Our client is one of the world’s top buy-side institutions, managing multi-asset portfolios across geographies and operating under strict regulatory oversight. With trillions of dollars in daily transaction value flowing through their systems, they needed a technology partner to modernize their decision-making infrastructure, improve operational efficiency, and strengthen compliance, without disrupting their trading rhythm.

The firm faced challenges that many asset managers today will recognize:

• • Siloed, Slow Data: Market, research, and reference data were fragmented across systems, making it difficult for portfolio managers to get a unified view of risk and performance.
• • Manual Bottlenecks: Reconciliation, reporting, and compliance checks relied heavily on manual workflows, consuming hours of analysts’ time each week.
• • Execution Pressure: In a world where milliseconds count, trade order routing and risk checks were not optimized for ultra-low latency.
• • Rising Compliance Burden: Regulatory regimes required auditable processes, explainable models, and transparent reporting, with penalties for non-compliance.

NuWare partnered with the client to design and implement a data-first, AI-enabled modernization strategy. Our approach was phased, ensuring stability while delivering quick wins.

Discovery & Planning
We began with a fit-gap analysis and ROI assessment across portfolio management, trade execution, and fund administration. This helped the client prioritize use cases that would deliver the highest impact, such as real-time data unification and predictive risk modeling.

Data & Cloud Enablement
We built a cloud-enabled data hub that unified market, reference, and historical trading data into a single source of truth. Using hybrid-cloud architecture and database platforms like Oracle and PostgreSQL, we ensured 24×7 availability and compliance with data residency requirements.

AI-Driven Insights
NuWare’s data science team developed time-series forecasting models (LSTMs and transformers) to anticipate market volatility, regime shifts, and liquidity needs. We also implemented NLP pipelines that parsed earnings calls, filings, and news to generate actionable sentiment scores for portfolio managers.

Workflow Modernization
Through RPA and intelligent workflow automation, we reduced manual reconciliation cycles, integrated compliance checks into trade order workflows, and automated reporting for regulators. Trade order management systems were tuned for ultra-low latency, with built-in pre-trade risk checks and automated routing logic.

Governance & Explainability
Given the client’s regulatory environment, every model and workflow included explainability features: SHAP-based interpretability for AI models, audit trails for trade execution, and full documentation for internal and external audits.

The transformation delivered measurable improvements across the business:

• • Decision Speed: Portfolio managers gained access to a unified data view and AI-powered forecasts, enabling faster and more confident allocation decisions.
• • Operational Efficiency: Automated reconciliation reduced processing time from days to hours, freeing analysts to focus on alpha generation.
• • Execution Performance: Trade routing latency dropped significantly, improving execution quality and saving basis points across large trades.
• • Compliance Confidence: With automated reporting and explainable models, the client passed regulatory audits with zero findings and reduced compliance costs.
• • Scalability: The cloud-based architecture now supports rapid onboarding of new asset classes and geographies without disruption.

For the client, the transformation was about more than technology, it was about reclaiming time and confidence. Their teams now spend less time gathering data and more time making high-value investment decisions, knowing that every action is backed by auditable, regulator-ready systems.

NuWare continues to partner with the client to expand AI-driven analytics to new asset classes, integrate ESG scoring into portfolio construction, and explore generative AI agents for research summarization and compliance monitoring, keeping the firm at the forefront of data-driven investing.

Key Highlights

• • Industry: Financial Services (Asset Management)
• • Services Delivered: Cloud & Infrastructure, Data Engineering, AI/ML Modeling, RPA, Trade Order Modernization
• • Business Outcomes: Faster decisions, reduced manual effort, improved compliance, scalable architecture
• • Technologies: Hybrid Cloud, SQL Server, Oracle, PostgreSQL, LSTMs, Transformer Models, RPA Tools, SHAP Explainability Frameworks