In this post, we are starting a new series of articles called “WealthTech Cookbook” in which we intend to discuss all the main components of wealth management software platforms, including digital and robo-advisors. We’ll analyze functionality, architecture patterns, and examples of implementation for each component. The entire WealthTech Cookbook will be based on the knowledge base gained in our Competency Center. Our expertise encompasses all financial and investment aspects, which allows us to supplement theoretical knowledge with practical examples. Another significant source of knowledge for our knowledge base is our experts, who are executives of leading WealthTech companies and have shared their experience with us, including their successful solutions and failed attempts.
Here’s an overview of the components that we will discuss.
Portfolio Construction & Management
As a rule, the first steps for a new platform user include completing a questionnaire and choosing a portfolio.
The questionnaire is one of the most important features that differentiates between robo-advisors. In it, users define their sociodemographic indicators, risk tolerance, goals, and time horizons. Schwab and E-Trade are examples of companies that offer comprehensive questionnaires.
Charles Schwab offers an Intelligent Portfolios platform that allows investors to build, monitor, and rebalance their portfolios:
Some platforms also enable users to indicate their investment preferences. Hedgeable, for instance, enables clients to choose socially responsible companies for investing.
When creating a portfolio for a user based on the information received, platforms typically use one of the following strategies:
- The platform creates the best portfolio based on the user’s answers, such that once the questionnaire has been completed the user has no control over the portfolio. Adjustments are possible, but only by the advisor.
- The platform offers the user a number of portfolios to choose from.
- The platform recommends particular allocations and gives the user complete control over the asset allocation.
We will discuss questionnaires, portfolio management strategies, and related issues, such as how these aspects can be technologically implemented, and the possible difficulties and downsides therein.
Risk Profiling
Once the questionnaire has been answered, the user’s risk profile is created. This has a significant impact on asset allocation and enables the mitigation of potential risks and treats. Risk-tolerance questionnaires help identify the level of risk that is acceptable to the user. Questionnaires differ across companies, but they usually identify a time horizon, the user’s willingness to tolerate possible risks, and their experience of risky investments.
Based on the user’s responses, risk-scoring algorithms indicate the risk level and behavioral investment category that is appropriate for that specific investor. This is then used for asset allocation recommendations and portfolio-management strategies.
Riskalyze provides technology for quantifying the risk-tolerance of investors and portfolio risk:
B2B WealthTech platforms may provide an option for financial advisors to create specific questionnaires and algorithms for scoring results.
We will discuss questionnaire building, risk scoring, and how behavioral investment patterns may influence recommended portfolio allocation.
Rebalancing Software
Rebalancing is the process of buying and selling assets in a portfolio to realign it with the originally chosen weightings of asset allocation. Rebalancing is important to maintain a portfolio appropriate to the investor’s risk profile.
Depending on the account type and the services offered, rebalancing may be conducted automatically by the platform, or manually by a human advisor or by the investor.
Morningstar offers a TRX (Total Rebalance Expert) service for outside account management:
When talking about algorithms for automating the process, we will discuss rebalancing options and examples of implementation, which basic features are required for rebalancing tools, and how the standard functionality can be expanded.
Portfolio Analytics & Optimization
Portfolio analytics tools allow the platform or financial advisors to measure performance, risk, and other characteristics of the current portfolio allocation, and evaluate the expected rate of return when choosing various assets for the portfolio.
Portfolio optimization tools may implement a number of techniques depending on the goal of the optimization. For example, to find a portfolio allocation that adjusts risk and maintains an efficient frontier, mean variance optimization is used. To minimize the expected tail loss, the conditional value-at-risk optimization strategy is used. There are also techniques to optimize the Sortino ratio, Omega ratio, and other portfolio metrics.
Personal Capital provides tools for portfolio analysis whereby investors can compare their current portfolio allocation to an ideal target allocation:
We will discuss available models, the pros and cons of each, the inputs they require, and their suitability for different situations.
