How to Build a Robo-Advisor Platform for Investment Firm

  • Fintech
Mar 22, 2023
How to Build a Robo-Advisor Platform for Investment Firm, image #3

Over $770 billion in assets were handled by robo-advisors in the US in 2020. Since 2017, this fintech market has grown significantly, doubling the assets’ value by 2021 to reach one trillion dollars.

What’s the reason for robo-advisors’ growing popularity? For instance, the efficiency they bring to banks, financial institutions, startups and insurance companies. They automate time-consuming tasks such as portfolio rebalancing, tax-loss harvesting, and reporting. In this case, machines are more cost-effective than traditional financial advisors, not to mention their scalability accommodating a growing client base. 

However, creating your own robo-advisor is a sophisticated task. Thus, it’s worth entrusting it to a skilled technical team.

Working in fintech for over 3 years while creating solutions for billion-dollar worth companies gave our team the expertise to share our knowledge with you. In this article, we will examine robo-advisors’ value and target audience in further detail, analyze their key features and architecture, and give valuable information about their development. Also, we’ll cover other vital aspects of how to build a robo-advisor business based on WeSoftYou’s years of expertise in financial technology

How does a robo-advisor work?

A robo-advisor is an automated investment platform that uses algorithms to manage investment portfolios. Mainly, it’s powered by artificial intelligence and machine learning. It is usually used for automated wealth management and serves as a viable solution for beginners or small investors.

It works in the following way:

  1. The investor provides necessary data (investment goals, the risks they are comfortable with, and other relevant information).
  2. The algorithm creates a personalized investment portfolio that’s designed to meet the investors’ specific needs based on the data they previously provided.
  3. Eventually, it keeps an eye on the investments and makes adjustments as necessary to maintain the desired level of risk and return.

Robo advisors’ complete automation allows investors not to think about investment decisions, streamlining the investment process. Since it’s online, the costs are much lower than what they would pay for a traditional financial advisor.

Who Should Use a Robo-Advisor?

Robo-advisors can be a good fit for various investors. However, their primary target audience tends to be people looking for a simple, low-cost way to invest their money. 

Here are a few types of people who may benefit from using such software:

New investors

Robo-advisors can be a good option for people new to investing and lacking experience or knowledge about the markets. The algorithms can take the guesswork out of investing and provide a more straightforward approach.

Passive investors

Robo-advisory software development is often designed for passive investors who want to invest their money in a diversified portfolio and hold it for the long term. If they are not interested in actively managing their investments, a robo-advisor can handle the ongoing management and rebalance for them.

Investors with smaller portfolios

Since investors with smaller portfolios have lower minimum account balances and lower fees than traditional financial advisors, it also makes them a proper target audience for robo-advisor development. This makes them accessible to people who may not have much money to invest.

Investors who value convenience

One more group of people who often benefit from robo-advisors are busy investors. Usually, they lack time or desire to manage their investments themselves. With robo-advisor development, they can set up their account online and have their portfolio managed automatically.

Robo-advisory software development explained in detail

Key Features of Robo-Advisor Platform

To develop a robo-advisor that will be comprehensive and usable, the developing team should introduce several must-have features.

Automated portfolio management

The robo-advisor algorithm creates and manages a customized investment portfolio for each investor based on their profile and preferences.


The portfolio is typically diversified across asset classes, such as stocks, bonds, and cash, to help manage risk.


The robo-advisor algorithm periodically rebalances the portfolio to maintain the desired asset allocation and risk profile.

Tax optimization

Offering tax-loss harvesting, which means selling losing investments in a portfolio to offset gains in other assets, is one more beneficial feature. This can help reduce an investor’s tax bill.

Low fees

Robo-advisors typically charge lower fees than traditional financial advisors since they are automated and require less human intervention.

Investor education

Many robo-advisors offer educational resources, such as articles and tutorials, to help investors learn about investing and financial planning.

Customer support

Most robo-advisors offer customer support via phone, email, or chat to answer questions or provide additional support as needed.

Launch a robo advisor with all the necessary features

Components of a Robo-Advisory Platform

While coding the software, robo-advisor developers will have to work with the following components:


Algorithms create and manage investment portfolios. The most common ones robo-advisors use include:

  • Modern Portfolio Theory (MPT) – aims to maximize portfolio returns while minimizing risk;
  • Mean-variance optimization – similar to MPT but uses statistical models to estimate the expected return and volatility of different asset classes;
  • Risk parity – aims to create a portfolio with equal risk exposure across different asset classes;
  • Black-Litterman – combines MPT with investor views on market conditions, allowing investors to incorporate their view to portfolio allocation;
  • Momentum investing – identifies and invests in assets that have shown positive price momentum in the recent past;
  • Value investing – identifies and invests in undervalued assets relative to their intrinsic value.

Robo advisor is a fintech product that helps automate processes

Back-end development

Common back-end technologies used in robo-advisor development include Python and its Django framework for offering a wide range of built-in features, such as authentication, security, and database integration. 

The next good choice is the Ruby language and its framework Ruby on Rails: thanks to its simple and intuitive syntax, it’s easy to operate, which comes in handy when precise software like robo-advisor is in question.

Front-end development

Robo-advisor’s front-end has to be understandable and responsive. This is why the good options for such a task would be 

  • React and Angular for their component-based approach, 
  • Vue.js for simple syntax and a range of built-in features, 
  • Bootstrap or Materialize for providing a range of pre-built UI components; in case of Materialize, they are based on Google’s Material Design principles.

