Decision Intelligence in Financial Services
Engineering executive dashboards, automated financial and investor reporting, and governed AI infrastructure for asset managers, capital markets, and financial institutions.
Engineering reproducible automation and decision intelligence for complex financial systems
Investment funds, capital markets teams, banks, and financial institutions face an ever-growing volume of portfolio data, multi-venue trade feeds, investor reporting deadlines, and fragmented spreadsheets. Analytical capacity stalls when senior analysts and risk officers spend weeks manually reconciling workbooks and Word documents before decisions can be made.
Data Sense bridges FRM-certified financial domain expertise with production software engineering. Proven at global regulatory scale, we replace fragile manual compilation with automated reporting pipelines, executive decision dashboards, and governed AI infrastructure.
Covering ~85% of all global investment funds across nearly 40 IOSCO jurisdictions
Enabled jurisdictions to self-discover and resolve reporting anomalies
Automated end-to-end regulatory ETL and publication pipelines
OTC benchmark transition surveillance for the Ontario Securities Commission
Proven in Regulatory & Capital Markets Environments
Production supervisory portals, executive OTC derivatives dashboards, automated statistical publications, and interactive Excel-based dashboards.
Global Investment Funds Statistics Dashboard
Built the backend ETL pipeline and Plotly Dash interactive portal covering USD 72.5 Trillion in global net asset value (~85% of all global investment funds) across nearly 40 jurisdictions. Improved reported data quality by 40%, enabled by jurisdictions being able to more easily identify and discover issues in reported information, while transforming a static 60+ page report and 500,000+ rows of EDGAR data into an interactive global supervisory platform.
“Completely automated the process, resulting in a 75% reduction in time-to-report production. His modernization of the IFSR report and dashboard also drove a 60% increase in survey participation.”
Executive OTC Derivatives Market Share Dashboard
Engineered an executive decision-support dashboard benchmarking Canada's OTC Interest Rate derivatives market against global BIS, DTCC, ICE, and CME trade repository data. Built with Python ETL (automated FX normalization and maturity bucketing) and Tableau Server around a strict 5-to-10-second rule for policy lawyers, risk committees, and senior leadership.
“Nick was the technical expert our derivatives team relied on. He has a rare ability to distill complex technical concepts into clear, concise advice that directly supported our legal and policy objectives.”
Counterparty & Transaction Network Graph Dashboard in Excel
Designed a zero-dependency interactive network graph dashboard built natively inside Microsoft Excel using VBA, structured pivot tables, and dynamic shape manipulation. Visualizes $1.35T+ in notional counterparty exposure, weighted node-edge relationships, and multi-product connectivity (Swaps, Options, CFDs, Forwards) without external BI licenses.
Regulatory Report Evolution
Transformed an unformatted, hand-assembled Microsoft Word report into a fully automated publishing pipeline built in Python with Jinja2 and Quarto. Structured statistical inputs dynamically update report narratives, tables, and customizable 'deep dive boxes', generating both brand-aligned Word templates and an interactive web-based report.
CORRA OTC Derivatives Trend Analytics
Engineered the data pipeline behind the first public-facing report published by the OSC Derivatives branch, showcasing how trade repository data provides market transparency and oversight during the critical CDOR-to-CORRA transition. Cross-referenced 10M+ rows of derivatives position data against activity data to align, reconcile, and ensure reported trades were accurate and up to date.
Endorsed by Regulatory & Academic Leaders
Verified recommendations from senior leadership at international securities commissions and regulatory institutions.
“Nick delivered exceptional results on the Investment Funds Statistics Report (IFSR) project. He took ownership of the ETL, redesigned the report structure, and completely automated the process, resulting in a 75% reduction in time-to-report production. His modernization of the IFSR report and dashboard also drove a 60% increase in survey participation.”
“Nick was the technical expert our derivatives team relied on. He has a rare ability to distill complex technical concepts like crypto staking or derivatives data analysis into clear, concise advice that directly supported our legal and policy objectives. He is extremely dedicated to advancing thinking in the areas his work touched on and was an integral part of our oversight team.”
“Nick has a rare ability to not only understand complex policy challenges, like leverage in NBFI, but also to build the elegant, automated solutions required to monitor and manage them effectively. He understands markets deeply, he understands data deeply too and he can bring it all together. It is indeed rare to find someone who can speak to policy makers in their language when it comes to data.”
Software & Governance Infrastructure
Alongside our advisory mandates, we engineer open-source BI compilers, Model Context Protocol (MCP) servers, and runtime policy engines for deterministic AI governance.
SimBI & Power BI MCP
Combines natural-language and reference-image dashboard compilation with the open Model Context Protocol server. SimBI inspects raw data, detects schema shapes, unpivots wide time-series in Power Query M, authors Tabular Model Definition Language (TMDL), enforces strict DAX linting, and emits production-ready .pbip project files in under 10 minutes.
