NLP in Finance Market Trends, Size, Share, Growth, Industry Analysis, Advance Technology and Forecast 2028

NLP in Finance Market Trends, Size, Share, Growth, Industry Analysis, Advance Technology and Forecast 2028

“Microsoft (US), IBM (US), Google (US), AWS (US), Oracle (US), SAS Institute (US), Qualtrics (US), Baidu (China), Inbenta (US), Basis Technology (US), Nuance Communications (US), Expert.ai (Italy).”
NLP in Finance Market by Offering (Software, Services), Application (Customer Service and Support, Risk Management and Fraud Detection, Sentiment Analysis), Technology (Machine Learning, Deep Learning), Vertical and Region – Global Forecast to 2028

The global NLP in finance market is projected to register a CAGR of 27.6% during the forecast period, reaching USD 18.8 billion by 2028 from an estimated USD 5.5 billion in 2023. Major drivers for the market include the rise in content creation and creative applications, evolution in AI & deep learning, innovation of cloud storage enabling easy access to data, and acceleration in the deployment of Large Language Models (LLMs).

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By offering, Services to register for the highest CAGR during the forecast period

The scope of the services segment comprises professional and managed services. Services are essential to the NLP in finance software life cycle, including product upgradation, maintenance, training, and consulting. In the era of the digital economy, enterprises are evolving and demanding new ways to improve their  Return on Investment and business optimization. Vendors offer various services in the NLP in finance market, such as support, maintenance, and consulting, to execute and manage the life cycle.

By application, Risk Management and Fraud Detection to register for the highest market size during the forecast period

The use of NLP in risk management and fraud detection has been increasing due to its benefits, such as improved speed and accuracy of risk identification and more effective fraud detection. By analyzing large volumes of data, NLP algorithms can identify emerging risks that could impact financial markets. For example, NLP can analyze news articles, social media posts, and other data sources to identify emerging risks that could affect the industry.

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Unique Features in the NLP in Finance Market:

Massive volumes of financial news can be processed and analysed by NLP, which can then be used to extract pertinent sentiments and information to provide real-time insights into market patterns and possible investment possibilities.

By analyzing social media, news articles, and financial reports, NLP can gauge market sentiment. This sentiment analysis helps predict market movements and investor behavior, providing a strategic advantage in trading and investment decisions.

NLP aids in ensuring regulatory compliance by analyzing legal documents, financial reports, and communication logs. It can identify potential compliance risks and flag suspicious activities, thus enhancing risk management efforts.

NLP analyses client communications, transaction patterns, and behaviour to identify fraudulent activity. It assists in spotting irregularities and questionable trends that could point to fraud.

Financial firms utilise virtual assistants and chatbots with natural language processing (NLP) to automate client support. By handling inquiries, offering financial guidance, and helping with transactions, these solutions can enhance client satisfaction while cutting expenses.

Major Highlights of the NLP in Finance Market:

Because there is a growing need for automated customer service, increased data analysis, and improved decision-making capabilities, the NLP industry in finance is expanding quickly. To remain competitive, financial institutions are making significant investments in NLP technologies.

Chatbots and virtual assistants with NLP capabilities are transforming customer service in the financial industry. These tools greatly increase customer happiness and engagement by offering prompt answers to consumer questions, individualised financial advice, and effective transaction handling.

Financial firms may analyse real-time data from several sources, such as financial reports, social media, and news articles, thanks to natural language processing (NLP). This improves trading techniques and decision-making by offering timely insights into investor sentiment, market movements, and possible investment opportunities.

NLP assists in detecting and stopping fraudulent activity by examining communication records, transaction patterns, and client behaviour. This lowers the possibility of financial crimes while improving the general security and integrity of financial transactions.

NLP technology automate the study of financial statements, communication logs, and legal documents, helping businesses ensure regulatory compliance. This lessens the workload for compliance teams by assisting in the identification of possible compliance concerns and optimising the review procedure.

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Top Companies in the NLP in Finance Market

Some leading players in the NLP in finance market include Microsoft Corporation (US), IBM Corporation (US), Google LLC (US), Amazon Web Services (AWS) (US), Oracle Corporation (US), SAS Institute Inc. (US), Qualtrics International Inc. (US), Baidu Inc. (China), Inbenta Technologies Inc. (US), Basis Technology Corp. (US), Nuance Communications, Inc. (US), and Expert.ai (France). These players have adopted various organic and inorganic growth strategies, such as product launches, partnerships and collaborations, and mergers and acquisitions, to expand their presence in the NLP in finance market.

Microsoft caters to a wide range of verticals, including finance and insurance, manufacturing and retail, media & entertainment, public sector, healthcare, and IT & telecommunications. For customized NLP workloads, Spark NLP is an efficient framework for processing a large amount of text. Spark NLP offers functionality such as spell-checking, sentiment analysis, and document classification. It also improves previous efforts by providing state-of-the-art accuracy, speed, and scalability. Microsoft exclusively licensed GPT-3, allowing it to leverage its technical innovations to deliver advanced AI solutions for its customers, as well as create new solutions that harness the power of advanced natural language generation.

IBM is a multinational technology and consulting corporation offering infrastructure, hosting, and consulting services. Within the past two years, IBM has shifted its focus from the hardware business to digital, with increased investments in data, analytics, and natural language processing. IBM Watson AI makes complex NLP technologies accessible to employees who are not data scientists. It provides flexible payment solutions, including leases, loans and deferred payments, and Red Hat products & services that help start projects sooner, achieve business goals more quickly, and increase flexibility and agility.

Google Cloud continues to build AI in numerous solutions that customers can use to develop AI-powered applications — including processing documents, images, and translation — to understand and analyze data more efficiently and to use packaged solutions for a variety of industries. Google Cloud accelerates an organization’s digital transformation through data democratization, app and infrastructure modernization, people connections, and trusted transactions. The result is an organization—and its workers who can take advantage of all the benefits of cloud computing to drive innovation. Google Cloud for financial services empowers transformation and growth and maximizes data-driven innovation, actionable insights, and exceptional customer experiences while meeting security and compliance needs.

AWS offers NLP service named Amazon Comprehend for entity extraction, sentiment analysis, tokenization, and unstructured data classification. This fully managed service allows users to pay as per their usage. Financial institutions are accelerating innovation and digital transformation by leveraging cloud software solutions and harnessing insights from data at scale.

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