Financial Services
AI in Wealth Management: A Complete Guide
Discover how using AI in wealth management operations improves decision-making, enhances client experiences, and increases operational efficiency.
The use of artificial intelligence (AI) has grown exponentially in financial services, specifically in wealth and asset management. While many financial services and wealth management firms have started using generative AI in their daily operations, there is a lack of AI software designed specifically for financial services.
Financial services organizations can mitigate risk, improve efficiency, and offer more personalized experiences with trusted AI for financial services. These teams have discovered that AI can be used to streamline and expedite a wide range of processes. AI can provide calculations, forecast trends, and support investment research, helping teams work more efficiently and effectively. Here are some key stats:
- An impressive 91% of financial services business leaders believe that generative AI would benefit their organizations.
- Financial services experienced a 26% increase in productivity when using generative AI.
Engage your customers and employees with Financial Services Cloud.
Accelerate digital process innovation across the front, middle, and back office and put your customer at the center of everything. Unlock data and insights to build customer trust and increase employee productivity with Financial Services Cloud – a single, connected financial services AI CRM.
What are the benefits of using AI in wealth management?
Using AI in wealth management helps clients and businesses alike. It automates tasks like portfolio rebalancing, risk assessment, and client reporting. This helps firms save time and money. AI also helps wealth managers make better investment and risk decisions by analyzing vast amounts of data and identifying trends that humans might miss.
- Increased productivity and efficiency: The hallmark of AI is increased efficiency and productivity. Today, you can find everything you need in one place with solutions like Financial Services Cloud. Built-in AI enables you to manage data from core banking, wealth, and insurance platforms, saving you time — and money.
- Personalization: Automation and industry specific AI for financial services personalization gathers insights from customer data, and then makes specific recommendations based on a customer’s history and goals. This tailored content increases engagement and helps build stronger customer relationships.
- Improved decision-making and risk management: AI in investment management improves decision-making by analyzing vast amounts of data in real time, identifying patterns, and predicting market trends quickly and accurately. It continuously monitors portfolios and alerts human advisors to potential risks or opportunities, enabling them to proactively make adjustments that align with client goals.
- Cost-effectiveness and scalability: AI automates routine tasks such as portfolio rebalancing, client onboarding, and compliance checks, reducing operational costs. Its scalability allows firms to serve a larger client base with personalized services, regardless of the client’s portfolio size or complexity.
AI in wealth management use cases
There are many use cases that demonstrate the benefits of implementing financial services AI software such as lead generation and client acquisition for sales or marketing teams and compliance and regulatory management for risk teams. Even customer service in financial services will be able to scale and provide support faster. Client-facing advisors especially will be able to delegate routine tasks to AI, so they can focus on what matters most — the client.
Client retention and engagement
When it comes to financial services, it's essential to keep your clients engaged and coming back for more. Virtual advisors can help you achieve this by responding to financial queries instantly and guiding users through budgeting or investment strategies with personalized assistance. This way, your clients will always feel supported and informed, no matter what their needs may be.
While a human customer support agent may take time to respond or struggle with language barriers, an AI chatbot can reply instantly in the customer’s language and provide support right on the company’s platform or the client's channel of choice.
Portfolio optimization and asset allocation
Investment and wealth management solutions powered by AI can analyze market data to spot trends and make data-driven portfolio recommendations to clients. A traditional wealth manager may look at data from the last month or year. AI can review that data and also use real-time data to make the best possible decisions when it comes to portfolio optimization and asset allocation.
Risk management and fraud detection
With AI, firms can identify risky borrowers and applications, detect fraud, and manage cybersecurity threats. AI will use smart tools like identity verification and credit scoring to spot fraud and ensure Know Your Customer (KYC) and Anti-Money Laundering (AML) obligations. Additionally, AI can analyze large datasets in real time to identify patterns and anomalies that might indicate fraudulent activity. Firms can also use AI to automate tasks to improve operational efficiency and reduce the risk of human error. This results in a more secure and reliable wealth management experience for clients.
Financial planning and advice
AI can personalize financial planning by analyzing a client’s income, expenses, and investment goals to give tailored recommendations. It can also offer real-time insights and predictive analytics to help your clients make informed decisions based on market trends and risk assessments. Plus, AI can continuously monitor a financial portfolio and suggests adjustments periodically or instantly based on changing economic conditions.
What are the ethical considerations when using AI in wealth management?
In the wealth management industry, trust is vital for keeping customer data secure. AI offers many benefits, but it's important to weigh potential risks and considerations. Stay up-to-date with compliance restrictions and software updates. Before implementing AI and granting access to customer data, thoroughly review and test the software.
