada areas are a primary driving force behind this. Some of the most well-known companies operating on the global market's multiregional scale and constantly advancing related systems while also innovating the technology itself are found in the former. Further, the U.S. NLP in Finance market held the largest market share, and the Canada NLP in Finance market was the fastest growing market in the North America region.
Further, the major countries studied in the market report are The US, Canada, German, France, the UK, Italy, Spain, China, Japan, India, Australia, South Korea, and Brazil.
Figure 2: NLP IN FINANCE MARKET SHARE BY REGION 2022 (USD Billion)
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Europe NLP in Finance market accounted for the healthy market share in 2022. Growth in Europe is predicted to be fueled by the increasing use of machine learning and AI technology across all industrial sectors, particularly the local marketing and advertising industry. Further, the German NLP in Finance market held the largest market share, and the U.K NLP in Finance market was the fastest growing market in the European region
The Asia Pacific NLP in Finance market is expected to register significant growth from 2023 to 2032. Regional growth is driven by an increase in the number of small and mid-size businesses who are utilising the benefits of NLP, such as developers of chatbots and autocorrect applications. Moreover, China’s NLP in Finance market held the largest market share, and the Indian NLP in Finance market was the fastest growing market in the Asia-Pacific region.
Leading market players are investing heavily in research and development in order to expand their product lines, which will help the NLP in Finance market, grow even more. Market participants are also undertaking a variety of strategic activities to expand their global footprint, with important market developments including new product launches, contractual agreements, mergers and acquisitions, higher investments, and collaboration with other organizations. To expand and survive in a more competitive and rising market climate, NLP in Finance industry must offer cost-effective items.
Manufacturing locally to minimize operational costs is one of the key business tactics used by manufacturers in the global NLP in Finance industry to benefit clients and increase the market sector. In recent years, the NLP in Finance industry has offered some of the most significant advantages to medicine. Major players in the NLP in Finance market, including Microsoft, Google, AWS, Oracle, SAS lnstitute, Qualtrics, Baidu, Inbenta, Basis Technology, NuanceCommunications, Expert.ai, LivePerson, Veritone, Automated lnsights, Bitext, Conversica,Accern, Kasisto, Kensho, ABBYY, Mosaic, Uniphore, Observe.Al, Lilt, and Cognigy, are attempting to increase market demand by investing in research and development operations.
A company called Grammarly Inc. (Grammarly) offers artificial intelligence products. The company's digital writing assistant solution finds and identifies errors in word choice, grammar, spelling, punctuation, and style. Its solutions offer context-specific adjustments that can be used in social media posts, papers, and messages. Grammarly makes use of a variety of cutting-edge techniques and tools, such as deep learning and sophisticated machine learning. The business provides its products for a range of uses, including work, academic, personal, and commercial. The headquarters of Grammarly are located in San Francisco, California, in the United States. Grammarly attained a list of 30 million active users in 2021.
A healthcare organisation with a focus on speeding data science progress is called John Snow Labs. A healthcare firm that specialises in AI and NLP, John Snow Labs, announced the release of two NLPs in October 2022: Legal NLP and Finance NLP. Modern algorithms and new pre-trained models that can perform Relation Extraction, Entity Recognition, Entity Resolution, Assertion Status Detection, Text Classification, and other tasks are included in the new products or libraries.
May 2022: A newcomer to the market, One AI Inc., announced the fundraising of $8 million for its launch. The business uses natural language processing technologies, and a number of well-known technology investors donated the cash.
| Report Attribute/Metric | Details |
| Market Size 2022 | USD 4.2 Billion |
| Market Size 2023 | USD 5.4 Billion |
| Market Size 2032 | USD 39.3 Billion |
| Compound Annual Growth Rate (CAGR) | 28.20% (2023-2032) |
| Base Year | 2022 |
| Market Forecast Period | 2023-2032 |
| Historical Data | 2018- 2022 |
| Market Forecast Units | Value (USD Billion) |
| Report Coverage | Revenue Forecast, Market Competitive Landscape, Growth Factors, and Trends |
| Segments Covered | Offering, Technology, Application, Vertical, and Region |
| Geographies Covered | North America, Europe, Asia Pacific, and the Rest of the World |
| Countries Covered | The U.S., Canada, German, France, U.K, Italy, Spain, China, Japan, India, Australia, South Korea, and Brazil |
| Key Companies Profiled | Microsoft, Google, AWS, Oracle, SAS lnstitute, Qualtrics, Baidu, Inbenta, Basis Technology, NuanceCommunications, Expert.ai, LivePerson, Veritone, Automated lnsights, Bitext, Conversica,Accern, Kasisto, Kensho, ABBYY, Mosaic, Uniphore, Observe.Al, Lilt, and Cognigy |
| Key Market Opportunities | Development of customized NLP solutions for specific financial services and use cases |
| Key Market Dynamics | Increasing demand for automated and efficient financial services worldwide and rising need for accurate and real-time analysis of complex financial data |
NLP in Finance Market Highlights:
Frequently Asked Questions (FAQ) :
The NLP in Finance Market size was valued at USD 4.2 Billion in 2022.
The global market is projected to grow at a CAGR of 28.20% during the forecast period, 2023-2032.
North America had the largest share in the global market
The key players in the market are Microsoft, Google, AWS, Oracle, SAS lnstitute, Qualtrics, Baidu, Inbenta, Basis Technology, NuanceCommunications, Expert.ai, LivePerson, Veritone, Automated lnsights, Bitext, Conversica,Accern, Kasisto, Kensho, ABBYY, Mosaic, Uniphore, Observe.Al, Lilt, and Cognigy
The Software Offering dominated the market in 2022.
The Deep Learning Technology had the largest share in the global market.
Research Analyst Level II With a technical background in information technology & semiconductors, shubham has 4.5+ years of experience in market research and analytics with the tasks of data mining, analysis, and project execution. he is the poc for our clients, for their consulting projects running under the ict/semiconductor domain. shubham holds a bachelor’s in information and technology and a master of business administration (mba). shubham has executed over 150 research projects for our clients under the brand name market research future in the last 2 years. his core skill is building the research respondent relation for gathering the primary information from industry and market estimation for niche markets. he is having expertise in conducting secondary & primary research, market estimations, market projections, competitive analysis, analysing current market trends and market dynamics, deep-dive analysis on market scenarios, consumer behaviour, technological impact analysis, consulting, analytics, etc. he has worked on fortune 500 companies' syndicate and consulting projects along with several government projects. he has worked on the projects of top tech brands such as ibm, google, microsoft, aws, meta, oracle, cisco systems, samsung, accenture, vmware, schneider electric, dell, hp, ericsson, and so many others. he has worked on metaverse, web 3.0, zero-trust security, cyber-security, blockchain, quantum computing, robotics, 5g technology, high-performance computing, data centers, ai, automation, it equipment, sensors, semiconductors, consumer electronics and so many tech domain projects.
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