- Reference Image & Prompt to .pbip EmissionInspects raw datasets or reference mockups and compiles complete, production-grade Power BI projects ready for git version control.
- Wide Time-Series UnpivotingAutomatically detects wide economic and financial formats, creating Power Query M unpivot partitions into star schemas.
- Model Context Protocol Tooling25+ programmatic tools for Claude, Cursor, Gemini, and coding agents to author, refactor, and lint DAX measures with zero manual UI work.
SimBI
AI agents should propose actions, never authorize them. SimBI introduces Autonomous Decision Infrastructure (ADI) to govern the boundary between an agent's proposed operation and actual execution. Before an action touches live systems, SimBI normalizes the bounded operation, resolves authorized context and delegation chains, evaluates deterministic policy rules, and attaches enforceable runtime obligations.
Every execution produces an immutable receipt linking caller identity, policy state, and operational context for audit-proof verification. SimBI does not claim to replace enterprise IAM, define universal interception, or guarantee LLM inputs are truthful. Instead, it provides the deterministic runtime control and cryptographic evidence required to deploy autonomous agents in regulated, high-stakes environments.
- The Bounded Operation as Control UnitNormalizes the exact operation, target resource, canonical arguments, and delegation chain rather than trusting advisory prompt guardrails.
- Deterministic Decision SemanticsResolves operations into strict outcomes (ALLOW, DENY, ESCALATE, CONDITIONAL, INDETERMINATE) with typed pre- and post-execution obligations.
- Execution Boundaries (PEP) & EvidenceEnforces decisions at integrated execution boundaries and records verifiable execution receipts linking identity, context, and policy state.
VaultGraph
A local-first knowledge and data environment built around Obsidian vaults and knowledge graphs. It bridges human documentation, typed semantic relationships (Vault-LD), and local deterministic SQL computation (DuckDB), freezing analytical results as durable, version-controlled markdown artifacts that feed back into the graph.
- Typed Semantic Relationships (Vault-LD)Upgrades YAML frontmatter into a queryable knowledge graph connecting dashboards, datasets, ETL pipelines, and analytical decisions.
- Deterministic Local SQL (DuckDB)Executes queries against local datasets, freezing analytical snapshots as durable, citable markdown tables with tamper-evident provenance.
- Closed-Loop Agent ReasoningAI agents traverse graph dependencies, compute verified metrics, and write structured findings back into the vault for human review.
Want SimBI, VaultGraph, or our MCP server deployed in your private environment?
We deploy on-premise or within your isolated cloud perimeter (AWS, Azure, GCP) with enterprise SSO, role-based access control, and complete compliance documentation.
Core Technical Services
Specialized engineering across the full analytical lifecycle, from raw data ingestion and validation to executive dashboards and regulatory publications.
Dashboard Development
Production supervisory and executive dashboards in Power BI, Apache Superset, Plotly Dash, Tableau, React/Next.js, and native Excel.
Regulatory Reporting Automation
End-to-end automated pipelines in Python, Jinja2, Quarto, and Apache Airflow producing brand-aligned Word, PDF, HTML, and XBRL filings.
Financial Data Governance & AI Lineage
Finance data lineage for AI, executable metadata, BCBS 239 controls, and compliant synthetic data with immutable audit logs.
Excel Process Automation
Migrate fragile multi-workbook spreadsheets to Python/SQL pipelines or engineer zero-dependency native Excel network dashboards.
Power BI, Microsoft Fabric & MCP Automation
Microsoft Fabric & OneLake engineering, star-schema modeling, DAX optimization, Row-Level Security (RLS), and Power BI MCP compilation.
Decision Intelligence & Advanced Analytics
KPI architectures, semantic metric layers, Apache Iceberg/DuckDB lakehouses, and AI policy engines across BI and AI.
Structured Delivery Models
Every engagement is scoped with explicit deliverables, deterministic validation criteria, and full code and documentation ownership upon handover.
Diagnostic & Architecture Prototype
Designed for teams that need an immediate audit of a reporting bottleneck or a production-grade proof-of-concept dashboard before committing to a broader rollout.
- End-to-end audit of existing spreadsheets, SQL queries, or semantic models
- Automated data validation & reconciliation specification
- 1 working production dashboard or automated reporting prototype
- Documented architecture roadmap & effort estimate
End-to-End System Delivery
Full lifecycle design, engineering, validation, and deployment of regulatory reporting pipelines, supervisory portals, or enterprise Power BI / Plotly Dash systems.
- Automated multi-source ETL pipeline with deterministic validation gates
- Custom interactive dashboard or publication-ready PDF/HTML report generator
- Row-by-row parallel reconciliation against legacy outputs
- Full Git version-controlled codebase & internal team enablement
Principal Advisory & Governance
Continuous principal-led analytical engineering and governance oversight for regulatory commissions, investment funds, and scaling finance organizations.
