How AI Impacts the Personal Finance Mobile Apps

Personal finance apps have proven to be a reliable tool for managing money and increasing personal wealth, effectively helping us with tasks such as tracking expenses, budgeting, and investing. The growing adoption of artificial intelligence allows such products to be even more helpful to end users through fast and high-quality data processing, task automation and improved security. In this article, we’ll talk about how AI-powered solutions are changing the personal finance market.

The Current State of the Personal Finance App Market

The fintech market is full of money management software offerings. Here you will find solutions for different needs. For example, budget tracking apps help you keep track of different budget categories and manage your expenses and income. Financial assistant apps allow you to collect financial information from all your accounts, set financial goals and get advice on achieving them. Saving apps are designed to automate savings and help build savings habits. 

Despite the app type, users are hungry for new features to help them manage their finances more effectively and invest more intelligently. Artificial Intelligence further alters this rapidly-expanding industry. The killer apps of the coming decade will be those that take advantage of the full potential of feature-forward AI. According to Research and Markets, AI in the fintech market size is expected to reach $41.16 billion by 2030, growing at a CAGR of 16.5% from 2022 to 2030.

Benefits of Using Artificial Intelligence in PFM Apps

Building personal finance apps like Mint, Personal Capital, or Prism is a popular fintech startup trend, and adopting AI allows you to create more engaging, efficient and technologically advanced solutions. AI automates the money management process and helps to turn an app into a digital financial advisor.

With the same deep understanding and decision-making power that AI brings to the forefront of application security, AI takes personal finance to a new level with algorithmic trading, predicting the movement of stock prices while pulling the trigger on trades with jaw-dropping effectiveness. Big names like JP Morgan made large investments in Algo-Trading after seeing huge gains in the performance of traders with the help of AI assistants.

In addition to trading, artificial intelligence helps users gain valuable insights into their financial data, allowing them to find savings opportunities. Solutions equipped with an OCR module with machine learning also allow the application to scan receipts, automatically translate scanned images into text and enter this data into expenses categories. And a conversational engine can give your users the ability to rely on voice commands to check balances, for example.

Improved Customer Experience With Chatbots

The days of “Press 1 to speak to an associate” are coming to an end, as year by year, AI assistants creep closer to parity with human agents. New leaps in generative text transformers give AI assistants a human touch, even if the user is aware that they’re speaking to a chatbot. The AI chatbots of the present can answer much more complicated queries and also can onboard clients and deal with account issues, parsing the real meaning of a client’s text or voice input.

One of the principal benefits of AI chatbots is their always-on availability, giving customers a realistic alternative to speaking to a human agent outside of regular business hours.

Data-Driven Financial Decisions With Predictive Analytics

Following the digitalization trend, fintech developers should take into account the power of artificial intelligence for data analysis. The key advantage of AI is its superior pattern recognition abilities. Relying on statistics and modeling techniques, AI algorithms process the historical data of account transactions. Thanks to this, the system can make predictions about future users’ income and expenses, allowing users to plan their budget more accurately. Thus, the user gets much more than just a spending tracking application, and the creator of such a product gets a better chance of success in the market.

However, you should remember that AI implementation as part of the fintech app development process requires experienced software developers who know how much data is enough to create an effective AI model and how to build a solution that meets all the business goals of the project. 

Enhanced Security With Fraud Prevention Mechanism

Money-related applications require advanced security features. A landmark study by Provenir discovered that fraud prevention is the biggest driver for investments in AI projects. The study drew from a pool of 100 key decision-makers in the fintech industry across Europe, and 90% of those figures plan to adopt AI-enabled risk management software to combat fraud.

AI is particularly good at spotting potential cases of fraud, utilizing massive training data sets to make inferences that human agents might not. AI is trained on a countless array of different security scenarios and can automatically prevent many cases of identity theft, unauthorized account access, and malicious activities with a speed that simply cannot be matched by human agents. 

Wrapping Up

There’s no way to avoid the importance of AI when designing a current or next-generation personal finance product. Pivotal advantages such as improved security and fraud detection, dynamic customer support, and AI-powered money management make AI a baseline requirement rather than an optional feature.


Maksim Bieliai, 

BA Team Leader, Fintech Market Analyst at MobiDev