Writer, Jay Jackson, discusses how AI can help individuals with personalised financial advice.

Artificial intelligence (AI) is revolutionising most, if not all, industries, and the finance sector is no exception. When it comes to personalised finance, individuals can use AI to achieve their financial goals more effectively.

How AI and personalised finance advice can work together

AI-influenced financial advice systems enhance the financial decision-making process through structured steps. Here are a few examples of how these systems can work.

Data collection and analysis

AI systems begin with a thorough data collection process, which is crucial for generating accurate advice. The data collected may include:

• Financial transactions - AI systems may access users’ financial transactions through bank accounts, credit card statements, and other financial records when given permission.
• Income statements - information about users’ income is collected, which includes salaries, bonuses, rental income, and any other source of revenue.
• Investment portfolios - AI examines users’ investment portfolios, such as stocks, bonds, mutual funds, and retirement accounts.
• Personal information - demographic data such as age, marital status, number of dependents, and career stage may be collected.

Once researchers collect this data, AI systems can use advanced analytical techniques to interpret it. This might include:

• Pattern recognition - AI identifies patterns and trends in a user’s financial behaviour, such as recurring expenses, saving habits, or investment performance. Recognising those patterns can help AI predict future financial behaviours and outcomes.
• Trend analysis - by analysing long-term trends in a user’s financial data and market conditions, AI can examine how their spending patterns have changed over time, or how their investments perform in different market conditions.
• Risk factor analysis - AI assesses various risk factors that could impact a user’s financial situation. This can include market volatility, economic shifts, or personal financial challenges. This analysis helps when developing strategies to mitigate potential risks.

Risk assessment

After comprehensive data analysis, AI will move on to evaluate an individual’s risk profile and financial goals. This process involves:

• Risk tolerance evaluation - AI determines users’ risk tolerance by analysing their historical financial behaviour and reactions to market changes. This could involve looking at past investment choices. It may also include psychological tests or surveys to measure comfort with financial risk.
• Financial situation assessment - by assessing users’ overall financial health, AI can consider factors such as income, expenses, debt, and existing investments to help it understand the individual’s capacity to handle financial risks and determine appropriate risk management strategies.
• Investment horizon - AI considers the time frame for users’ investments. For example, older investors who are near retirement age might prefer more stable investments.
• Alignment with goals - AI aligns the risk profile with the individual’s financial goals. AI can customise the risk assessments to ensure that the advice aligns with objectives such as buying a home, adding to a rainy day fund, or retiring comfortably.

By integrating these elements, AI creates a nuanced risk profile that will guide its recommendations - balancing the potential for growth with its user’s comfort levels and financial capacities.

Personalised recommendations

Based on the aforementioned steps, individuals can use AI to generate personalised financial advice tailored to their needs and goals.

Investment strategies

Specific investment strategies are recommended that align with the individual’s risk tolerance and financial goals. For example, it might suggest a diversified portfolio for users with moderate risk tolerance, or a more aggressive investment approach for those willing to take higher risks.

Real-world applications for investment strategies

Two examples of real-world applications that use AI to develop investment strategies are Nutmeg and Moneyfarm.

Nutmeg is one of the UK’s most popular digital wealth managers, using AI and machine learning to create and manage diversified portfolios based on the user’s risk level and financial goals. This application offers a range of portfolios, including Smart Alpha portfolios which leverage JP Morgan’s investment insights and strategies.

Tailored to UK residents, Moneyfarm is another digital wealth management service that offers AI-driven investment advice and management. Similar to Nutmeg, Moneyfarm uses algorithms to recommend a tailored portfolio based on the individual’s financial goals, investment horizon and risk level. This is also a recommended application for investors in the UK looking for a mix of automated and human advice.

Retirement planning

Users can plan for retirement by calculating how much they need to save, recommending suitable retirement accounts and projecting future retirement income based on their current savings and investment performance.

Real-world applications for retirement planning

Two applications that can help with retirement planning are PensionBee and Moneyhub. PensionBee is exclusively UK-based, so is entirely focused only on the UK pension system to help individuals looking to get a clearer image of their retirement savings. The platform can help users consolidate their existing pensions into a single plan by providing personalised recommendations and access to retirement planning tools (such as the retirement planning calculator).

Similarly, Moneyhub equips users with the tools for budgeting, saving, and investing. It also offers specific features for retirement planning through leveraging AI to help users plan their long-term financial future. As well as retirement planning tools, Moneyhub provides scenario analysis which allows users to model different retirement scenarios and see the impact of different saving strategies.

Debt management

Users with significant debt can use AI to find strategies to manage and reduce it effectively. Platforms may include recommendations for consolidating debt, prioritising high-interest payments, or creating a budget to pay off loans faster.

Real-world applications for debt management

An application that could be useful for debt management is StepChange Debt Charity. This is a UK-based debt charity offering free debt advice and management services. While it’s a more traditional service, it has integrated AI-driven tools to help users manage their debt more effectively. Some examples of what StepChange can offer include debt management plans, a debt remedy tool, and budgeting support - all while focusing entirely on the UK market.

Budgeting

AI assists users in creating and maintaining a budget by analysing their income and expenses. It suggests ways individuals can cut costs, increase their savings, and manage their spending.

Real-world applications for budgeting

Financielle is a UK-based financial wellness application that focuses on helping users manage their budgets, save money, and reduce financial stress. They use their own experience and knowledge paired with AI-driven insights to help users create and stick to a budget, while also setting and achieving financial goals.

Emma is another popular UK-based budgeting application that helps users track their spending, manage subscriptions and save money. It uses AI to provide users with insights into their financial habits and suggests ways to improve their financial health. Users may use this app to identify recurring subscriptions and assess whether they should cancel them, as well as receive AI-driven insights and advice relating to their spending habits.

Final thoughts

AI is transforming the landscape of personalised financial advice, offering individuals more accessible, affordable, and customised solutions to manage their finances.

By leveraging AI’s capabilities in data analysis, risk assessment, and goal setting, we can make more informed financial decisions and achieve our financial goals with greater confidence.

Nevertheless, as with any technological advancement, it is essential to approach AI-powered financial advice with a critical eye and consider the challenges involved. By balancing its potential with human judgement and ethical practices, we can harness the power of AI to create a more inclusive and effective financial advisory ecosystem.

Develop your knowledge in finance

At Kaplan, we can support you in developing your finance knowledge with our professional courses and apprenticeships so that you can feel confident in your ability to offer advice and services. From training within the accountancy and tax, banking and finance, or data and technology sectors, you’ll certainly find the perfect course that will help you upskill and excel.