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AI and ML in Financial Planning Apps: Applications, Cost, and Case Studies

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12 min read

Embracing the era of AI-powered solutions, financial software has evolved into intelligent assistants, with AI finance apps leading the charge. From simplifying budgeting to optimizing investments, AI financial advisor apps have taken the world of financial planning, offering personalized financial assistance at our fingertips.

Relying on our extensive experience working with Artificial Intelligence and Machine Learning, in this article we will uncover how and why to integrate these technologies into your financial apps and gain a competitive edge in today’s market.

Table of contents:

AI/ML in the Financial Software Market

What is an AI Personal Finance Management App?

Top 6 Applications of AI/ML in Financial Planning Software

AI Financial Planning Software Benefits

Examples of AI Financial Planning/Advisor Apps

AI Personal Finance App Cost

The Future of AI in Finance

How HQSoftware Can Help You with Personal Finance App Development?

AI/ML in the Financial Software Market

Artificial Intelligence and Machine Learning are two of the most influential trends in building personal finance apps today. The ability of AI to analyze trends, make predictions, gather insights, and offer solutions to problems has proved beneficial for many fields of business.

Financial companies are recognizing the benefit as well. It is estimated that by 2028 the application of AI in FinTech will be worth up to $49,43 billion.

Apart from the improvements AI and ML offer to FinTech products, there is another great perk to using advanced tech: higher interest from venture funds. Investors now see great potential in the advancement of Artificial Intelligence and are ready to back companies that offer enhanced solutions with advanced technologies.

Personal finance market is also rapidly growing and is expected to reach $1,91 million in 2026.

What is an AI Personal Finance Management App?

Personal finance management applications help track an available budget, reach saving goals, and improve investing. There is no need for numerous spreadsheets anymore, as you can automate financial management and keep data in one place.

If an app is linked to your bank accounts, it automatically tracks incomes and expenses in real time, even further reducing manual work. Thus, you can decrease errors and always have access to financial information with several clicks.

AI personal finance apps offer you even more opportunities to improve your financial habits. For example, Artificial Intelligence can provide investment options based not only on your preferences and capabilities but also on advanced market forecasts. The technology also keeps your data safe and provides comprehensive insights into your financial status.

Professionals and companies also use tools for financial management, but most often as a part of their comprehensive financial systems. However, AI and ML can enrich such systems too.

Top 6 Applications of AI/ML in Financial Planning Software

Artificial Intelligence makes analyzing big volumes of data and pulling relevant insights easy, which puts it in the spotlight with the financial industry.

AI and ML have proved useful to a wide variety of financial operations, such as banking and credit offerings, asset management, personal financing, and so on.

Let’s take a look at some of the most helpful applications of AI/ML in financial planning software.

Data-driven decision making

One of the most important factors in financial planning is making timely decisions. It requires analyzing a huge amount of data, which is almost impossible for a human without the help of advanced solutions. This is where software powered by cutting-edge technology comes in handy.

AI finance apps are great at identifying patterns from sifting the data it gathers. Its inherent efficiency at handling large volumes of information helps it make the most accurate predictions on, for example, market behavior.

2 ai in fintech applications decision making - AI and ML in Financial Planning Apps: Applications, Cost, and Case Studies
Data-driven decision making

Artificial Intelligence can be used in many ways to help users get the most out of a financial app. Among those are:

  • Automated loan approvals;
  • Budgeting tips;
  • Investment management assistance;
  • Automated operations based on pre-determined rules.

Fraud detection

Another field where Artificial Intelligence and Machine Learning can help financial software is in detecting fraud. How does AI do it?

AI can analyze transaction information, find inconsistencies in different payment documents, and identify fraudulent behavior. Using all of the data available, AI personal finance apps are able to detect any kind of unusual activity.

What’s even more effective is that it can apply predictive analytics to alert users about the potential risk of fraud.

