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Robotic Process Automation (RPA) in Investments
Architecture, Costs, Success Stories
ScienceSoft relies on 19 years of experience in engineering investment automation software and 8 years in RPA implementation to deliver robust RPA solutions for the investment industry.
Robotic Process Automation for Investments: Key Aspects
Robotic process automation (RPA) in investments is used to minimize manual workflows across the investment management cycle. RPA solutions offer an intuitive low- or no-code toolkit, which allows investment and IT teams to quickly design and configure task automation rules.
RPA lets investment companies establish 10–2,000x quicker service and business processes, reduce low-value employee efforts by more than 45%, and cut operational costs by up to 75%. The technology drives a 70–90% improvement in workflow accuracy, streamlines integrations between modern and legacy investment systems, and simplifies compliance with sectoral regulations (SEC, FINRA, GLBA, etc.).
Investment firms implementing RPA can expect an ROI of 240%+ over three years. RPA solutions typically pay off within 6 months after launch.
RPA in the Investment Industry: Market Info
The global market of robotic process automation in financial services was valued at $3.51 billion in 2023 and is projected to reach $12.5 billion by 2032, growing at a CAGR of 13.54%.
RPA-supported investment, representing one of the major market segments, is anticipated to show a corresponding increase. The main driver for the popularity of investment RPA solutions is their ability to enhance investment service efficiency, cut operational expenses, support continuous workflow improvements, and simplify adherence to corporate and regulatory rules.
According to Deloitte, 85%+ of companies who implemented RPA indicate that the technology met or exceeded their expectations for improved productivity, capacity, accuracy, and compliance.
Investment Operations to Automate With RPA
Investor relationship management
- Investment product catalog population.
- Lead processing.
- Account opening.
- AML/OFAC screening.
- Investor notifications.
- Investor reporting.
- Investor self-service operations.
Investment data and document processing
- Data scraping from integrated systems.
- Data capture from investment documents.
- Data entry into corporate systems.
- Data sorting.
- Investment document generation.
- Basic analytics (calculation of historical metrics).
Investment operations management
- Investment order creation.
- Asset and portfolio valuation.
- Fundamental metric calculation.
- Stress testing.
- Portfolio KPI tracking.
- Limit compliance tracking.
- Task assignment to investment specialists.
Trading
- Technical metric calculation and monitoring.
- Notifications on capital market events.
- Trade execution.
- Fund transfer processing.
- Clearing and settlement.
- Algorithmic trading.
Financial control
- Investment transaction bookkeeping.
- Service fee calculation and invoicing.
- Tax calculation and filing.
- Cost allocation.
- Revenue recognition.
- Reconciliation.
- Financial reporting.
Security and compliance
- Audit logging.
- Compliance monitoring.
- Permission-based access control.
- Employee fraud detection.
- Security threat detection.
- Risk alerts.
- Regulatory reporting.
Maximizing automation in investments
RPA is perfect for straightforward, rule-based routines, but it struggles with more complex operations that require processing unstructured data, understanding context, or making independent decisions. To overcome these constraints, consider reinforcing RPA with artificial intelligence (AI). By enabling image analysis, natural language processing, and predictive analytics with AI, you can automate up to 98% of workflows across multi-format document processing, investor communication, and complex portfolio optimization tasks.
Key Features of Investment RPA Solutions
RPA building
Visual modeling of digital processes
Drag-and-drop modeling interfaces let investment professionals and IT specialists design and visualize digital processes: KYC verification, asset valuation, portfolio rebalancing, report filing, and more. The teams can collaborate on process visualization and use built-in testing tools to validate RPA logic before deployment.
Prebuilt RPA components
A library of reusable components (process diagrams, rules, forms, decision trees, etc.) and templates for digital investment processes (e.g., data entry, investor due diligence, order submission, insider threat reporting) streamlines RPA design for standard investment tasks.
Custom automation rule design
Users can build custom logic components, compliance rules, actions, and decision points to automate unique investment scenarios, such as portfolio risk scoring based on the investment firm’s proprietary formulas or trade transaction segmenting based on non-standard criteria.
