The use of AI systems and techniques in finance is expanding quickly thanks to the volume of data that is now available and the lower cost of processing power, as reported by Global News Wire.
Use of AI
Financial services companies are increasingly using AI in areas like retail and corporate banking, fraud detection and monitoring, natural language processing (NLP), customer support, asset management, trading, and insurance. Financial authorities and businesses in the public sector are also implementing AI in supervisory technology (Suptech) and regulatory technology (Regtech) applications.
By reducing commissions and other costs associated with transaction execution and increasing productivity, the use of AI in finance can increase efficiency and boost profitability. Additionally, the utilisation of automation and technologically enabled cost reduction allows for increased decision-making transparency, capacity reallocation, and spending effectiveness. Applications of AI in financial services speed up the quality of services and products provided to financial clients, boost product customisation, and expand the range of available goods. By enabling businesses to assess the creditworthiness of customers with little credit history, AI aids in the data insights needed to establish investment plans and improve financial inclusion.
One of the key factors driving market expansion globally is the banking, financial services, and insurance (BFSI) sector’s increasing digitization. For running virtual help, sentiment and prediction analysis, debt collection, reporting, and customer behaviour research, AI is heavily used in the finance industry. It increases efficiency, reduces the possibility of human error, and quickly processes massive amounts of data. AI also aids in the automated and real-time analysis of credit, investment, and cash accounts for assessing personal financial health and creating tailored insights for the future.
The industry will also rise as a result of technological developments including the fusing of financial technology solutions with ML, big data, evolutionary algorithms, and neural networks. These innovations provide improved financial transaction oversight, speech recognition, risk management, and secured network access to banks and financial organisations.
- A comprehensive overview and up-to-date analysis of the current and future global markets for artificial intelligence (AI) in the financial services industry
- Analyses of the global market trends, with market revenue data for 2021, estimates for 2022, 2023 and 2025, and projections of compound annual growth rates (CAGRs) through 2027
- Global market outlook and estimation of the actual market size for AI in Fintech, revenue forecast, and corresponding market share analysis based on component, deployment, application, and region
- Assessment of the key growth driving factors and constraints that will shape the market for AI in financial services, as the basis for projecting demand over the next five years (2022-2027)
- Identification of the companies best positioned to meet this demand owing to or in conjunction with their proprietary technologies, product launches, M&A deals, and other market strategic advantages
- Coverage of the technological, economic, and business considerations of the AI in Fintech market, with analyses and growth forecasts through 2027
- Analysis of the vendor landscape and the global company share analysis of the companies based on their segmental revenues
- Safeguarding Customer Accounts Against Cyber Attacks and Banking Fraud
- Increasing Digitization of the BFSI Industry
- Demand for RPA in Financial Institutions
- Data Confidentiality and Privacy Concerns
- Need for Skilled Workforce to Deploy Ai in Fintech
- Increasing Competition in the Finance Sector
- Increasing Mobile Workforce
- Increasing Use of AI-Enabled Solutions in the Capital Market
Did you subscribe to our newsletter?
It’s free! Click here to subscribe!
Source: Global News Wire
Good post, now the fintech sphere is only becoming more popular due to the multitude of products and the investor. I recently studied the issue of the difference between fintech and regtech in order to better understand how this niche works.