The process is triggered when a customer submits a loan application. This initiates the agentic orchestration workflow, which consists of a set of defined tasks mapped to people, BOTs, and AI agents.
A BOT extracts necessary information from the application using advanced OCR (Optical Character Recognition) and NLP technologies. The agent converts unstructured data into a structured format, including the applicant's personal details, financial status, credit history, etc.
A loan recommendation agent gathers additional data from various internal and external systems (e.g., credit reporting agencies, taxation departments). The agent analyzes this data using machine learning algorithms to assess the applicant's loan eligibility.
Although the AI agent performs sophisticated analysis, a human-in-the-loop is essential for reviewing the agent’s recommendation. This ensures compliance with banking standards and leverages human intuition and discretion before final loan approval.
If the application is approved, BOTs calculate the loan amount, interest rates, and other terms. They then automatically update the banking system with these details, eliminating manual errors and ensuring consistency and speed.
A customer communication AI agent drafts an approval or rejection letter based on the outcome. The agent understands language nuances, ensuring the message is clear, respectful, and empathetic.