Digital process sequence configuration
Investment automation processes can be configured to run in parallel or according to user-defined workflow sequences. Users can also set and adjust sequencing properties of selected process elements, such as investment transaction approval hierarchies and investment order processing queues.
Investment data flow mapping
Users can interlink data sources, processes, and intended results and configure automation flows for utilizing various types of investment data. For example, they can list reliable platforms for stock data capture, specify investor document pieces relevant to OFAC screening, or map P&L report fields to auto-populate with portfolio data.
Access management
RPA solution admins can configure user roles (e.g., investor relationship specialists, trade specialists, accountants) and assign role-specific access rights. Permission-based access controls ensure that only authorized users can modify RPA rules and access sensitive data, enhancing operational security and compliance.
RPA execution
Investment automation enforcement
RPA software instantly captures predefined event triggers and enforces the assigned investment automation rules. Automation can be triggered by investment professionals (e.g., for ad hoc investor report generation) or run autonomously in the background (e.g., for scheduled report creation and submission to investors).
Digital process control
Users can monitor the real-time status of automated investment processes via interactive dashboards. The RPA solution immediately notifies responsible parties about automation failures and process rerouting to contingency scenarios. Built-in analytics provide insights into the areas of poor and superior RPA performance.
Integration management
Prebuilt APIs and connectors let IT specialists quickly integrate an investment RPA solution with back-office systems and external platforms. RPA’s screen scraping and data extraction capabilities can be combined with optical character recognition (OCR) to pull data from legacy investment tools that lack modern integration interfaces.
Orchestration of digital processes
Standalone digital investment operations can be orchestrated to enable end-to-end automation of complex tasks like investment portfolio planning or algorithmic trade execution. Users can also map exception-handling flows for non-standard operational scenarios like temporary trade halting during high market volatility.
AI-supported features
Intelligent process design and optimization
Smart copilots can suggest the optimal RPA patterns for investment operations, assist business and IT users in process modeling and rule construction, and recommend ways to resolve automation issues — all in a real-time, human-like conversation. AI copilots can also autonomously run digital investment workflow optimization.
Designing and enforcing intelligent automation
Advanced RPA solutions enable dynamic rule mapping for AI-supported investment automation. In this scenario, tailored machine learning (ML) models are integrated directly into RPA workflows for analytics and decision-making. RPA components automate model output validation, real-time workflow path adjustment, and process compliance checks.
Sample Architecture of an RPA Solution for Investment
While we can build RPA software on any platform of the client’s choice or develop a custom solution from scratch, I usually recommend Microsoft Power Automate, especially if the business is already using the Microsoft ecosystem. Power Automate has a robust engineering toolkit, built-in smart copilots, and native integration with Power BI and AI Builder services, which drastically speeds up RPA design and launch. From my experience, rolling out RPA on Power Automate can be 70% cheaper than custom RPA development and 30–50% cheaper than RPA implementation on other platforms.
Below, ScienceSoft’s consultants share a sample architecture of a Power-Automate-based investment RPA system and describe its key components.
The business users involved in RPA rule design and supervision interact with the solution via customizable user interfaces built on the Microsoft Power Automate platform. The intelligent assistant, Microsoft Copilot, guides the users in creating, optimizing, and extending process automation.
After being mapped, the logic components are routed to the RPA app data storage and management service, Microsoft Dataverse, for storing and tracing.
The RPA back-end engine triggers automation upon the predefined events, for example:
- An investment professional clicks the ‘Submit order’ button in the portfolio management system. The RPA engine checks the system’s database, sees the update, and routes the order to the relevant third-party platform (investment, trading, etc.).
- CRM receives a new investor reporting schedule. The RPA engine captures the update in the CRM database, enforces report generation, and submits the ready report to the investor via the agreed interaction channels (portal, mail, messaging).
- New investor-related data emerges in the company’s data storage or connected data sources (capital market data platforms, AML/OFAC databases, etc.). The RPA engine spots the new data and communicates it to the investment analytics system.