Bias and fairness in AI algorithms
Data bias, algorithmic bias, human bias, and feedback loops are the main sources of bias in AI. As advanced as AI software is, it was built and trained by humans and is looking at data that humans provided and learning from human behavior and interactions. Remember that the same biases that humans have will be reflected in AI because it's a human-designed product. Algorithmic bias could lead to unfair or discriminatory financial outcomes for certain groups. Employees should test the AI software’s responses with this in mind.
Security
Data security is a top priority when adopting and implementing AI in wealth management. Financial information is highly sensitive, and the industry is subject to numerous compliance regulations. Your AI solution must have robust data privacy features, such as cryptographic keys and layers of authentication. Compliance laws around AI are always changing. Assign someone to stay up-to-date with the latest information.
Transparency, accuracy, and explainability of AI decisions
AI isn’t always accurate. How do you know the information you’re getting from your wealth management AI software is correct? Choose a solution with a good track record and includes sources when listing statistics. Ensure your software is up-to-date with the latest laws and regulations. Ask an AI chatbot to explain its reasoning and offer context for its decisions.
Trends in AI wealth management
Conversations between people and AI will feel more natural as natural language processing (NLP) improves and chatbots advance. Chatbots will soon speak more languages, so businesses can expand their global reach.
AI is the future, and it's only going to become more integrated with other emerging technologies. Blockchain technology can be used to support more secure transactions, and augmented and virtual reality can be used to increase client engagement. Additionally, the latest real-time data software and quantum computing can be used to simulate market scenarios and risk assessments, providing analysts with extremely reliable data to work from.
The evolving regulatory landscape and AI governance will become even more important. Regular AI audits will be essential to ensure compliance with ethical and legal standards. Certification programs will likely be developed for both AI systems and human users. Stricter privacy laws around data collection, storage, and processing will likely emerge.
How to get started with AI in wealth management
The sooner you integrate AI into your wealth management operations and market-facing services, the faster you’ll see results. Get started by taking a few key steps.
- Identify goals and use cases: Confer with client-facing employees as well as those in the mid- and back-offices.
- Evaluate benefits, risks, and costs: AI goes a long way toward streamlining operational processes and saving advisor’s time. To help mitigate risks — and consequently costs — consider implementing risk-management, compliance, and data-protection features.
- Provide training and adoption strategies: Ensure that current tech platforms are up to date and that employees have the training required to use them successfully.
- Conduct proof-of-concept demonstrations and pilot projects: Set up innovation labs and sandbox trials to allow for development, testing, and implementation.
Above all, get familiar with financial services software and all its applications, particularly customer relationship management for financial advisors.
AI in Wealth Management FAQs
How is AI used in wealth management?
AI is used in wealth management to improve decision-making, enhance client experiences, and increase operational efficiency. Here are the most common use cases.
- Portfolio management
- Personalized financial advice
- Risk management
- Fraud detection and security
- Client onboarding and support
- Tax optimization and compliance
How will AI reshape wealth management?
Artificial Intelligence (AI) will change the face of wealth management by offering personalized financial advice. AI will analyze individual financial goals, spending habits, and risk tolerance to provide tailored recommendations. This will create an interactive and immediate experience for clients, enhancing their engagement. AI will also use vast amounts of financial data to generate insights using the most up-to-date information. This will help identify market trends and investment opportunities with greater accuracy.
This data-driven approach will enable wealth managers to:
- Make informed decisions
- Optimize portfolios
- Improve long-term financial outcomes for clients
What is the market size for AI wealth management?
In 2020, the global market for AI in wealth management was valued at $202.9 million USD. The global market size for asset management increased in 2022 to 2.61 billion USD. Some financial analysts expect the market to grow at a compound annual growth rate of 24.5% between 2023 to 2030. Others project a compound annual growth rate of 35.6% between 2021 to 2025. A PWC study predicts that assets managed by these algorithm-driven and AI-enabled digital platforms will reach around $6 trillion USD by 2027.
Can wealth management AI replace financial advisors?
AI is a powerful tool that can help wealth managers quickly conduct research and troubleshoot problems. However, AI shouldn’t completely replace human financial advisors. Only humans can truly understand the complexities of human behavior. For example, wealth management software or an AI financial advisor would not be able to determine how risk averse a client is by the tone of their written messages. A human advisor is able to ask follow-up questions to better understand the situation, while AI may struggle to take subtle nuances into account when responding.