Goal-based Financial Planning
Goal-based financial planning provides investors with better clarity regarding their finances, and gives them confidence in making investment decisions and control over their financial lives. Goal-based planning may focus on short, intermediate, or long-term financial needs.
Within goal-based planning, the investor’s specific goals are divided into groups and a specific investment strategy is then built for each group. The performance of the portfolio is measured against each goal, and the main risk is the failure to reach a particular goal.
PlanPlus provides software for financial and investment planning:
In discussing goal-based planning tools, we will look at the most-demanded features, and identify what inputs may be needed and how detailed the results can be.
Customer Relationship Management for Financial Advisors
Today, as the number of investors rises, customer relationship management (CRM) tools become crucial for financial advisors. They offer a broad range of instruments for communicating with clients, managing their portfolios, monitoring performance, and reacting to changes in clients’ circumstances or the market situation.
CRM tools can empower financial advisors to scale their business and make their communication with clients more frequent and personal. CRM tools may comprise desktop, web, and mobile versions, and may include the following core features:
- Tracking clients’ data (e.g., financial information, files, phone calls, emails, etc.)
- Filtering clients according to various parameters (e.g., previous contact date, service or AUM level, custom tags, etc.)
- Reporting, creation of report templates and customized reports, and sharing of reports with clients.
- Planning events and sharing them with coworkers and clients.
Wealthbox offers a web-and-mobile CRM application for financial advisors with a focus on simplicity and usability:
We will discuss the structure of the components, the required integrations, and the basic and unique features offered by the most popular CRM solutions.
Custodian & Brokerage API Integrations
Integrations with third-party systems, such as market-data vendors, custodians, and broker systems, are very important for wealth management platforms. Today, financial information exchange (FIX) APIs enable all sides, including custodians, financial advisors, investors, and brokers, to provide connections, exchange information, and improve performance.
Interactive Brokers offer API and FIX CTCI solutions that allow financial companies to receive market data and develop their own applications for trading securities:
We will discuss the benefits and limitations of working with REST and FIX APIs, and the principles of interacting and integrating with various services using APIs.
Artificial Intelligence for Asset Management
Artificial intelligence (AI) is becoming common in many areas of asset management. It helps investors create a diversified portfolio, rebalance it, improve performance, and mitigate risks. AI includes the following processes: data aggregation and processing, and data use for predictive market modelling.
Hedgeable has created the AI Lab in which it researches and develops AI FinTech products:
We will discuss and analyze successful cases of AI use in wealth management software.
Mobile Apps
Most WealthTech companies provide mobile apps to attract investors, particularly tech-savvy millennials. The functionality of mobile apps may vary significantly. Some apps give users access to their accounts that is limited to checking the balance, portfolio allocation, and investment returns, while others provide investment recommendations and allow users to add and change goals, manage their asset allocation, and trade securities.
Robinhood has developed an application for trading US securities via mobile devices:
We will discuss whether mobile apps should have the same functionality as the web platforms, or can provide only basic features. We will also analyze the related technical issues and the most popular tools.
System Security
Security is incredibly important for the entire financial services industry, and WealthTech is no exception. Wealth management software must comply with bank-level security regulations to ensure all data is secure. When talking about security, it is not just technical issues that matter but the human factor as well—that is, software-development teams and processes. We will discuss how to create a secure development environment and deliver security features to robo-advisors.
System Services
Wealth management software is not limited to the components described above, and a number of services are essential for robo-advisors, including:
- Scheduling—the development and execution of planned, asynchronous tasks that trigger business logic in the backend.
- Configuration—providing changes according to an advisor’s philosophy or regulatory norms.
- Internationalization—mechanisms for selecting the language to be used or tailoring output to match local conventions.
These and other services will be covered in the final section of our WealthTech Cookbook.
Conclusion
To build successful wealth and asset management software, knowledge has to extend beyond what to build. Understanding financial processes and the growing needs of investors and advisors is crucial, while knowledge of best practices and examples of successful and failed experiences significantly increase the likelihood that the resulting software will be effective.
