Reinventing Personal Finance Management with Artificial Intelligence

The software for personal finance management (PFM) aims at automation and simplification of routine tasks. As a term, PFM appeared almost 40 years ago, when Scott Cook came up with an idea to help his wife with paperwork related to paying bills. That’s the story of how Scott ran into Tom Proulx who created the first check-balancing PFM program. 

A broader range of programs and applications for personal financial management in areas of income, spending, savings, investing and others have appeared since then. Keeping in step with modern technologies, PFM software may be given a second wind by Artificial Intelligence. According to Mordor Intelligence, AI in the Fintech market is projected to reach $26.67 billion by 2026, and AI in finance management occupies a significant part of the aforementioned market.

The Key Challenges of Personal Finance Management 

The amount of people using Excel sheets for personal finance management is permanently decreasing as their choice now centers on mobile applications that are more convenient to use. However, any mobile application or similar solution should be aligned with issues of PFM. The key challenges of personal finance management include the following:

• Incorrect planning
• No clear vision of how to split the money for different needs
• Lack of consistency between earnings and expenses
• Irregular savings
• Unclear objectives
• No emergency fund
• Difficulties related to establishing and monitoring investment funds
• Neglecting tax breaks
• Spontaneous expenses that increase the debt
• No monitoring of the credit score

Besides challenges, there are the main principles of PFM to consider: evaluation (includes consideration of income-generating and expenditures alternatives), prioritization (foresees focusing on efforts that bring money and their proper distribution), moderation (adherence to the financial plan – a form of discipline against the temptation to spend more).

Modern money management tools are built in accordance with these challenges and principles of PFM. Their number is increasing along with the other alternative financial solutions. This is where AI and machine learning are the driving force behind the development of the fintech market. 

Digital wealth and financial applications built with AI or machine learning algorithms help users gain insights related to available investment options and financial health, simplifying the formation of both short-term and long-term financial plans. 

How Artificial Intelligence Changes the Rules

There are different types of AI-powered money managing apps, but AI personal financial assistants are the most popular of them. AI financial assistants allow users to track their expenses and incomes, and find effective ways to save and invest. Thanks to smart algorithms, these applications analyze incoming information and provide smart money management tips based on this data, just like a real financial assistant.

PFM and AI financial assistant applications are designed to tackle challenges and manage money more wisely. This is achieved through a variety of functions:

 

• Accurate tracking of expenses and incomes

 

AI may automate expense and income management, improving visibility, making reports more accurate, and minimizing the risk of expense fraud. Technologies that are applied to achieve these goals include quantitative analysis for data processing and Optical Character Recognition (OCR) which automates converting paper receipts, contracts or invoices and image files into digital machine-readable documents. OCR allows companies to minimize manual data entry, reduce errors, and achieve fast data processing.

 

• Smart Budgeting

 

Having a clear and visual idea of ​​where your money is going makes it much easier to manage your budget. Smart budgeting includes NLP and other analyzing methodologies, among them, sentiment analysis to evaluate asset classes, which is useful for traders investing in stock. Another prominent part of Smart budgeting is an AI forecasting tool that predicts expenditures and potential revenue based on the history data. 

 

• Smart Budgeting

 

Smart Budgeting foresees NLP and other analyzing methodologies, among them, sentiment analysis to evaluate asset classes, which is useful for traders investing in stock. Another prominent part of Smart Budgeting is an AI forecasting tool that predicts expenditures and potential revenue. Reporting, planning, and automating AI capabilities form the icing on the cake and significantly improve AI financial assistant.

 

• Automated saving and investing

 

AI-powered applications allow consumers to save extra money, while banks and other financial institutions can use them to offer competitive advantages and benefits. This generates the demand for AI app development services from financial companies. 

Here is a short list of how financial institutions can benefit from partnering with personal finance management startups:

• Attraction of new customers, especially young people who are thrilled about AI saving capabilities (according to Cornerstone Advisors, 16% of Millennials apply automated saving tools).
• Increase in customer engagement (banks can advise their clients on how to enhance their saving strategy).
• Additional income generation (banks or financial institutions that provide users with AI saving applications can charge monthly fees or fees based on the number of services).
• Drafting personalized reminders (users are reminded of following their saving strategy. it is also possible to notify them about potential dangers like running out of money due to high expenditures)

 

• Risk assessment & financial advisory

 

Machine learning algorithms can also serve for the analysis of financial activity, credit cards records, loans, and payment habits. This data helps to find errors or inconsistencies and make strategic financial decisions. As a result, the amount of repetitive work is reduced, and human errors are eliminated.  

AI analyzes expenditures and behavioral patterns to come up with ideas of how consumers can save money, offering relevant financial advice and even making forecasts regarding the financial future.              

The Future of AI in Fintech

AI technology is one of the tools that makes fintech so much more effective than traditional financial apps. AI algorithms are used to simplify decision-making processes, improve customer support, detect frauds, assess risks, and enhance personal finance management. 

If we dive deeper into AI use cases in the fintech industry, we can find out a diverse number of ways to execute implementation:

• An AI platform that assesses the potential borrower profile (it works efficiently even if there is no available credit information or history).
• ML platform to check customer behavior and avert suspicious financial operations.
• Built-in AI features for data analysis and document assessment.

This is not a complete list of the ways artificial intelligence can drive the development of the financial market. By accelerating the pace of adoption of this technology, now not only companies but also ordinary users can get a smart money management tool that will adapt to the needs of each user.