Artificial intelligence (AI) is evolving in asset management and is revolutionizing the industry in many ways. Asset management companies that use AI and structured and unstructured data can gain a competitive advantage because large amounts of information can be accessed faster and more accurately.
By applying NLP to investment research and analysis, AI can gather key insights, summarize and create potential action steps from data that wealth managers can use in their investment decisions.
What is Artificial Intelligence?
AI is a branch of computer science that’s defined as technology that simulates human-like reasoning by learning from data. In the asset management industry, AI uses computer algorithms to replicate human behavior based on historical data and then make better decisions.
For instance, AI can search across a portfolio and find trades that produce the best results based on historical data.
For example, you can tag information like the date the transaction was made or the instrument the money went to. This would allow AI to be able to look through the data and find relevant data.
What are the benefits of AI in asset management?
AI can perform thousands of jobs that were previously requiring highly-skilled, professional investment professionals.
AI can: Algorithmically predict trading strategy. Find low-cost funds or specific investment strategies. Appraise stocks to provide critical, high-level insights. Accelerate the analysis and discovery process. The growing demand for quantitative data is motivating asset managers to move quickly to embrace AI.
The National Council of Underwriting Management states that more than two-thirds of insurance companies are using data analytics to better understand their clients and to grow their businesses. Asset managers that embrace AI will benefit from greater productivity and reduced costs, as well as improved risk management and profitability.
How does AI assist in investment decisions?
To create tailored investment solutions, asset management companies use both structured and unstructured data to guide investment recommendations. This type of structured data refers to data that can be categorized into specific logical boxes that AI can interpret. Unstructured data refers to data that can’t be stored or reviewed into logical, linear categories.
The introduction of AI can transform the way wealth managers approach investment research by analyzing financial, data, and social media content to create more valuable investment recommendations. Hiring the right technology is just the first step. Ensuring it is in the right place to support your business requires strong data management, user experience design, and intuitive design.
The asset management industry is changing at a rapid rate and the adoption of innovative tools and services is accelerating. Financial firms are turning to AI to identify investment opportunities and better monitor macro-economic and industry-specific trends, as well as to implement the right strategy to drive out performance and capture value for clients.
The asset management industry has been a leader in using emerging technology in recent years and is likely to remain so in the future. As fintech start-ups continue to enter the asset management space and invest in technologies such as AI and blockchain, the future of financial services is likely to be defined by technology. However, AI can only be leveraged if there is strong industry-wide adoption.