The finance industry is one of the tech-enabled industries that always uses the latest technologies to streamline operations or enhance client experience. The robo-advisor platforms are trending in the finance sector right now, used for providing personalized financial and investment advice and managing portfolios based on set preferences.
Experts predicted that the global robo-advisory market will be worth $41.83 billion by 2030, increasing at a CAGR of 30.5% from 2024 to 2030. Another report shows that there will be 34.1 million users in the robo-advisors market by 2028.
Considering the growth in the coming years, it is the right time to invest in robo-advisor platform development. In this blog, we have provided a detailed guide to developing a robo-advisor platform tailored to your business. So, without further delay, let’s begin.
What is Robo Advisor and How it Works?
Let’s start with a brief introduction to robo-advisors and their workings. The robo-advisor consists of two words – Robo, meaning robot, indicating automation in this context, and advisors, meaning consultants.
Robo-advisors are digital platforms that leverage financial data and high-end algorithms to provide personalized financial or investment advice/consultations tailored to specific financial goals.
These advisor platforms often automate the buying and selling of assets based on the risk involved, asset performance, market conditions, and more. Moreover, these continuously monitor the portfolio performance and rebalance or readjust it as needed, to ensure efficient portfolio management.
The robo-advisor platforms leverage artificial intelligence and machine learning capabilities to understand past financial data, such as cash flow, risks involved, potential returns, and more, and based on these insights, they offer personalized data-driven consultations that align with the client’s financial goals.
All the consultations offered by robo-advisor platforms are backed by data, which is why they are usually accurate. We are using “usually” here because the accuracy depends on various factors, such as data quality, machine learning algorithms, etc., which vary from platform to platform.
Benefits of Building a Custom Robo-Advisor Platform
In this section, we will discuss the advantages of building a custom robo-advisor platform for a business.
- Automation
The robo-advisor platforms offer financial advice, consultations, and managing client portfolios with minimal or human intervention.
The platforms leverage machine learning algorithms that analyze the finance data and provide recommendations, reducing the need for a workforce.
- Accessibility
Unlike human finance advisors, the robo-advisor platforms can provide consultations 24/7.
Moreover, these platforms eliminate geographical boundaries, as clients from different countries can access robo-advisors to get AI-based financial consultations from the comfort of their place.
- Personalization
In the fintech sector, every client has distinguished financial goals and objectives. They require tailored pieces of advice and consultations that help them fulfill their requirements.
The robo-advisor platform development allows finance businesses to offer personalized financial consultations and asset management services that align with their client’s specific objectives.
- Data Insights
Clients provide their financial data, such as asset holding, liabilities, risk-taking capacity, and more, to use AI-powered advisor platforms.
Finance businesses use this information provided by clients in different areas, such as creating financial products, schemes, and services.
- Revenue Generation
Last but not least, the robo-advisor platforms can help finance businesses generate revenue.
These platforms enabled by artificial intelligence can generate recurring revenue by offering subscription-based financial services.
Now, that you have understood the advantages of creating a robo-advisory platform, let’s jump straight onto its development process.
Step-By-Step Process to Develop a Robo Advisor Platform
The following is the step-by-step process of developing a robo-advisor platform
Step#1. Planning and Research
The first thing to do when developing a robo-advisor platform is to plan the development and research the market.
You need to determine the objective of creating a robo-advisor platform; portfolio management, retirement planning, asset allocation and management, and more.
Also, you need to understand the latest market trends, potential users, competition, and finance regulatory requirements, such as Know Your Customer (KYC), and Anti-Money Laundering (AML).
Step#2. Setting Up a Development Team
Robo-advisor development is a complex job. You need professional assistance from experts to build your platform. So, you need to set up a development team that consists of:
- Project managers
- Software developers
- Data Scientists
- UI/UX Designers
- Tester and Quality Analysts
You can either hire dedicated developers or outsource the project to a leading AI development company to build your AI-enabled advisor platform.
Step#3. Designing the Platform
After setting up the development team, begin with designing UI/UX for the robo-advisor platform. Your focus should be on offering a simple, intuitive, and visually appealing interface for the users.
Also, you need to ensure that the UI designs are perfectly aligned, with different platforms like Android and iOS, and devices, such as desktops, phones, tablets, and more, to offer an enhanced user experience.
