Best Financial Planning Software For Advisors 2020 – Financial well-being makes us feel safe and secure, and personal finance software helps us do that by analyzing our spending habits, telling us how to save money, how to grow capital, and how to reach our financial goals. The best way to make money management software as good as possible for users and therefore more successful in the market is to empower it with artificial intelligence. This guide will answer all the important questions about how to create that personal finance program.
The global economy has begun to recover from the Covid-19 outbreak, but a full recovery is still far off. According to a Charles Schwab survey, 53% of Americans have been financially affected by this pandemic. Due to this situation, the issue of better management of personal finances has become very important, and tools designed to help with this are needed more than ever.
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According to Verified Market Research, the global market for personal financial software is expected to reach $1420.96 million by 2026, and according to NMSC this figure may grow to $1.80 billion by 2030, with a CAGR of 6.1% from 2020-2030.
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One of the main trends in personal finance software is the use of artificial intelligence technology. According to Mordor Intelligence, the global artificial intelligence fintech market was valued at $7.91 billion in 2020 and is expected to reach $26.67 billion by 2026.
AI money management tools help users get the most out of their budgeting and investing. Personal finance software solutions based on learning algorithms allow you to adjust financial recommendations based on the user’s spending habits. Not surprisingly, a large portion of the personal finance market is owned by robo-advisors that offer automated financial planning solutions and AI budgeting applications.
Personal finance software or personal finance assistant is software that helps users manage their money more intelligently. Such software can perform many functions, from monitoring expenses and income to providing advice on the most suitable investment options. Some apps can also manage subscriptions and get better rates for your bills. For example, TrueBill automatically analyzes a user’s bills and finds the best ways to save.
Artificial intelligence financial assistants can also be applications or programs linked to personal bank accounts. In the second case, the user will have more opportunities to manage and control his expenses and income, as the program will automatically pull data such as transaction history.
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The open banking standard, which is gaining popularity in the US and Europe, enables the secure exchange of user data between banks and fintech applications with user consent. This mode helps to automate data flow and gain more meaningful insights for better financial advice. As of March 2021, there were 502 registered Banking Service Providers for 502 Banking Service Operators (TPPs) in Europe. Also, according to Statista, in 2020 the number of free banking users in Europe was approximately 12.2 million and this number is expected to reach 63.8 million users by 2024.
Before getting into the question of how to build a personal finance program, let’s find out what types of programs are on the market. According to the functions they provide, personal finance applications are divided as follows:
It is worth noting that many personal finance applications combine several types into one to provide a better user experience and provide complete financial management services. Which features to choose for your program need to be decided. We recommend that you look at your business goals, the needs of your potential users, and market trends to help you make your decision.
To get a big picture of how to develop a personal financial assistant with artificial intelligence from the technical side, you must first create an initial list of components of your financial software solution. Let’s start with some of the functions that form the basis of any money management software. Here are the features users can expect to see by default when they download a financial assistant app and some quick tips on how to implement them correctly:
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The line between simple money management software and a powerful financial assistant comes down to the use of artificial intelligence. Designed correctly, personal finance applications with artificial intelligence can be a perfect replacement for human financial advisors, providing the same level of customer service. So, let’s look at the top four features based on AI technology. Here are some ways you can make your money management software even better.
The issue of security cannot be ignored when talking about building applications for the financial market. Security is one of the main decision-making factors for consumers when choosing financial software. If you plan to connect your application to users’ bank accounts and credit cards, you must ensure that this process is completely secure and that user data will not be lost or compromised. This is an area where artificial intelligence can show its full power.
According to IBM, 20% of data breaches are caused by compromised credentials. Biometric authentication technology is considered one of the most secure ways to protect data. Modern algorithms can easily guess the correct account password, but they cannot destroy the unique characteristics of users.
Biometric technology can be implemented through facial recognition, iris scanning, fingerprint identification or voice authentication. However, each option has its own implementation characteristics. For example, creating an iris scan on phones and desktops is impossible without special equipment, because the resolution of standard cameras is not enough.
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According to Statista, facial recognition is one of the top three AI technologies being adopted worldwide. Let’s find out how it works.
In order for your face recognition system to work correctly and avoid errors, it is important to use anti-spoofing techniques that will find the difference between the real face and the replica.
Artificial Intelligence is that magical tool that can transform software into a financial assistant that interacts with users in a human-like way. Instead of looking up information in an app, a user can ask something like “Hey, what’s my credit card balance?” and get a voice response. Conversational AI enables. Based on Natural Language Processing (NLP) and Natural Language Understanding (NLU) technology, the chat engine enables seamless communication between the financial software and its users. Let’s see how it works.
AI voice assistants use the device’s microphone to receive voice requests. First of all, they need to recognize the command (wake word) that helps to wake up the device, since normal helpers usually just listen. Plus, when it’s turned on, voice recognition, audio analysis and language processing go to work and the magic happens.
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A properly trained chat engine makes interacting with financial software easier and increases user engagement while interacting with the software. Developing such a module requires deep expertise in artificial intelligence and machine learning algorithms.
Another powerful AI capability to build Fintech applications is predictive technology. Thanks to that, personal finance assistant programs can identify user behavior patterns, as well as make predictions about future users’ income and expenses. This happens due to statistics and modeling techniques. Predictions are made based on historical data of account transactions powered by machine learning algorithms. AI financial planning software with predictive analytics will allow users to set financial goals and tell them how best to achieve them, acting as a true financial advisor.
When it comes to giving financial advice and recommendations, due diligence is also involved. Basically, this technology takes what predictive analytics has learned and goes a step further by determining the best course of action in a given situation. However, you should know that this analysis module is a complex solution that requires deep knowledge of the industry and technology and a large amount of historical data.
If you’re going to develop a personal finance assistant app like Expensify, you’ll need a recipient recognition feature that allows you to scan receipts and automatically enter expenses into the app. Expensify offers a SmartScan feature based on character recognition (OCR) technology that streamlines the data entry process and translates scanned images into text. It reads the vendor, date and amount of the transaction, generates the cost and enters this data into the cost report. Sounds simple right? However, from a technical point of view, the process seems more complicated.
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To ensure bill recognition, the system extracts text from your bill image and analyzes it to determine which data matches the system’s built-in categories, such as date, amount, currency, and so on. After that, the module analyzes the existing usage categories and finds the appropriate ones to add information from the new account.
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The main challenge of implementing this feature is that the accounts can be presented in different formats, which makes it difficult to analyze the information and its further distribution. This is where you need the best machine learning models. AI and ML will allow you to prevent errors occurring in the data conversion process and efficiently process different types of documents thanks to advanced algorithms. Also,
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