This title slide features the main text "Corporate Lending Deal Annual Review Automation with Agentic AI." Its subtitle states "Revolutionizing Annual Reviews with Agentic AI."

Corporate Lending Deal Annual Review Automation with Agentic AI

Revolutionizing Annual Reviews with Agentic AI.

Source: Elegant AI automation background in corporate banking.

This slide overviews a use case for annual reviews of over 1,000 corporate lending deals, delivering 67% faster processing with error-free insights. It highlights multi-agent AI that automates data gathering and analysis while ensuring governance and compliance.

Use Case Overview

• Annual reviews of 1000+ corporate lending deals
• 67% faster processing with error-free insights
• Multi-agent AI automates data gathering and analysis
• Ensures governance and compliance throughout

Source: Annual review process and use case for agentic AI.pptx

The Annual Review Process Lifecycle workflow outlines seven automated phases: Data Collection, Risk Analysis, Compliance Check, Governance, Reporting, Insights, and Data Update. Each phase lists key activities, the responsible AI Agent, and its estimated automated duration, totaling about 13.5 hours.

Annual Review Process Lifecycle

{ "headers": [ "Phase", "Key Activities", "AI Agent", "Duration (Automated)" ], "rows": [ [ "Data Collection", "Gather borrower financials, market data, and updates from multiple sources", "Data Ingestion Agent", "2 hours" ], [ "Risk Analysis", "Perform credit risk assessment, stress testing, and exposure analysis", "Risk Analysis Agent", "4 hours" ], [ "Compliance Check", "Validate KYC, AML, regulatory requirements, and internal policies", "Compliance Agent", "1 hour" ], [ "Governance", "Apply decision rules, escalate high-risk cases for human review", "Governance Agent", "3 hours" ], [ "Reporting", "Generate standardized reports and interactive dashboards", "Reporting Agent", "1 hour" ], [ "Insights", "Derive actionable recommendations and forward-looking intelligence", "Insights Agent", "2 hours" ], [ "Data Update", "Incorporate insights back into data repository for next cycle", "Data Ingestion Agent", "30 minutes" ] ] }

The AI Agent Governance Tree slide depicts a workflow with five phases: Supervise (Supervisor Agent 🛡️), Data Ingestion (Alice 👩), Analyze (Bob 👨), Risk Assessment (Carol 👩), and Compliance & Report (Dave 👨 & Eve 👩). Each phase assigns key tasks to its owner, from overseeing the process and preparing data to financial analysis, risk evaluation, regulatory checks, and final reporting.

AI Agent Governance Tree

{ "headers": [ "Phase", "Owner", "Avatar", "Key Tasks" ], "rows": [ [ "Supervise", "Supervisor Agent", "🛡️", "Oversees entire process and coordinates agents" ], [ "Data Ingestion", "Data Agent", "👩 Alice", "Gather, clean, and prepare deal data" ], [ "Analyze", "Analyzer Agent", "👨 Bob", "Perform financial and performance analysis" ], [ "Risk Assessment", "Risk Agent", "👩 Carol", "Evaluate risks and flags" ], [ "Compliance & Report", "Compliance (Dave) & Reporter (Eve)", "👨 Dave 👩 Eve", "Check regulations and generate final report" ] ] }

Source: AIAgentGovernanceTreeforAnnualReview.docx

The "Agent Roles & Tasks" slide features a grid of six agent functions with icons. These include overseeing workflow, gathering documents, computing metrics, flagging risks, validating compliance, and generating reports.

Agent Roles & Tasks

{ "features": [ { "icon": "👨‍💼", "heading": "Oversees Workflow", "description": "Manages overall process flow and agent coordination." }, { "icon": "📁", "heading": "Gathers Documents", "description": "Collects and organizes required deal documents efficiently." }, { "icon": "📊", "heading": "Computes Metrics", "description": "Analyzes data and calculates key performance metrics." }, { "icon": "⚠️", "heading": "Flags Risks", "description": "Identifies and highlights potential risk issues." }, { "icon": "🛡️", "heading": "Validates Compliance", "description": "Ensures adherence to regulations and standards." }, { "icon": "📄", "heading": "Generates Report", "description": "Compiles and produces the final review report." } ] }

The Agent Collaboration Narrative workflow outlines five phases: Data Ingestion (Data Agent, instant), Analysis (Analyzer Agent, 2 hours), parallel Risk & Compliance Review (Risk and Compliance Agents, 4 hours), Supervisor Review (Supervisor Agent, 1 hour), and Reporting (Reporter Agent, 30 minutes). Phases are sequential with dependencies on prior steps, except for the parallel review.

Agent Collaboration Narrative

{ "headers": [ "Phase", "Agents", "Dependencies", "Duration" ], "rows": [ [ "Data Ingestion", "Data Agent", "N/A", "Instant" ], [ "Analysis", "Analyzer Agent", "Data Ingestion", "2 hours" ], [ "Risk & Compliance Review", "Risk Agent & Compliance Agent (parallel)", "Analysis", "4 hours (parallel)" ], [ "Supervisor Review", "Supervisor Agent", "Risk & Compliance Review", "1 hour" ], [ "Reporting", "Reporter Agent", "Supervisor Review", "30 min" ] ] }

Source: Annual Review Automation with Agentic AI

The slide shows the current manual review process takes 3 days per deal, reduced to 1 day with Agentic AI automation, yielding a 67% total efficiency gain. This saves 2000 analyst-days annually across 1000 deals.

Business Case & ROI

• 3: Days per Deal (Current)

Manual annual review process

• 1: Days per Deal (Automated)

Agentic AI acceleration

• 2000: Analyst-Days Saved Annually

From 1000 deals per year

• 67%: Total Efficiency Gain

Time savings percentage Source: Annual Review Automation Analysis