To enhance fraud detection capabilities, companies can implement solutions that check  images and documents to find traces of digital manipulation that would otherwise trick human observers.

3 ai in fintech applications fraud detection - AI and ML in Financial Planning Apps: Applications, Cost, and Case Studies
AI for fraud detection

Customer experience personalization

The financial sector, just like any other field of business, aims to improve the experience of customers. The secret lies in understanding the problems customers face and coming up with effective solutions.

With the help of Artificial Intelligence, AI personal finance apps can more effectively analyze users’ information and their behavior, such as comments, clicks, and transactions. All of that data can be used to improve interaction between the user and the software, as well as generate personalized recommendations.

And there’s one more benefit: As customers continue to interact with the software, AI will get better at recognizing their behavioral patterns and offering the right services. Regular customers can expect better advice on asset management, more accurate risk calculation, flexible rates, and more.

4 ai in fintech applications customer experience personalization - AI and ML in Financial Planning Apps: Applications, Cost, and Case Studies
Customer experience personalization

Customer service

Traditional customer support has its drawbacks, which include:

  • long queues;
  • difficulties in explaining certain problems over the phone;
  • chatbots that are clueless for the most part — all many of them do is redirect the customer to endless FAQs.

But Artificial Intelligence can improve the situation, making solving customers’ issues quick and efficient without the need for a customer service agent to engage.

Powered by AI, advanced chatbots are able to apply natural language processing to understand the customer’s problem, whereas regular chatbots can only understand a certain number of phrases and struggle to grasp complex sentences.

Automation can happen through the chatbot. For instance, chatbots can manage claims from users, conduct transactions, and review information that the customer provides.

All of this can be done without human intervention, which removes the need for a customer to wait their turn on the phone. This allows customer support agents more time to address more complex issues.

5 ai in fintech applications customer service - AI and ML in Financial Planning Apps: Applications, Cost, and Case Studies
AI for customer service

So, what about those more complex issues?

Even though AI-powered chatbots are more powerful than ever before, they can’t do everything. In some cases, customers might still need a real human’s assistance.

But here’s the next best thing: AI chatbots can analyze the issue and assess its complexity on their own. If they decide they can’t help with the problem, they will send the customer to a support agent.

Data management

Financial operations are conducted on the basis of huge volumes of data from a wide variety of sources. Managing it could be a nightmare.

Sure, paperless management makes this more convenient, but it’s not enough. There is simply too much information to deal with, and too much possibility of wasted time and human error when analyzing it.

Artificial Intelligence makes a huge difference.

Natural language processing, text analysis, data analytics, and predictive analytics allow AI finance apps to extract deep insights beneficial to the decision-making process.

6 ai in fintech applications data management - AI and ML in Financial Planning Apps: Applications, Cost, and Case Studies
AI for data management

For instance, Machine Learning can be implemented into software to recognize information from scanned documents. Despite the abundance of document templates and the quality of scanning, an ML-powered solution can successfully identify relevant information and digitize it.

7 ai in fintech applications invoice scanning - AI and ML in Financial Planning Apps: Applications, Cost, and Case Studies
AI-powered software is able to recognize information from invoices and organize them into an e-form with editable fields

Predictive modeling

The ability of AI to analyze huge volumes of historical and behavioral data is beneficial in one more way. It allows AI financial planning software to feature predictive modeling, to provide personalized financial recommendations tailored to individual financial goals and circumstances. For example, it can provide advice on optimized investment strategies, budgeting tips, and debt management.

Predictive modeling is also closely related to risk assessment and management. An AI assistant for budgeting can forecast potential market fluctuations, identify risk factors, and provide users with a better understanding of their portfolio’s risk exposure. And then, again, offer recommendations on how to allocate available funds, leading to more informed decisions.

AI Financial Planning Software Benefits

Artificial Intelligence and Machine Learning have many applications in financial software thanks to the numerous benefits they can bring:

  • erasing friction;
  • reducing repetitive work;
  • eliminating human errors;
  • saving money;
  • improving security; and more.

