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FinBot is an AI-driven financial complaint classification and resolution system designed to automate the triaging, categorization, and response suggestion for consumer financial issues. Powered by sentence embeddings, hierarchical machine learning models, and a semantic knowledge base, FinBot efficiently understands and routes customer complaints using advanced Natural Language Processing (NLP) techniques.

Built using real-world data from the Consumer Financial Protection Bureau (CFPB), FinBot serves as the backbone for:

• AI-powered customer support bots

• Complaint routing systems

• Semantic search engines in compliance and financial service platforms

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• Automate the classification of financial complaints into Product → Sub-product → Issue categories

• Build a semantic knowledge base from real-world complaints for retrieval-based guidance

• Enable natural language understanding for chatbots and support agents

• Achieve scalable, interpretable, and modular deployment-ready architecture

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Feature	Description
Complaint Narrative	User’s description of the issue (free text)
Product	High-level category (e.g., “Mortgage”, “Credit card”)
Sub-product	Specific subcategory (e.g., “FHA mortgage”)
Issue	Nature of complaint (e.g., “Incorrect info on report”)

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FinBot demonstrates a complete pipeline for understanding, classifying, and resolving customer complaints using modern NLP techniques. With a modular design and high accuracy at every step, it can be integrated into enterprise-scale customer support, compliance triaging, or regulatory monitoring systems.

It blends:

• 🧠 Semantic representation (via BERT)

• 🧩 Hierarchical ML classification

• 🔍 Knowledge-based semantic retrieval