Banking App PFM & CX Training Datasets + LLM Fine-Tuning

The labeling team will annotate a financial conversation dataset for an AI financial advisor.
Each sample will include:
Intent classification (e.g., spending insight, budgeting, card support)
Transaction & Merchant category classification
Assistant response labeling (tone, completeness, professionalism)
Function-call tagging for backend data queries (get_user_summary, get_transactions, run_custom_sql)
SQL validation labeling (mark if query is safe, parameterized, and read-only)
Annotators will produce structured JSON records containing the user query, labeled intent, function name (if applicable), arguments, and assistant reply.
Required skills:
Familiarity with personal finance terminology
Experience labeling chatbot or conversational data
Understanding of function calling / API-style structured data
Basic SQL literacy to identify safe vs unsafe queries