The financial services industry is no stranger to artificial intelligence or AI. Financial apps use AI to perform different user tasks and help them make better money decisions. That means, when it comes to AI and personal finance, you get the kind of personalized advice and strategic help that was previously accessible only to the very wealthy.
Here’s how you can use this technological powerhouse to manage your money, meet financial goals, and grow your wealth.
AI and Personal Finance: Financial Tools
From generative text AI engines such as ChatGPT and Gemini to apps that use AI to help improve your budgeting and savings choices, such as Mint and Rocket Money, AI is already hard at work helping to manage your money.
AI-powered tools and chatbots can even deliver personalized guidance and strategy like traditional (human) financial advisors do. You can also use AI engines and AI-integrated tools to learn more about money management; with generative AI engines, you can even turn financial education into a fun game to make it painless and help you retain your new knowledge in the future.
If you’re managing your budget and want to control your spending more effectively, AI and personal finance can help. Streamline your expense management, and your app will automatically categorize and analyze every dollar you make and spend to see how well your actions support your stated goals.
Perhaps most impressively, AI’s real-time monitoring and analytics can help forecast market behavior in the future. What stocks are on an upswing? Are there rumblings of current global events that might later impact the stock market significantly? AI can find out the answers to these and other questions in seconds. Those answers, in turn, help you make even better investment decisions.
Smart Money Management with AI
AI and machine learning are already helping you manage your money more efficiently through better budgeting, spending analysis, and more.
Creating and Managing a Budget With AI
Budgeting is a key part of managing your money. Creating a budget is often viewed as an overly complex struggle, but it’s the perfect project for AI since it relies on basic math and data entry.
With apps like Credit Karma (formerly Mint) and You Need a Budget (YNAB), you can create a budget with transaction categories. Then, when the app logs your expenditures, the AI engine automatically categorizes them. Over time, the app will analyze patterns and trends. Then, you can get deeper data-driven insights into your spending and savings habits, which can help you make better decisions in the long run.
Other apps have more specialized functions that are AI-powered. For example, Cleo is a chatbot app that offers personalized recommendations to help you meet your savings goals and manage your finances more efficiently. PocketGuard, will calculate how much disposable income you have left after you pay bills and display it for you so you know immediately how much you can safely spend. The Rocket Money app analyzes spending and predicts your future expenses to help you stick to your budget.
Machine Learning for Spending
Machine learning is a type of AI that learns from its own past experience. Instead of following instructions precisely as they’re written in code, these programs examine raw data for existing patterns. Then, based on those patterns, they make their own predictions. Banking and lending institutions have begun using machine learning to help make better credit decisions and lead to more effective risk management.
By examining more than preselected information on a potential borrower, machine learning programs can make more informed decisions on whether the bank should issue a loan or line of credit. This helps to broaden access to loan products and services to those who are actually ready to manage a loan but who may not meet those rigid criteria.
AI can also do things humans simply can’t, such as instantly detecting fraud and unusual activity on an account. Thanks to AI’s ability to perform real-time monitoring of scores of transactions, it can more readily detect potential fraud and call the bank’s attention to it more quickly. Financial fraud is estimated to cost the U.S. banking industry billions yearly. As with most industries, rising costs are frequently passed along to the customer to bear in the form of higher fees.
AI in Wealth Management
AI is likewise democratizing wealth management. While using robo-advisors or specially trained and coded chatbots to offer investment advice might seem risky, AI and machine learning are broadening accessibility to these services while constantly improving the quality of their recommendations.
AI-powered investment advice relies on portfolio management algorithms and massive amounts of relevant data. These robo-advisors are available 24/7 for a lower price. For example, Magnifi is an AI-powered advisor that helps the user explore different scenarios and their impact on the user’s finances. Using AI to help users build and manage wealth also expands access to financial institutions and products in areas that traditionally lacked access.
AI-Powered Personal Finance Features
As AI-powered personal finance tools evolve and further develop, personal guidance becomes more accessible and effective. Consequently, users feel more comfortable taking greater control over their financial lives.
Financial Goals Optimization
With powerful AI and machine learning, personal finance apps help users set and track money-related goals more efficiently. By reviewing past spending patterns and income, the AI can help you set more targeted and realistic money goals, such as how much you want to save or what strategy to use in repaying debt, for two examples.
