In current years, financial institutions are embracing artificial intelligence (AI) technology for maintaining their financial assets and decreasing operating cost, thereby enhancing the revenue. Several fintech businesses and banks are quickly deploying voice assistants and chatbots to handle customer interactions and resolve problems (queries) with minimal human entanglement. Computer vision, Machine learning, and speech recognition technologies are in request and a significant amount of acquisitions in the recent years were connected with these technologies, and the related technologies will control the investment models in the coming years.
Significant fields where AI could be deployed in managing financial assets include personal financial management, fraud detection, and investment banking. With the adoption of financial asset management, the financial institutions can efficiently manage their financial assets and meet expectations of the developing customer behavior by leveraging technologies, inclusive of AI, machine learning, and predictive analytics. This will help organizations in automation and improves business processes, thus succeeding in enhanced customer’s encounter.
The global AI in financial asset management market is classified based on the appearance of diversified small and large organizations. IBM, Genpact, Infosys, and Synechron are among the key vendors expanding their global footprint in this area. However, various vendors such as IPsoft and Lexalytics are struggling with them in the global market by giving solutions at a competitive cost with the customized product offering. The market increase is fuelled by critical vendors entering into strategic partnerships with suppliers and third-party vendors in the ecosystem to expand the global footprint and customer service capabilities.
Natural language processing (NLP) is the most durable growing technology in the global AI in financial asset management business owing to the ever-increasing deployment of chatbots and virtual personal assistants in the banking area. Additionally, the ever-increasing demand for sentiment analysis and management of large volumes of contracts will encourage the NLP segment during the predetermined period.
Data analysis has the largest market share in the application section of the global AI in financial asset management market. Primarily due to the availability of vast volumes of data being produced from multiple sources and needs to analyze theses datasets for judgment composition. Investment banks are executing AI in areas such as alternative investment strategies, investment decisions, managing hedge funds, and others.
As per the Infoholic Research, the global AI in financial asset management market is anticipated to grow at a CAGR of 33.84 percent during the forecast period 2019–2025. This report directs to define, describe, section, and forecast the AI in financial asset management market based on application, technology, and regions. Besides, the report supports the venture capitalists in understanding the businesses better and make well-informed decisions. The report is designed initially to provide the company’s managers with strategically substantial opponent information, data analysis, and understanding about the market, advancement, and implementation for an efficient marketing plan.