- Recurring reporting cycle execution (monthly, quarterly, annual filings)
- Semantic metric governance (SimBI ADI) & cryptographic lineage (VaultGraph)
- Ongoing DAX, Python, and data warehouse optimization
- Direct FRM-certified principal advisory for policy and risk committees
From Fragmented Data to Verified Production
A disciplined four-phase engineering methodology designed for zero production disruption and row-by-row auditability.
Discovery & Schema Audit
We audit your existing spreadsheets, SQL databases, or regulatory templates, mapping every data source, transformation rule, and failure point.
Pipeline & Semantic Architecture
We engineer automated ingestion pipelines, deterministic validation checks, and governed star schemas or declarative BI models.
Parallel Validation & Visual Build
We build the executive dashboard or publication generator and reconcile every figure cell-by-cell against historical reports.
Handover & Team Enablement
We deploy into your environment, transfer full repository ownership, and train your internal analysts to operate and extend the system.
Why Financial Services & High-Stakes Teams Choose Data Sense
Combining quantitative financial domain credentials with hands-on software engineering and open-source transparency.
Decision-Backward Engineering
We measure engagements by regulatory accuracy, time saved, and executive adoption, structuring every dashboard and pipeline around real operational decisions.
Principal-Led Execution
No junior analysts learning on your mandate. Every system is architected and delivered directly by our FRM-certified principal with 15+ years across global regulators and capital markets.
Open & Reproducible Code
Zero black-box lock-in. We build with inspectable Python, SQL, Microsoft Fabric, Power BI PBIR/TMDL, the Apache ecosystem (Airflow, Superset, Iceberg), Plotly Dash, and native Excel so your team owns the entire repository.
Governed AI & Semantic Rigor
From our SimBI Power BI MCP compiler to SimBI ADI runtime policy controls and VaultGraph lineage, we enforce deterministic accuracy across BI and AI.
- Power BI (PBIR / TMDL / MCP)
- Apache Superset
- Plotly Dash
- Tableau Server
- Native Excel & VBA
- Microsoft Fabric & OneLake
- Snowflake & BigQuery
- Azure Synapse & Data Factory
- PostgreSQL & SQL Server
- Direct Lake Semantic Models
- Apache Airflow
- Apache Iceberg
- Apache Spark
- Apache Arrow & Parquet
- DuckDB
- Python, Jinja2 & Quarto
- Automated Word & PDF Templates
- SimBI ADI Policy Engine
- VaultGraph (Vault-LD)
- XBRL / iXBRL & Trade Filings
Nicholas Lombardi
Nicholas holds the FRM certification and an MA in International Economics and Finance, with over 15 years in data analytics across startups and domestic and international financial regulators. He specialises in turning complex regulatory and financial data into transparent, reproducible, and actionable intelligence.
Answers for Technical & Regulatory Leaders
Have a specific question about regulatory data validation, Power BI MCP, or custom dashboard architecture?
Ask Our Principal Directly→What does Data Sense do?
Data Sense provides regulatory reporting automation, custom dashboard development, financial data governance, and decision intelligence for governance, risk, compliance, and finance teams. We automate recurring regulatory publications (using Python, Jinja2, and Quarto), build interactive dashboards in Power BI, Microsoft Fabric, Apache Superset, Plotly Dash, Tableau, and native Excel, and engineer governed semantic layers (SimBI) and cryptographic provenance systems (VaultGraph).
What industries and institutions does Data Sense serve?
We serve international financial regulators, securities commissions, central banks, capital markets institutions, asset managers, and high-growth operating teams. Our work includes global investment fund surveillance and automated reporting for IOSCO, OTC derivatives analytics for the Ontario Securities Commission (OSC), and custom analytics for enterprise and SMB finance teams.
How is Data Sense different from generalist data consulting firms?
Every engagement is architected and led directly by our FRM-certified principal, Nicholas Lombardi, who holds an MA in International Economics and Finance and brings 15+ years of regulatory and capital markets experience. We combine deep financial domain rigor with hands-on software engineering, handing over documented, version-controlled pipelines with zero vendor lock-in.
What technologies and platforms does Data Sense specialize in?
We work across Python (Jinja2, Quarto, Pandas/Polars), SQL, DuckDB, Microsoft Fabric, Power BI (including PBIR/TMDL and our SimBI Power BI MCP compiler), Plotly Dash, Tableau, React/Next.js, and advanced native Excel/VBA. We also build on the modern Apache ecosystem (Apache Airflow, Apache Superset, Apache Iceberg, Apache Spark, Apache Arrow/Parquet) as well as Snowflake, BigQuery, Azure Synapse, and PostgreSQL.
How do I get started with Data Sense?
Reach out through the consultation form below or email info@datasenseco.com. We start with a direct technical discovery call to understand your reporting, dashboard, or governance bottleneck, and provide a clearly scoped architecture and delivery timeline before any work begins.
Discuss Your Data & Reporting Architecture
Schedule a 30-minute technical discovery call directly with our principal. No sales development representatives, no generic pitch decks.