Primary Technologies and Tools Used to Create This Solution

PedroAtencio.ai - Financial Portfolio Copilot

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Financial Portfolio Copilot is a new project being developed with the following features:

1. AI-assisted financial analytics: Natural language interaction for portfolio, credit risk, delinquency, and executive reporting questions.
2. Curated analytics data mart: Structured fact and dimension tables that transform normalized banking data into analysis-ready datasets.
3. Exploratory data analysis: Jupyter-based profiling for table relationships, data quality, missing values, duplicate detection, and business attribute distributions.
4. Modular ETL pipeline: Python-based ingestion, validation, cleansing, joins, derived metrics, and analytics table creation.
5. SQL analytics engine: DuckDB or SQLite support for reproducible portfolio analysis without requiring enterprise database infrastructure.
6. Executive insight generation: Summaries, KPI explanations, and management-ready narratives based on validated portfolio metrics.
7. Interactive application layer: Streamlit interface for demonstrating the copilot, analytics outputs, prompts, and visual summaries.
8. AI-ready data layer: Controlled datasets designed to ground LLM responses and reduce unsupported or invented answers.
9. Visualization support: Matplotlib or Plotly charts for portfolio exposure, delinquency trends, regional performance, and risk segmentation.
10. Version-controlled delivery: GitHub repository with notebooks, SQL scripts, application code, requirements, and documentation for portfolio demonstration