Financial Insights

How AI is helping Financial Planning and Investment Management

30th Apr 2024

6 minute read

Mariel Diez

Mariel Diez

Head of content

Compare Wealth Managers

Jordan Gillies

Jordan Gillies

Partner

Saltus

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financial advisers should be more concerned about failing to integrate AI to improve efficiency and increase the quality of service than being replaced by it

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In recent years, Artificial Intelligence (AI) has emerged as a game-changer in various industries, and the financial sector is no exception. With its ability to process vast amounts of data, identify patterns, and make predictions, AI is trying to reshape the landscape of financial planning and investment management, empowering both financial advisors and investors alike. But are we there yet?

AI is driving startups and has the potential to transform the way financial institutions operate. Using real-time market data to get deeper insights and direct investment decisions, AI models could execute trades at a speed and precision never seen before. There are some key areas where AI can optimise processes and improve the overall financial journey of many, however it is still at a very early stage and regulation for these tools in the financial world are even further behind.

According to Jordan Gillies, partner at Saltus, the main areas that AI will assist in the near term -or is currently assisting- are areas such as:

  • Automatically populating digital fact finds following recorded meetings between advisers and their clients, optimising the experience for both parties
  • Assessing data to help understand correlation between demographics and ages to determine when or what advice might be useful across a large client base.
  • Various administrative burdens, like password recovery processes or handling minor administrative tasks.
  • Assessing advice reports to reduce errors and producing simple reports for minor recommendations.
  • Compliance: supporting advisers with assessing suitability on an ongoing basis by reducing human error and identifying patterns of personal bias.

Gillies adds that, whilst AI is rarely being used effectively in the financial industry at present, its potential is very exciting. It should drive significant efficiencies in the finance industry, but there’s still some way to go. “So far it’s been steady evolution rather than revolution. As you’ll note from fairly mundane list of the near-term benefits of AI, we’re a long way from the concept of AI being able to replicate a human adviser. We may never get there due to the behavioural elements of how people interact with their money. At present, financial advisers should be more concerned about failing to integrate AI to improve efficiency and increase the quality of service than being replaced by it.”

What is AI (potentionally) doing for the finance industry

Some other areas where it’s starting to be applied are:

AI in Financial Planning

• Data Analysis and Pattern Recognition: AI algorithms can analyse enormous datasets with lightning speed, enabling financial advisors to extract valuable insights. By recognizing patterns in market trends, customer behaviour, and economic indicators, AI could equip advisors with a comprehensive understanding of the financial landscape.

• Personalised Financial Advice:

AI can’t currently provide regulated personal financial advice. However, AI powered-tools can be used by a professional, chartered financial adviser to support them in providing personalised advice, tailored to individual needs and preferences. Nonetheless, a professional adviser might know the client's history and preferences better, including his aspirations and those of his family, so their input in the process will be valuable. The combination of AI-powered tools and professional experience will probably optimise the planning and advice given to the customers. 

• Risk Management:

AI-powered tools excel in risk assessment and mitigation by evaluating various factors that could impact investment performance. These tools could analyse market volatility, economic indicators, and geopolitical events in real time, allowing advisers to make informed decisions to protect and optimize their clients' portfolios.

• Automated Trading:

AI algorithms are increasingly being utilised for automated trading strategies, executing trades based on predefined parameters and market conditions. This automation not only enhances efficiency but also minimises the impact of human emotions when making investment decisions. This could lead to more disciplined and consistent trading practices. Nonetheless, an experienced "human" eye can spot trends that repeat throughout history and add valuable insights that the algorithms may fail to take into consideration.

AI in Investment Management

• Portfolio Optimisation:

AI-driven portfolio optimisation algorithms continuously monitor market dynamics and adjust asset allocations to maximize returns while minimising risk. By leveraging machine learning techniques, these algorithms adapt to changing market conditions and investor preferences, ensuring optimal performance of investment portfolios. But, as mentioned above, a seasoned investment manager can bring more to the table and interpret the algorithm better for the customer to achieve his personal goals faster and more effectively.

• Predictive Analytics:

Through sophisticated algorithms, AI can analyse historical data, news sentiment, and macroeconomic indicators to anticipate market movements and make data-driven investment decisions.

• Fraud Detection and Security:

AI plays a crucial role in enhancing security measures within the financial industry by detecting fraudulent activities and safeguarding sensitive information. AI algorithms can detect anomalies in transaction patterns, identify potential security breaches, and prevent unauthorized access to financial assets, thereby bolstering the trust and confidence of investors.

• Customer Experience Enhancement:

By leveraging AI-powered chatbots and virtual assistants, investment management firms can provide personalised customer support and answer queries in real time. This seamless integration of AI technology enhances the overall customer experience, fostering long-term client relationships and loyalty.

Artificial Intelligence in Finance Governance

Monitoring is necessary to guarantee appropriate use and low risk while using AI in finance. Given that financial institutions handle enormous volumes of sensitive data, proactive governance can promote the use of AI in a responsible, moral, and transparent manner.

IBM, one of the biggest developers in digital tools that can also be used in the financial industry, issues a warning on how the advantages of AI must be balanced with its responsible and accountable use, which requires safeguards to ensure ethics, regulatory compliance, transparency, and explainability—so that stakeholders understand the decisions made by the financial institution. By creating oversight and clear standards for its use, AI may continue to evolve as a trusted, powerful tool in the financial industry.

What are AI's challenges in the finance industry?

According to a Forrester survey, 98% of institutions believe artificial intelligence and machine learning can give them a competitive edge and improve their business processes. However, 80% to 85% of machine learning (ML) initiatives fail to launch because of various logistical and managerial problems, indicating that institutions require assistance from IT and AI network professionals to complete AI projects.

Financial organisations deal with sensitive and private data daily, which puts them in compliance with several security and compliance standards in addition to logistics. Any AI solution must be able to safeguard that data and adhere to regional and industry-specific regulations, as finance is a global issue involving a wide range of businesses. A seasoned financial adviser or investment manager can spot the dangers drawing from experience and protect their clients and the organisation while keeping the customer’s goals in mind.

One of the many complicated challenges is the vast volume of data. Institutions must arrange all their data into well-organized channels and structures for Machine Learning to properly forecast and predict markets in line with particular business goals.

AI is transforming investment management and financial planning by giving advisers access to cutting-edge analytical tools, improving investment strategies, and boosting the security and efficiency of the financial ecosystem as a whole. However, implementing change requires making difficult choices, which is where the expertise of professional advisers and their years of experience prove useful.

AI will play a bigger and bigger part in the future of finance as it develops and innovates, but it is up to us to make sure that everyone who benefits from the change—investors and professionals alike—will do so.

Before letting AI take over your fianances, we suggest you talk to an experienced and qualified professional to make your financies are well taken care of. Compare Wealth Managers offers a free service to help you find a wealth manager. Simply click the orange "start comparing" button to get started.

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