Artificial Intelligence has brought revolution to the finance industry with its various use cases. Now, AI-based applications are used to streamline strategic business processes to make them more efficient. Among the various finance sectors, AI is impacting one sector, in particular, wealth management. The wealth management sector needs more accuracy and precise analysis of a great volume of data. So, the wealth management industry is using the power of AI to innovate new AI financial applications that will make the sector run more efficiently.
The wealth management sector helps individuals to effectively handle their finances by providing expert advice. This sector encompasses tax, real estate, and legal guidance. The wealth manager gives you a comprehensive wealth strategy for your unique needs.
AI is helping wealth managers to make more informed decisions with its predictive analytics. It helps them to identify the right investment opportunity and manage risks. AI-based client data analysis also allows managers to provide their clients with tailored advice.
In this blog, we will explore the use cases of AI in wealth management, the difference between traditional and AI-based wealth management, and the future of AI in wealth management.
Let’s get started!
Key Statistics On How AI Is Revolutionising Wealth Management
Before we dive further into the blog, let’s look at some of the key statistics on how AI is revolutionising the field of wealth management.
- The assets under management or AUM by robo-advisors will reach $5.9 trillion by 2027. (1)
- 40% of institutional investors want to allocate their funds to custom indexing products. (4)
- A report published by IDC suggests that, by 2026, the implementation of AI in wealth management will build an empire of $300 billion. (2)
- 67% of wealth management clients are gradually becoming dependent on AI for financial advisors for their financial help. (6)
- A report published by Accenture suggested that 9 out of 10 wealth managers agreed that AI has helped to grow their business by 20%. (2)
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Use Cases Of AI In Wealth Management
Let’s understand in detail some of the most prominent use cases of AI in wealth management and how they help generate more profit for the industry.
Automating Client Onboarding
AI has automated the client onboarding process in the wealth management sector. Investment companies are automating tasks such as initial communications, document verification, and risk profiling. As AI can complete all these processes smoothly, it has increased efficiency and accuracy in the workplace. The productivity of investment firms using AI has also been reported to have increased.
The Deutsche Bank Wealth Management is a leading wealth management platform and they have adopted AI to verify user identities. The application gathers background data about their current and potential customers. It helped the company in making a comprehensive profile for their client.
Portfolio Management
AI-driven wealth management applications help with data and market trends to provide personalised investment strategies. These strategies are very valuable to wealth managers as they help them with asset allocation and portfolio diversification. The AI application continuously monitors the market and can automatically rebalance the portfolios based on their risk tolerance and investment goals.
BlackRock’s Aladdin is a wealth management platform that uses AI to assess risk, manage assets, and adjust portfolios based on market conditions and client’s financial goals. The application makes real-time adjustments to optimal portfolio allocation to achieve the desired investment results.
Predicting Investment Opportunities
AI has given investment companies the benefit of predictive analytics. With it, the companies can forecast market trends and can make informative decisions. Predictive analytics evaluate historical data and current market trends and predict ideal investment opportunities.
IBM’s Watson is a data platform that has helped investment companies make informed decisions based on market movements. Watson has helped companies to forecast any changes in the market and prepare investment strategies according to that analysis.
Personalised Investment Recommendation
The use of AI in wealth management provides personalised investment recommendations to the client. AI analyses individual client profiles, such as risk tolerance, investment preferences, and financial goals. The use of AI in this field can process a massive amount of data on investment performance and market trends to develop personalised investment strategies.
Betterment is one of the most important advisory platforms and it uses AI to develop personalised portfolios based on their client’s financial needs. The AI application keeps updating itself with market conditions to provide personalised advice to clients.
Robo advisors
A survey done by Statista suggests that by 2027, the robo-advisors market will reach 234.3 million users. The robo-advisors provide clients with automated and algorithm-driven investment advice. These advisors help in creating personalised portfolios by analysing client’s financial goals and their risk tolerance. These robo-advisors are cost-effective and they make the wealth management services available to a broader area.
Wealthfront is an investment service firm and a good example of implementing robo-advisors to provide their customers with more precise investment strategies. Robo-advisors have helped the company to automate investment strategies and make the strategies available to a wide range of customers.
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Differences Between Traditional Wealth Management And AI-Based Wealth Management
Now, let us see the difference between traditional wealth management and AI-based wealth management to understand the impact of AI applications better.
Aspects | Traditional Wealth Management | Ai-Based Wealth Management |
Investment advice | This wealth management is based on market analysis done by humans | AI in wealth management analyse huge amount of data and then provide personalised strategies |
Client onboarding | It is a manual process, and the client needs to provide expensive paperwork and go through a complex verification process | AI provides an automated onboarding process. AI can verify documents and access risk profiles more effectively |
Cost | The cost is high because of its dependency on manual processes and human resources | The low is low because of the automation of various tasks |
Personalisation | The scope of personalisation is less as this wealth management is based on individual needs | The implementation of AI personalises every service depending on the customer’s needs |
Transparency | Transparency in traditional wealth management varies depending on the communication of the advisors | Transparency in AI-based wealth management is clear, as it provides information solely based on the data provided |
Future Of AI In The Wealth Management
Now that we have understood how AI is helping the wealth management sector let us see what the future looks like.
Rapid Growth of AI Integration
AI and investment management will be very closely related in the future, and AI integration in the field of wealth management will increase significantly. The global spreading will be triple or more by 2030. This transformation will fundamentally change how financial decisions are made. This shift shows the embracing of advanced technologies in the finance sector.
AI as a Strategic Partner
As the integration of AI will be more and more effective, it will switch its role from a supporting partner to a strategic partner. This shift will change the overall strategic planning and execution of investment opportunities.
Enhanced Personalisation Through AI
The incorporation of AI will lead to hyper-personalised investment strategies made for each client’s financial needs. Wealth managers will use this power of AI to offer effective solutions that will help clients tackle complex market conditions more efficiently.
Shift in Wealth Manager Roles
There will be a shift in the role of wealth managers as well. They will evolve from manual data analysis to a more strategic advisory level. As AI will handle data processing, humans can focus on building strong client relationships and provide insightful financial advice to increase client engagement.
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Conclusion
The implementation of AI in the future of wealth management in 2024 will bring a pivotal shift and will revolutionise traditional wealth management practices. AI integration in the wealth management field will redefine how financial decisions are made. It will bring more efficiency and effectiveness to the workspace. AI will foster an environment where personalised services and automated operations will become trademarks of the wealth management industry in the future. The role of AI will enhance the industry’s financial performance and decision-making.
FAQs
What is wealth management?
Wealth management provides its customers with a comprehensive financial service to manage and grow their assets. It offers services such as investment management, tax planning, and financial and retirement planning. All these services are provided to the clients to meet their financial goals.
How does AI help detect fraud in wealth management?
AI tools for financial planning help in detecting fraud in wealth management by:
- Monitoring all the client’s transactions to detect any fraudulent activities in real-time.
- Analysing the history of the client’s fraud patterns to detect any suspicious activities early.
- Providing warning alerts to wealth managers to take preventive measures to stop fraudulent activity.
Will AI replace human wealth managers?
Though in future the role and importance of AI will increase, human wealth advisors will still play a key role in the wealth management industry. They will keep providing personalized financial advice, strengthen relationships with clients, and provide solutions for complex financial situations.
How does AI help in investment decision-making?
There are various benefits of AI in wealth management. One of those benefits is helping in investment decision-making. As AI can analyse a vast amount of data, including market trends and individual client needs, it is capable of providing a more informed investment decision. The AI algorithm can identify market patterns more efficiently than a human being, which leads to making a more informed investment decision.
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