Application programming interfaces

APIs are used to integrate the robo-advisor platform with external data sources, such as market data feeds and financial news sources. Popular APIs include Alpha Vantage, Yahoo Finance, and Bloomberg.

Technologies Required for Building a Robo-Advisor

How to create a robo-advisor that is reliable and functioning? You’ll have to pick the proper tech stack. Let’s see what the future developers will have to operate with.

Programming languages

Java, Python, and Ruby are popular choices for building robo-advisors. These languages offer robust frameworks and libraries for data analysis, machine learning, and automation.

Data storage and management

Robo-advisors require reliable and scalable data storage and management solutions. Popular choices include SQL and NoSQL databases, such as MySQL, PostgreSQL, and MongoDB.

Machine learning and data analysis

Machine learning algorithms analyze data and generate investment recommendations. Tools and frameworks for machine learning include TensorFlow, Scikit-Learn, and PyTorch.

Cloud infrastructure

Cloud computing platforms, such as Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform, provide a scalable and secure infrastructure for robo-advisor development.


Robo-advisors handle sensitive financial information, so security is a critical consideration. Security technologies should include encryption, firewalls, and intrusion detection and prevention systems.

Robo-advisory software development requires a broad tech stack

How to Create a Robo-Advisor Platform Step-by-Step

How to build a robo-advisor platform? The following are the fundamental steps to making one.


In robo-advisory software development, the premiere stage of discovery demands conducting a lot of research work, including defining the target market (the clients and their investment goals) and determining your type of product, namely its investment philosophy and strategy. This should include selecting the asset classes, investment style, and risk management methods that will be used.

Select the technology stack that you will use to build your platform. This will include selecting a programming language, framework, database, cloud infrastructure, APIs, and algorithms.

After the vision and target audience have been formed, it is time to determine the program’s functional and non-functional requirements and discuss MVP with your technical contractor.


At this stage, a team of UI/UX designers works on your robo-advisors’ outlook. Now, the team of devs and designers work together to conduct UX research, define user paths and user stories, and make mockups.

Development and testing

The platform in question is being built: this is when developers write the code and put it together with a UI/UX design. After the development scope of work has been done, the software is being tested to ensure that it works as expected and that it is secure.

Deployment, support and maintenance

Once all the technical work is done, it comes time to launch the product. Afterwards, make sure to provide ongoing support and maintenance for the software to ensure it continues functioning effectively. Make updates and improvements as necessary to enhance the user experience and optimize performance.

To launch a robo advisor, you have to follow sdlc pattern

Challenges of Building a Robo-Advisor

Building a robo-advisor is a responsible task with numerous hurdles to overcome, demanding a precise and expert approach. Let’s take a closer look at the potential roadblocks.

Data Management

Robo-advisors need to process and analyze large amounts of data quickly and accurately, which can be challenging. This includes data on financial markets, investment trends, and individual client profiles.


There are strict regulatory requirements that must be met by robo-advisors to ensure compliance with financial regulations, such as KYC and AML regulations. These regulations may vary by jurisdiction and can be complex to navigate.


Robo-advisors must ensure the security of their platforms to protect user data and prevent cyber-attacks. This includes implementing strong encryption methods, secure data storage, and two-factor authentication.


Robo-advisors need to handle large volumes of users and data as they grow. This requires a scalable infrastructure that can adapt to changing needs and demands.

Creating a robo advisor necessitates security, compliance and data management

WeSoftYou Is Ready to Become Your Reliable Partner

Starting a robo-advisor business, it’s critical to have a reliable technical team on your side. Let WeSoftYou take this place: see what fintech products our team has worked with earlier.

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Entrust your next robo-advisor development to WeSoftYou

Developing a custom robo-advisor will positively influence the banks’, startups’, or financial institutions’ budget, accelerate returns, and generally help make data analysis and clients’ investment management more streamlined in automating routine operations.

If you’re wondering how to build a robo-advisor application to reap its full benefits, trust the knowledgeable staff at WeSoftYou with the construction of this solution. 

Let’s talk about your next idea: we will help you calculate the estimations and assist in requirements generating to draft a custom product that will bring better customer experience, scalability, and revenue increase to your business.

Introducing visionOS Development Services by WeSoftYou


What Algorithms Do Robo-Advisors Use?

Creating your own robo-advisor suggests working with a variety of algorithms that manage and create investment portfolios. Modern Portfolio Theory (MPT), Mean-variance optimization, Risk parity, Black-Litterman, Momentum investing, Value investing, and AI are the most common.

Do Robo-Advisors Make Money?

Yes, robo-advisors make money by charging fees to their clients. The fees vary depending on the robo-advisor and the services provided, but they typically range from 0.25% to 0.75% of the assets under management (AUM) annually.
Robo-advisors may also generate revenue through other sources, such as interest on cash balances held in client accounts, securities lending, and referral fees for directing clients to other financial products and services.

How Long Does It Take To Start A Robo-Advisor?

Ultimately, depending on the unique objectives and conditions of the project, it may take several months to more than a year to launch a robo-advisor. To guarantee a successful launch, it is critical to thoroughly plan and manage each step of the process, as well as entrust robo-advisory software development to a qualifier team of engineers like WeSoftYou.

What’s The Ideal Tech Stack For Developing A Robo-Advisor?

Most frequently, robo-advisor software developers use Java, Python and Ruby programming languages to code this solution. The best choice for data storage and management software would be SQL and NoSQL databases, such as MySQL, PostgreSQL, and MongoDB. Popular APIs include Alpha Vantage, Yahoo Finance, and Bloomberg.

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