Erasing friction

With advanced chatbots, financial software vendors are able to offer 24/7 customer support that is quick and effective at solving customers’ issues.

Reducing repetitive work

Powerful algorithms allow for automating simple tasks, saving time, and sparing staff a lot of repetitive work.

Eliminating human error

An AI finance app always makes decisions based on data and never on emotion. It helps to keep users from acting irrationally.

Saving money

Automation and fast but accurate decision-making helps even a small team of specialists be more effective. On top of that, AI in financial software development enables advanced risk management and fraud detection to protect you and your customers against financial losses.

Improving security

The flagging of fraudulent activities and timely alerts help customers keep their finances protected.

8 benefits of using au in financial planning - AI and ML in Financial Planning Apps: Applications, Cost, and Case Studies
AI benefits for financial apps

Examples of AI Financial Planning/Advisor Apps

There are plenty of financial software developers that have already recognized the power of Artificial Intelligence and Machine Learning in finance management.

Here are just some of them:

Talking finance management app 

Cleo is a personal AI money management app. Available for iOS and Android, it provides personalized spending breakdowns and budgeting tips. 

It can be connected directly to the customer’s bank account and supports sending money through Facebook Messenger.

In addition to all those smart things Cleo can do, it allows customers to sort of talk to the app about their budgeting.

Cleo uses an AI-powered chatbot that can review the customer’s budget. The customer then can ask whether they can afford a certain purchase and receive an answer.

9 cleo app - AI and ML in Financial Planning Apps: Applications, Cost, and Case Studies
CLEO has an AI-powered chatbot that users can talk to

Gamified personal finance assistant

MintZip is an AI budget app that has gone far beyond just showing transaction information. The app uses conversational AI as a companion that can help users better manage their finances and have a good idea of how much money they have.

In addition, the app provides budgeting tips and even sets challenges for its users: for instance, it can challenge them to save 10% of their monthly income for half a year.

10 mintzip app - AI and ML in Financial Planning Apps: Applications, Cost, and Case Studies
MintZip offers gamification and AI-powered financial insights

Fintech solution with auto-saving

Wizely is another AI financial advisor app. Like other apps, Wizely monitors the customer’s spending and provides information in the form of dashboards. 

It also offers an auto-saving feature that allows the user to set a goal and then helps with daily, weekly, or monthly savings.

Based on the information it gathers, the app provides personalized finance management tips.

11 wizely app - AI and ML in Financial Planning Apps: Applications, Cost, and Case Studies
Wizely relies on AI to provide budgeting tips and has an auto-saving feature

AI Personal Finance App Cost

Now that we’ve covered some of the benefits and applications of Artificial Intelligence and Machine Learning, it’s time to talk about the costs of AI and ML financial software development and spendings on building personal finance software solutions.

The first thing you should know is that there is no universal pricing for creating an AI personal finance app as well as AI app development in general.

Frame 29 min - AI and ML in Financial Planning Apps: Applications, Cost, and Case Studies

Want to implement AI into your finance management app?

HQSoftware provides the expertise you need to build the project. Let’s collaborate!

Anna Halias
Business Development Manager,

To know how much exactly you will spend on developing it, you need to keep in mind major variables that influence the cost:

  • required features of AI financial advisor app;
  • development team composition and rates.

Let’s review each of these separately to see how they impact the overall cost of AI financial software development.

Main features of AI personal finance apps

The main difference between a regular personal finance app and an AI assistant is the ability of the latter to learn using information it pulls from the user’s bank account.

Not only does it display transactions and let the user track savings, it also gives tips on how to effectively manage the user’s budget.

So, what are the features that let a finance app act as an assistant?