Personalized Financial Recommendations
The algorithms that AI tools use can result in targeted advice. For example, the app can detect a significant amount spent on takeout and restaurants, then suggest less expensive restaurants or other alternatives so you can still meet your objectives. For investment guidance apps, you can review a list of suggested stocks or funds that align with your risk tolerance. The end result is better financial decisions and a healthy sense of ownership in managing your money.
Banking Services Integration
Modern AI-powered personal finance tools often integrate directly with users’ bank accounts, credit cards, and even investment accounts, providing a consolidated view of their finances. This integration enables real-time updates on transactions, balances, and spending patterns, enhancing accuracy and helping users avoid overdrafts or missed payments. Some apps also allow users to move funds between accounts, make payments, and monitor their credit scores from a single platform, reducing the need to switch between different banking apps.
Managing Expenses and Income Streams
AI tools excel in categorizing transactions and tracking income, helping users understand where their money goes each month. They automatically identify expenses like rent, utilities, subscriptions, and discretionary spending, giving users a clear picture of their financial flow. Additionally, AI-driven tools can aggregate income sources for those with multiple income streams, such as freelancers or small business owners, making budgeting and tax preparation more manageable.
Understanding AI Limitations
Sometimes relying on AI advisors isn’t … well, advisable. You might be exploring a financial strategy that would actually be tricky to implement without running afoul of legal requirements or other limitations. Or maybe you’re researching how to invest a significant bulk of your retirement savings fairly close to your expected retirement date.
In high-stakes situations like these, you might consider consulting a human financial advisor. Regardless, understanding AI’s limitations in financial management tools is always a good idea.
First, AI often performs well when dealing with generalities—“How can I meet this financial goal in ten years?” for example—but may not be as effective at detailed, personalized suggestions and guidance. That may be due to the lack of the human touch since AI lacks emotional intelligence and the personal understanding that makes human judgment sometimes more accurate.
Algorithms are much like humans in one key sense: They can be quite biased. AI used in credit and loan decisions may perpetuate biases that infect the AI because they’re present in the AI model’s training data.
Data Management and Privacy
AI-powered apps and tools often require access to personal data to formulate the most targeted guidance, which presents a few concerns.
First, there’s the matter of exposure itself. The vast amounts of data that AI and machine learning, in particular, need to render the best possible results often contain sensitive financial and personal data. That much access raises privacy concerns. Even when the personal data is anonymized, it’s possible for AI to “re-identify” the person, creating a real risk to privacy.
In addition, AI models may be susceptible to a hostile attack, especially in deep learning. For instance, an attacker could introduce malicious data that changes how the algorithm processes or validates transactions, creating opportunities for fraud.
As the industry increasingly embraces AI, regulatory bodies are especially concerned about data security. Financial institutions and apps must find a balance between what AI is capable of and strict compliance standards and laws.
AI Technology Constraints
Finally, there are some inherent limitations on AI, meaning it might be capable of performing a task, but that doesn’t necessarily mean it will do it well. Some generative AI engines have already made a notorious name for themselves based on factual errors and completely made-up events and information sources.
Unreliable underlying data means you can get false or even dangerous information in return for your prompt. Remember, AI is only as accurate as the information and data it uses to formulate its output. While AI systems are (or should be) constantly improving, the output may always be fallible and imperfect to some degree.
So, while AI offers tremendous potential to improve data management and streamline services, it also presents some risks. Those risks require careful management, robust security protocols, and an absolute commitment to protect customers’ sensitive financial data.
Future of AI in Financial Services
Generative AI and large language models (LLMs) are changing how banks and financial apps work. These AI tools help predict trends, answer questions, and provide insights, making financial planning easier for everyone.
To get started with leveraging AI in your personal finances, consider these steps:
- Use budgeting apps with AI features that help track your spending and give you personalized savings tips.
- Experiment with AI-powered credit monitoring tools and apps with investment robo-advisors.
- Explore the use of financial planning apps that offer personalized insights.
- Learn more about data privacy and choose apps that handle your data responsibly.
With AI in finance apps and tools, you can make smarter financial decisions with less effort.