Step#4. Developing the Core Algorithm
At this stage, you need to gather and refine historical and real-time financial data to train the platform.
Also, your AI developers will create high-end financial algorithms that are used to analyze data, assess risks, and provide recommendations by the robo-advisor.
Moreover, implement artificial intelligence and machine learning models to enhance the accuracy of the platform and on-point advice to users over time.
Step#5. Building the Robo-Advisor Platform
Once core algorithms are developed, proceed with building the robo-advisor platform. Create the frontend using HTML, CSS, and Javascript.
Similarly, build the server-side logic, databases, and application programming interface (APIs) to support and enhance the platform’s functionalities.
Also, implement robust security measures and protocols to protect user data from potential cyber-attacks.
Step#6. Testing and Quality Assurance
Post development, test the robo-advisor platform to identify bugs and fix them, if you find any. Also, you must use the AI advisor on different devices and platforms to ensure it is providing a consistent user experience.
Moreover, you can release a Beta version of the AI advisor platform in a closed group. Users in the group will use the platform, report its drawbacks, and provide suggestions for improvement.
This will test your robo-advisor platform and help you gather feedback on your platform’s performance.
Step#7. Deployment
Once testing is done and your robo-advisor platform is bug-free, deploy it for the general public use. Don’t forget to market it through advertisements, search engine optimization, and other marketing strategies.
Step#8. Continuous Improvement and Maintenance
After deployment, keep a tight eye on the robo-advisor platform to monitor its performance. Also, you need to regularly update the platform to increase its performance, security, and user experience.
Moreover, you must refine artificial intelligence and machine learning models frequently with new data and user interaction to keep the platform relevant in the market for a long time.
So, this is how you can develop a custom robo-advisor platform tailored to your specific requirements. If you need assistance with building the platform, feel free to team Quytech and we will help you in developing your robo-advisor platform.
Robo-Advisor Platforms Development!
Technology Stack For Creating a Robust Robo-Advisor Platform
Here we have listed a technology stack that you can use for robo-advisor platform development.
| Component | Tech Stack | Description |
| Frontend | React, Angular, Vue.js | JavaScript frameworks for building user interfaces and ensuring a smooth user experience. |
| Backend | Django, Flask, Node.js | Frameworks for server-side development, handling business logic, and API endpoints. |
| Database | PostgreSQL, MySQL, MongoDB | Relational or NoSQL databases for storing user data, financial information, and transaction records. |
| Data Processing | Pandas, NumPy, Scikit-Learn | Python libraries for data manipulation, numerical computation, and machine learning algorithms. |
| AI/ML Models | TensorFlow, Keras, PyTorch | Libraries for developing and training machine learning and deep learning models. |
| APIs | REST, GraphQL | Protocols for enabling communication between the frontend, backend, and external data sources. |
| Data Integration | Financial Market APIs like Alpha Vantage, IEX Cloud | APIs for integrating real-time and historical financial market data. |
| Security | SSL/TLS, OAuth, JWT | Technologies for ensuring secure data transmission, authentication, and authorization. |
| Version Control | Git, GitHub, GitLab | Tools for source code management and collaboration among development teams. |
| Monitoring | Prometheus, Grafana, ELK Stack | Tools for monitoring application performance, logging, and analyzing metrics. |
So, this is the suggested technology stack for creating an AI-powered advisor platform. However, please note that it is only suggestions, you can use different tools and frameworks to create a platform tailored to your specific needs.
Top Features of a Robo-Advisor Platform
Now, let’s talk about the top features you must integrate into the robo-advisor platform.
- Easy Account Setup
This feature involves a streamlined process to create an account for a robo-advisor platform. Users need to provide basic information, such as name, age, financial goals, income range, and more, to create their accounts hassle-free.
- Automated Portfolio Management
Another top feature of the robo-advisory platform is automated portfolio management powered by artificial intelligence. It creates and manages a diversified portfolio aligning with the user’s capacity to tolerate risks, their financial goals, and time period.
- Risk Assessment and Profiling
Users need to answer some personal finance-related questions while using the robo-advisor platform. The information provided by users to used by AI algorithms to assess their risk capacity and based on it, it creates a personalized investment strategy.
- Diversification
There is a saying for investment that is “Never put all the eggs in one basket”. Based on this, the diversification feature of the robo-advisory platform invests in several asset classes that help minimize risk and yield better returns.