  • Financial data management. An AI finance app is able to chew through large volumes of data quickly and deliver important insights to the user.
  • Conversation engine. Another common feature is Natural Language Processing, which lets the app understand human language. This makes interaction between the user and the software easier by shortening the learning curve.
  • Financial coaching. Using predictive analytics and big data, the app is able to analyze transaction info and offer financial management tips. This is helpful for users struggling to save or just stay within their budget.

The logic is simple: the more of those advanced features required to develop a personal finance assistant, the higher its cost.

12 ai finance app development cost  the features - AI and ML in Financial Planning Apps: Applications, Cost, and Case Studies
Major features that go into the AI financial assistant

Now, let’s talk about the development team.

Development team composition

Having found a software development company that will build the project for you, you may be presented with a couple of different cooperation models.

The way you cooperate can also influence the cost of the software.

 A dedicated development team is the most effective cooperation model, so let’s take a look at how such a team is composed. 

Keep in mind that when working with a dedicated team, you can alter the cost of the project by scaling the size of your team. 

Who’s on your team depends entirely on what you need for a project. Roles can include:

  • Business analyst: Checks the financial feasibility of the project and helps to create the project specification.
  • Project manager: Estimates the scope of work, breaks the project into tasks, assigns those to the developers, and keeps the client updated.
  • Developers: Build the software solution.
  • QA testers: Check whether the app runs well.

Depending on your project needs, you can hire a full-fledged team or just select a few specialists.

Below is a rough estimate of costs for a personal finance assistant. The actual cost will vary depending on your project needs, so be sure to contact us for a definitive cost breakdown.

13 ai finance app development cost  the team - AI and ML in Financial Planning Apps: Applications, Cost, and Case Studies
The development team composition also influences the costs

The Future of AI in Finance

As the financial world continues its rapid transformation, the future of Artificial Intelligence in finance appears more promising than ever before.

Apart from the opportunities for the financial sector mentioned earlier, AI can also enhance financial solutions with algorithmic trading, predictive analytics, robo-advisors, and many more.

However, for users, the primary advantage of AI in finance planning apps lies in its ability to provide a high level of personalization. Around 66% of users expect companies to understand their needs, making personalized recommendations a crucial aspect of modern financial apps.

Once users experience AI-powered planning apps with advanced features and personalized suggestions, they are unlikely to revert to traditional apps lacking such capabilities. By leveraging AI for budgeting and investing, users can receive personalized budgeting plans, make informed and profitable decisions, and allocate financial resources according to their unique circumstances.

Nevertheless, we can’t forget that humans still need humans. Certain financial decisions entail emotional complexities that require empathy, understanding, and the human touch. While AI finance apps offer unparalleled convenience and data-driven insights, human advisors bring essential qualities like intuition and emotional understanding to the table.

Striking the right balance between AI-driven automation and human interaction will ultimately enhance the financial sector, paving the way for a more inclusive and prosperous financial future.

How HQSoftware Can Help You with Personal Finance App Development?

As you can see, applying AI for budgeting and other financial applications is extremely beneficial for those who need to take their financial app to the next level. You can improve security, save operational costs, and boost customer satisfaction. But at the same time, AI app development requires extensive hands-on expertise.

Having worked with numerous fintech projects, our software specialists gained vast knowledge of how to deal with common and specific AI financial software development challenges. We know how to ensure uninterrupted streaming and display of large data sets, enable the system to recognize and process financial information in different forms, and create a solution that complies with local legislation.

We provide end-to-end AI app development services from consulting to deployment and ensure a quick start from 2 weeks to a month to bring you the value of advanced AI money management as soon as possible. Feel free to contact us to learn more about how we can help you with personal finance app development.

Andrei Kazakevich

Head of Production

Oversees all production processes and manages the Quality Assurance department. Develops the company’s IoT, AR, VR, AI, and ML expertise.

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Frequently Asked Questions

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What is an AI assistant?

What technology is used in AI?

How is Machine Learning used in finance?

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