Trade Order Management Software for Buy-Side

Investment IT consultants gather and document requirements for the new trade order management system. This assumes close collaboration with the investment firm’s stakeholders and OMS business users to ensure nothing important is overlooked. Based on the collected information, consultants compose a software requirements specification (SRS).

• The depth and completeness of initial discovery directly impact the accuracy of preliminary estimates and the predictability of the entire project. To ensure accurate estimation, consultants at ScienceSoft study the investment firm’s order management workflows (roles, target asset classes, data flows), functional requirements for the OMS (supported order types, must-have and nice-to-have automation features, analytics complexity, etc.), as well as non-functional needs (system performance, scalability, latency, security, integrations).

• By defining compliance requirements for the trade OMS at this early stage, you ensure compliant solution design from the outset. Our compliance consultants analyze and map both the relevant data protection standards (e.g., SEC’s Reg SCI, GLBA, GDPR, SOC 2) and operational regulations (SEC, FINRA, Dodd-Frank, etc.). They also scope the client’s internal compliance mandates, such as specific rules for order handling, instruction approval, and trade audit trails.

Core activities at this stage include designing the architecture of a trade order management system, selecting a tech stack, and designing role-specific UX and UI.

• Modular architectures (SOA, microservices) allow independent development and evolution of trade OMS components, which enables iterative software delivery, shortens time to launch, and contributes to the solution’s longevity. Moreover, modular options support logic reuse across system components, driving up OMS accuracy and reducing development efforts. At the same time, architects at ScienceSoft consider each solution’s functional specifics and performance needs when selecting the optimal architecture patterns. For example, if your OMS requires ordering for high-frequency trade execution, architects prioritize hybrid design, where speed-sensitive trade modules are built into a monolith architecture that offers the quickest data exchange, and the rest of the system is designed using modular patterns.
• By using ready-made logic building blocks, off-the-shelf UI components, pre-built third-party components (e.g., authentication, low-latency messaging, reporting), and reusable deployment scripts, you can reduce the share of costly custom coding and speed up development. Consider low-code platforms like Microsoft Power Apps for non-execution parts of the OMS — from our experience, this helps cut down coding costs for ancillary modules by up to 70%.

• Tailoring navigation, layouts, and data density for each ordering team role is a must for maximizing adoption, driving employee efficiency, and minimizing human error. For example, portfolio managers value comprehensive blotters with drill-down options, and compliance experts prefer minimalistic screens with clear alert displays. At ScienceSoft, we apply adaptable user journeys and customizable layouts to meet the distinct needs of various user segments without inflating UX/UI design efforts.

Project managers map the scope of project tasks, compose a work breakdown structure (WBS), define the resources needed to deliver trade order management software, and estimate project timelines and budget.

• A solid risk mitigation strategy will help you effectively address arising obstacles. PMs at ScienceSoft plan responses to both known and potential risks, including technical and integration challenges, resource constraints, and regulatory shifts that affect trade operations. Explore our deadline management and budget management practices to understand how proactive contingency planning helps us prevent delays and cost leakage in complex endeavors like trade OMS development.

• It’s easy for an OMS project to balloon in scope if every new idea is added without discipline. Our PMs define structured scope management and change control processes upfront so that any additional feature requests are evaluated for feasibility and impact and scheduled appropriately. Progress reporting is another aspect we plan before development to prevent misaligned stakeholder actions and creeping work scope.

During this stage, developers code the back end of the trade order management system (including specialized components like AI models for intelligent order handling), create user interfaces, and set up scalable data storage.

• Implementing DevOps (CI/CD, container orchestration, etc.) helps significantly speed up development, testing, integration, and deployment operations. It also eliminates manual errors and minimizes regression risks in production releases. Discover how ScienceSoft leverages DevOps to enable rapid, reliable trade order software delivery with deployment failure rates under 5%.
• Running testing in parallel with coding helps catch issues before production, when they are easier and cheaper to fix. Our QA engineers run multiple layers of testing, including functional testing, component integration testing, performance testing (load, stress, spike, endurance), usability testing, and security testing. Test automation is our primary approach for fast, high-coverage quality checks; however, we also utilize manual testing where automation is not feasible or when a more exploratory approach is needed (e.g., when evaluating code security and trade data handling accuracy).
• By setting up a dedicated test environment that mirrors the production setup (including connections to test market data and execution venue simulators), you can validate trade OMS behavior under realistic operational conditions. Check how we applied this practice in ScienceSoft’s early trade automation software project to confirm system readiness for live trade ordering on the NASDAQ and NYSE American exchanges.

At this stage, engineers integrate the new OMS with the necessary internal and third-party systems. If replacing or upgrading an existing ordering system, you may also need to migrate trade data (positions, reference data, open orders, etc.) to the new solution.

• Most brokers, custodians, and market data services offer ready-to-use APIs and protocols (e.g., FIX interfaces) so that you can integrate your OMS with their platforms quickly and in conformance with industry standards. Integrating with legacy in-house systems may require building custom adapters and connectors or implementing specialized middleware. In both scenarios, integration testing is key for confirming that systems synchronize smoothly and securely.

• When moving trade data from an old system to the new OMS, do it in controlled stages with small batches. This way, if any issues arise, you can quickly roll the batch back without affecting all the transferred data. Data engineers at ScienceSoft use automated migration scripts with testing checkpoints across data extraction and transfer stages. This prevents manual migration errors and helps validate the integrity and completeness of data during transition. Reconciling the data between the new OMS and the old system after the final cut-over helps confirm that there are no accuracy issues.

Development teams configure secure infrastructure for order management software, finalize the necessary testing activities, and deploy the solution to production.

• New regulatory rules for trading can come into effect during development. Running a compliance audit just before the go-live will let you double-check OMS compliance with the latest sectoral regulations.
• Given the sensitivity of trade data and the OMS, you need to ensure that the production environment is protected via enterprise-grade security mechanisms. ScienceSoft’s minimal tool stack includes firewalls, intrusion detection/prevention systems, and SIEM systems for continuous monitoring. We also apply the principles of least privilege for system accounts and encryption for data in transit and at rest. After-launch penetration testing and vulnerability assessment of the live environment is another best practice to make sure no security holes were introduced during deployment.

• Once the OMS is live, regular maintenance (applying patches, adding new features, tuning performance, etc.) is needed to keep the solution running smoothly. You also need to organize L1–L4 support to help users who encounter issues and quickly resolve technical problems. Check out ScienceSoft’s dedicated page for ways to set up efficient maintenance and support operations both for outsourced and in-house scenarios.