1000+ Prompts to Transform the Future of Loan/Credit Underwriting
This course, Generative AI for Loan Underwriters, offers a cutting-edge curriculum designed to transform traditional credit assessment through the power of AI. It begins with a foundational overview of Generative AI, explaining how large language models (LLMs) like GPT can automate document generation, reasoning, and decision support. Learners are introduced to Loan Origination Systems (LOS) and how AI integrates into underwriting workflows. A deep dive into underwriting process mapping shows where AI can bring the most value—from initial screening to final credit approval. Prompt engineering is a core pillar, teaching participants how to frame effective queries for AI systems using instructional and analytical prompts. With techniques like zero-shot, one-shot, and few-shot prompting, learners simulate real-world underwriting scenarios.
What you’ll learn
- Understand the fundamentals of Generative AI and how it applies to credit assessment and underwriting tasks..
- Access and use a curated library of 1000+ prompts for real-world underwriting scenarios and documentation tasks..
- Navigate the structure and functionality of Loan Origination Systems (LOS) and identify where AI fits into the underwriting workflow..
- Map the traditional underwriting process and discover opportunities for AI integration and automation..
- Master Prompt Engineering techniques including zero-shot, one-shot, and few-shot prompting to extract, analyze, and summarize borrower data..
- Differentiate between instructional prompts for automation and analytical prompts for reasoning and decision support..
- Use prompt chaining to guide large language models (LLMs) through multi-step credit analysis tasks..
- Extract structured data from bank statements, paystubs..
- Generate clear summaries of borrower income, expenses, and financial inconsistencies using AI..
- Automate key underwriting components such as document checklists, risk summaries, and creditworthiness profiles..
- Detect financial red flags, suspicious transactions, and risk indicators with prompt-based analysis..
- Automate AML and KYC workflows and ensure regulatory alignment using compliance-focused prompt templates..
- Simulate loan scenarios to evaluate risk appetite and generate AI-backed recommendations for loan terms, collateral, and limits..
- Automatically generate approval/rejection memos, credit memos, and summary reports for committee review..
- Format and present AI outputs in markdown documents, slides, and audit trails suitable for both internal and external stakeholders..
- Design explainable and transparent AI outputs aligned with Fair Lending, AML, and ECOA requirements..
Course Content
- Introduction to Generative AI –> 1 lecture • 3min.
- Downloadable files –> 1 lecture • 1min.
- Understanding the Loan Underwriting Lifecycle –> 2 lectures • 5min.
- Prompt Engineering for Underwriting –> 4 lectures • 12min.
- AI-Powered Document Analysis –> 3 lectures • 10min.
- Borrower Risk Assessment Using AI –> 3 lectures • 8min.
- Fraud Detection and Regulatory Compliance –> 4 lectures • 10min.
- Loan Decisioning and Automation –> 3 lectures • 9min.
- Generating Underwriting Documents and Summaries –> 3 lectures • 7min.
- Human-in-the-Loop (HITL) and Auditability –> 1 lecture • 2min.
- 1000+ Prompts- Generative AI for Loan Underwriters –> 50 lectures • 1hr.
Requirements
This course, Generative AI for Loan Underwriters, offers a cutting-edge curriculum designed to transform traditional credit assessment through the power of AI. It begins with a foundational overview of Generative AI, explaining how large language models (LLMs) like GPT can automate document generation, reasoning, and decision support. Learners are introduced to Loan Origination Systems (LOS) and how AI integrates into underwriting workflows. A deep dive into underwriting process mapping shows where AI can bring the most value—from initial screening to final credit approval. Prompt engineering is a core pillar, teaching participants how to frame effective queries for AI systems using instructional and analytical prompts. With techniques like zero-shot, one-shot, and few-shot prompting, learners simulate real-world underwriting scenarios.
Advanced lectures guide learners through prompt chaining for multi-step analysis, extracting structured data from bank statements and paystubs, and summarizing borrower income and expense profiles. Modules on document automation demonstrate how prompt templates can populate underwriting checklists and generate borrower risk summaries. The course also trains learners to detect financial red flags, inconsistencies, and suspicious transactions using LLMs. Practical applications extend into AML/KYC verification workflows, compliance reporting automation, and scenario-based simulations tailored to organizational risk appetite.
Participants will use Generative AI to recommend loan terms, collateral, and limits, generate automated approval or rejection memos, and draft risk notes and credit memos in markdown or slide format. The course culminates in designing explainable AI outputs that meet audit and regulatory standards. Finally, learners gain access to a curated library of 1000+ expert-level prompts, enabling them to operationalize everything from decision summaries to QA workflows. This course is essential for underwriters, risk analysts, and lending professionals ready to embrace AI-powered transformation in credit operations.