To enable intelligent automation (e.g., for investment document analysis), the RPA solution requires a connection to AI services like Microsoft AI Builder. In this scenario, the RPA back-end engine can query the AI component to process complex operations like document data extraction, fraud detection, or content summarizing.
How Investment Companies Benefit from RPA
RPA clears BNY Mellon’s trades in 1⁄4 second
BNY Mellon, a US financial services giant with nearly $50 trillion in assets under management, implemented an RPA solution by Blue Prism to automate trade order entry, fund transfer, clearing, and settlement. The solution helps BNY Mellon enter trade orders 66% quicker and reconcile trade with 100% accuracy in a quarter of a second instead of 5–10 minutes. The bank estimates that its funds transfer RPA bots alone are saving it around $300,000 annually.
Credigy grows at a CAGR of 15%+ with RPA
Credigy, a B2B specialty finance company owned by the National Bank of Canada, relied on the IBM Robotic Process Automation platform to build its RPA solution for investment document processing. RPA bots process 100% of loan-related documents for Credigy’s portfolio purchases, removing repetitive employee tasks and accelerating the company’s decisions on portfolio deals. RPA launch enabled Credigy to steadily grow its business at a CAGR of 15%+.
Tech Stack for Developing Investment RPA Software
What Drives the ROI for RPA in Investments
Employee education on RPA usage
Investment teams may lack knowledge about RPA, which results in apprehension and slow RPA adoption. Some employees might resist RPA, perceiving it as a threat to their job security. Dedicated training programs will help investment professionals understand RPA’s supportive role and master the new solution quicker. Also, consider launching AI copilots with the RPA platform to streamline employee training on software use.
Adherence to the latest regulations
The static RPA rules can be designed to mirror any necessary investment regulations, but they cannot auto-adapt to regulatory changes. Missing legal shifts may lead to inadvertent compliance breaches. Integrating RPA software with compliance monitoring tools will let you quickly spot potential gaps and update automation rules as soon as possible. Platforms like Power Automate offer prebuilt process flows for compliance cross-checks.
Scalability for fluctuating operational loads
Your investment RPA solution must perform stably under spike loads, e.g., during end-of-day trade settlements or end-of-period investor reporting. Consider implementing your RPA solution in the cloud and applying automated scaling of computing resources depending on the load. Autoscaling helps ensure investment operation continuity and significantly reduces cloud costs during lower-demand periods.
Costs of Implementing RPA for Investments
From ScienceSoft’s experience, developing an RPA solution for investments may cost from $15,000 to $250,000+, depending on the number and complexity of processes to automate, the scope of integrations, and security and compliance requirements.
Here are our ballpark estimates for investment RPA solutions built on Microsoft Power Automate:
$15,000–$90,000
An RPA solution for automating a specific investment task (e.g., transaction recordkeeping, trade order entry, investor report generation).
Operational costs: $15 per user/month for Power Automate platform usage.
$150,000–$250,000+
A comprehensive solution combining RPA and AI to automate complex end-to-end operations like investor KYC and portfolio auto-rebalancing.
Operational costs: $15 per user/month for Power Automate platform usage; (optionally) $500/month for AI capacity add-on.
Bring RPA to Investment Management With ScienceSoft
In investment IT since 2005 and in Microsoft Power Automate services since the technology’s inception in 2016, ScienceSoft offers full-cycle consulting and engineering services to help investment companies implement reliable RPA.
RPA for investments: consulting
With your specific requirements in mind, we design the features, architecture, tech stack, and role-specific interfaces for your investment RPA solution. You also get a detailed plan for its smooth implementation.
RPA for investments: implementation
We develop your investment RPA solution on the chosen platform, integrate it with the required systems, and perform rigorous testing. You get a robust solution quickly and at the optimal cost.
What makes ScienceSoft different
We achieve project success no matter what
ScienceSoft does not pass mere project administration off as project management, which, unfortunately, often happens on the market. We practice real project management, achieving project success for our clients no matter what.