- Rebalancing
The rebalancing feature in an automated advisor platform adjusts the portfolio frequently to maintain the required asset allocation. This helps ensure the portfolio aligns with the client’s risk potential and financial objectives.
- Tax-Loss Harvesting
This feature allows users to perform tax-loss harvesting (a strategy to sell securities at a loss to lower taxes). Users can sell some securities at a loss and show that loss to save tax on other capital gains and income.
- Access to ETFs and Index Funds
Users can access various ETFs (Exchange-Traded Funds) and Index Funds to invest in passively managed funds to reduce investment risks.
- Goal Setting and Tracking
Users can set their financial goals, whether, short or long-term, using this feature in the robo-advisor platform. Moreover, they can also track the progress and how their investments are performing using the same feature.
- Customer Support
The “customer support” feature in an AI-powered advisor platform addresses client’s queries around the clock.
You can leverage generative AI like ChatGPT, to empower the customer support chatbot to understand clients’ questions and provide custom replies, enhancing their experience.
- Security Features
Last but not least on the list, robust security is crucial for protecting client’s personal and financial information from cyber threats and hacks.
Implementing high-end security features like biometric authentication, end-to-end encryption, Secure Socket Layer (SSL), fraud detection systems, and more, can safeguard user data and help you win their trust.
So, integrating these features in the robo-advisor platform can enhance your user’s investment and portfolio management experience.
Cost of Building a Custom AI-enabled Advisor Platform
The cost of developing a custom AI-enabled advisor platform depends on various factors contributing to its final development cost. These factors include:
- Type of platform
- Features and functionalities
- Tools and frameworks
- Use of emerging technologies like AI and Blockchain
- Size and location of the development team
- Any other custom requirements from the client, and more.
The cost of development can vary depending on these aforementioned factors. Hence, it is suggested to get in touch with our experts and share your requirements, and we will quote you the cost of building a robo-advisory platform.
Trends in Robo-Advisor Platform Development
Here are some futuristic trends you can follow to make your robo-advisory platform advanced and make it stand out from the competition.
- Sophisticated AI and Machine Learning Algorithms
The robo-advisor platform functions with the help of artificial intelligence and machine learning algorithms.
Investing in sophisticated algorithms not only enhances your platform’s accuracy but also empowers it to provide more personalized investment strategies, portfolio optimization, risk management, and predictive analytics.
- Improved User Experience (UX)
The UI/UX plays a crucial role in a platform’s success. Hence, you must invest in improving the UI of your robo-advisor platform to stand out from the competition in the market.
You can enhance UI and app experiences for better engagement and implement behavioral data to redesign the platform and its functionalities. To learn more about improving UI/UX, click here.
- Expanding to Alternative Investments
As of now, robo-advisor platforms are used in the fintech industry to provide automated financial consultations and portfolio management services to clients.
However, you can build AI-enabled advisor platforms that can be used for services related to alternative assets like real estate, private equity, and even blockchain-powered cryptocurrencies.
Conclusion
The robo-advisor platforms, powered by AI and machine learning algorithms, provide personalized financial consultations and manage portfolios of clients.
These platforms leverage historical and current financial data to analyze market trends, potential risks and gains, and interests. Based on these factors, they provide the best investment advice and manage portfolios.
You can follow this guide to create a robo-advisory platform tailored to your specific needs. We have covered every essential factor you need to know for developing your platform.
Moreover, if you need a professional team to build the platform, you can reach out to our experts, and we will build the robo-advisory platform for your business.
For more information, please visit our website: www.quytech.com
Frequently Asked Questions
The following are some frequently asked questions related to the robo-advisory platform development.
As the name suggests, it is a platform that provides financial advice and manages portfolios with minimal human interference.
Robo-advisory platforms are powered by AI and machine learning algorithms and use financial data to analyze and provide financial advice. The accuracy depends on the algorithms; the more sophisticated algorithms, the better the accuracy.
To build a custom advisory platform, you can either follow our guide, “Robo-Advisor Platform Development: A Comprehensive Guide”, or reach out to Quytech, and share your requirements.
The time to create a robo-advisory platform depends on the specific requirements, type of platform, development team, and other factors. However, it may take around 4 to 11 months, or more, to develop a robo-advisory platform.