By Andy Taylor, Founder and CEO of dough
Dough is a fintech startup dedicated to helping people manage and grow their money independently.
Thanks to science fiction films like Terminator, artificial intelligence (AI) or “machines” often get bad press. Robots are described as something to be feared or at least not to be trusted. However, the reality of AI is actually a lot less sexy and a lot more useful. Artificial intelligence and machine learning technologies are applied to industries ranging from manufacturing to money management to help improve efficiency and drive returns.
We all know that money can be a major source of anxiety. A recent study by FINRA find that 50% of people felt stressed when talking about their finances, and 60% were stressed just thinking about them. The main reasons for financial anxiety are: high debt, low financial literacy, and problems managing money.
Meanwhile, a recent Oracle study found that 59% of people trust a robot more with their finances than themselves. AI-powered fintechs are creating a new niche in autonomous finance, and consumers need to know how to best leverage them. AI can improve overall personal finance fitness, just like wellness and exercise apps can help improve overall health. It is a tool to help people. The key is consistency and accountability, and sticking to a plan.
Advances in AI and open banking that benefit everyday people
AI tools allow fintech companies to process and analyze large amounts of data, then apply that results to make more informed decisions. Not only are decisions “smarter”, but they can also be made faster.
Open banking, also known as open data banking, is a banking practice that helps drive innovation in the industry. It offers third-party financial service providers open access to banking, transaction and other consumer financial data from banks and even non-bank financial institutions through application programming interfaces (APIs). These interfaces allow different applications to connect with each other to share data. So, with this software, a personal finance application can import data from your bank accounts, credit cards, utility bills, loan providers, etc. and get a complete picture of your financial situation.
This data is then analyzed by AI and used to provide personalized advice, recommend financial products that might be useful, and even help make predictions about your financial future.
By using open banking, consumers, financial institutions and third party service providers can access a network of accounts and data between institutions. This information is then leveraged to streamline processes and improve financial performance and decision making. AI, data science tools, and data visualization can process complex data – and large volumes – and turn it into digestible customer insights. Machine learning is the ability of machines to become smarter and to actually “learn” from the data models they analyze. The more data that is fed into it, the smarter it becomes and the less a human needs to be involved.
What types of financial decisions and processes can be automated?
A wide range of financial activities can be put on “autopilot”. Some human guidance is needed to get started, but once in place these processes just need to be supervised. The apps are designed to do the heavy lifting and alert customers to action or change. Human intervention can occur, if the customer wants to change a savings goal, for example. Or if a major life event like a wedding or a new job arises and her financial situation changes.
For example, the initial setup of linking a direct deposit to a smart banking app is done manually by the customer. Then the customer can log into other external accounts, designate bills to pay, set savings goals, and then transfer the rest to an app.
- Budgeting – Once the app knows your monthly bills or other recurring expenses, it can calculate how much of your paycheck needs to be allocated to cover these things. Then the AI can help you decide where the rest of the money is going and how much.
- Spending – Thanks to technology, spending can be done automatically without worrying. This is because AI can set aside “free” money for discretionary spending once all the expenses are taken care of. AI can also help you see where your money is going by tracking your spending.
- Savings – Everyone wants to save, but like getting in shape, it can be a struggle. Thanks to technology, you can now set savings goals – a specific amount and timeframe – and automate the rest. AI can determine how much of each paycheck should be spent on savings. Smart banking apps can monitor progress towards savings goals and alert you when you’ve reached milestones.
- Investment – Roboadvisors are popular lately. But there are also hybrid models that call for human assistance and expertise. For example, AI can calculate how much money you have to invest, while human portfolio managers select the best combination of stocks. When it comes to wealth management, people can choose how much they want to automate.
- Credit Creation – Smart banking apps can almost provide information on how best to improve your credit score, once they’re connected to all of your credit cards, loans, and the like. Supplied with the necessary data, AI can reveal patterns that help or hinder your credit. This information can point you to different ways to build better credit.
Don’t be afraid of slots, instead harness their power
Remember when people were afraid to shop online for fear of compromising their credit cards? Well times have changed and online shopping is now the norm. The same goes with smart banking. AI and machine learning can boost financial literacy and ultimately help people live financially healthier lives.
By providing a holistic view of your finances and helping you understand how the different pieces fit together, financial technology can serve as an educational tool. AI can augment and optimize human intelligence – and automate tedious processes – saving you time (and money) so you can enjoy your life.
The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.