Azure-Based Investment Management Software for a Full-Service Family Office

About Our Client

The Client is a UAE-based family office providing full-cycle investment management services for ultra-high-net-worth families across the Gulf Cooperation Council (GCC).

Spreadsheets Were No Longer Viable for Complex Investment Management Tasks

Back in the day, when our Client focused on a limited range of investment options, Microsoft Excel’s functionality was sufficient to plan investments and monitor their performance. As the Client’s service scope, custodian base, and investment volume scaled, conventional spreadsheets became no longer viable for managing the growing number of complex multi-asset portfolios. Namely, it was difficult for the Client’s investment management teams to navigate large volumes of multi-format transactional data and visualize investment performance insights in Microsoft Excel. Another pain point was Excel’s limited integration capabilities. For our Client, it meant inefficient consolidation and reconciliation of siloed data and prolonged investment management workflows.

The Client decided to develop a custom investment management solution that would automate the company’s investment planning, valuation, and control activities. The company wanted the solution to be accessible to both employees and investors. This would streamline collaborative portfolio planning, let investors monitor portfolio KPIs in real time, and minimize reporting routines for the Client’s wealth managers. In the future, the Client also planned to distribute its investment management software as a commercial SaaS.

The Client lacked in-house software engineering skills, so it decided to fully outsource the initiative to a professional development firm. The company sought a technology partner with solid investment IT consulting competencies and experience in engineering custom investment software. With a sizable track record in investment IT, ScienceSoft matched both criteria and was chosen to carry out the project end-to-end.

Project Planning and Technical Design for Custom Investment Management Software

Investment system conceptualization

ScienceSoft’s investment IT consultant conducted several interview sessions with the Client’s stakeholders and subject matter experts (wealth managers, investment analysts, accountants) to elicit requirements for investment management software. She helped the company clarify its vision for the software, suggested non-apparent features that would enhance software value, and converted the gathered requirements into a detailed functional specification.

Given the Client’s plan to offer its investment management solution as a SaaS product, our consultant also researched the market and target audience expectations. She defined trending features for the software, shaped its competitive advantage and unique selling proposition, and suggested scenarios for smooth market entry.

ScienceSoft’s UX/UI designer joined the project at the early conceptualization stages. He created dedicated UX wireframes for various roles (family office specialists, investors, admins), prioritizing straightforward user journeys to minimize cognitive strain on the solution users.

Investment solution technical design

Next, ScienceSoft’s solution architect studied the functional specification and designed the optimal architecture and tech stack for the software. Our architect suggested applying a modular monolith architecture. Such an approach would streamline development and maintenance while still allowing for easy independent scaling and evolution of solution modules and ensuring flexibility to add new SaaS features in the future. Hosting investment software on the Azure Container Apps’ serverless platform would let the Client quickly deploy and scale the solution without the need to manage the underlying infrastructure.

The Client wanted its investment management software to automatically capture the data necessary for portfolio planning and control. ScienceSoft’s architect designed secure integrations with custodian banks and the FactSet capital market data platform to enable no-touch end-of-day aggregation of external data feeds. He suggested using test containers for investment software integration testing. This would allow engineers to safely run tests against the same database engine as used in Azure environments, minimizing risks of unforeseen integration issues.

For data analytics, ScienceSoft’s architect suggested using Azure Database for PostgreSQL. Its automated backup, elastic scaling, and patching capabilities would make it easier to build and maintain portfolio analytics pipelines. Using TimescaleDB for investment time-series analytics would ensure the smooth processing of large portfolio data sets and accelerate analytical workflows.

The Client’s investment management software required specialized visualization components to represent asset price movements and portfolio performance dynamics. ScienceSoft’s architect proposed using investment-specific UI component libraries by SyncFusion. SyncFusion’s capital market charting library offers 50+ pre-built charts for securities, derivatives, fiat and cryptocurrencies, and its dashboard library provides interactive drill-down and drill-up dashboards for KPI tracking. Employing ready-made packages of UI components would minimize the need for costly custom UI engineering while ensuring rich investment data visualization features.

Development project planning

After the Client approved the suggested technical design for its investment management system, ScienceSoft’s team proceeded to plan the development project. Our consultant triaged the software features for implementation and defined the functional scope for an MVP that would match both the Client’s business requirements and the SaaS market entry strategy.

ScienceSoft’s project manager studied the feature scope and suggested breaking down the development flow into four major stages:

• Developing functionality for automated entry and recordkeeping of investment data (investment options, asset price data, investment transactions, and more). This stage covers building integration APIs, functionality for automated investment data intake, and transaction auto-reconciliation features (e.g., cross-referencing data from the Client’s ledger with investors’ bank statements).
• Developing financial calculation and modeling features: automated investment valuation based on market price data, NPV and IRR calculation, portfolio structure modeling, etc.
• Implementing data visualization components: asset price charts, portfolio performance dashboards, and more.
• Developing admin features for setting up and configuring new asset classes, profitability formulas, and portfolio and business KPIs.

ScienceSoft’s project manager scoped the software development tasks for each stage, composed a time-framed work breakdown structure, and determined the resources needed to complete the project. In collaboration with ScienceSoft’s consultant and tech lead, he estimated project cost and time and designed a pragmatic strategy to mitigate risks.

The Client had a tight project budget and planned to attract external funding to evolve its investment management solution, so it was critical to obtain an MVP as quickly as possible. ScienceSoft’s project manager suggested applying iterative Agile methodology to speed up releases and optimize project expenses.

Once the project plan was finalized, ScienceSoft provided the Client with a team of a project manager, a business analyst (for Agile scoping), a UX/UI designer, a solution architect, a .NET developer, an Angular developer, a full-stack developer, and a QA engineer experienced in creating custom investment software. Based on ScienceSoft’s estimates, the Client could expect to get the ready-to-use lean software version within 8 months, which aligned with the Client’s MVP launch objectives.

Custom Investment Management Software Planned in 4 Weeks

In just 4 weeks, the Client received a clear functional concept, a technical design, and a detailed implementation plan for its custom investment management solution. With ScienceSoft’s advice on cost-effective software tech stack and development approach, the Client was able to confidently launch software project despite the limited budget. Thanks to the focus on SaaS-friendly software design and feature prioritization for the MVP, the company got the opportunity to speed up the solution launch and ensure its high value for current users and future SaaS customers.

As of November 2024, ScienceSoft is working on the development of investment data aggregation features. So far, the team managed to deliver the planned functionality strictly on the agreed schedule and budget.

Technologies and Tools

.NET, Angular, Microsoft Azure, PostgreSQL, TimescaleDB, SyncFusion.