Behind the Scenes: How We Built AI Systems for Finance (Partner With Us)

Behind the Scenes: How We Built AI Systems for Finance

Join us online to get an exclusive look at the tech and teamwork that powers our AI solutions for the finance world. Curious about how we tackle challenges and innovate? This is your chance to partner with us and dive into the journey behind the scenes. Don't miss out on this insider experience!

Behind the Scenes: How We Built AI Systems for Finance (and How You Can Partner With Us)

Thursday, November 27, 2025 at 10:30 AM ET (Online Event)

I. Opening & Welcome

• Quick introduction: who we are and why this session matters
• What attendees will learn today
• Overview of the agenda

II. Why AI in Finance? The Real Problems We Set Out to Solve

• Inefficiencies in traditional banking & financial operations
• Challenges in underwriting, risk management, scoring, and forecasting
• Why manual processes limit scale and accuracy
• The opportunity: How AI fixes these problems in practical, measurable ways

III. Behind the Scenes: How We Built Our AI Financial Systems

A transparent walkthrough of our internal development approach

A. Building the Data Foundation

• Data collection: financial statements, cash flows, behavioral data
• Data cleaning and structuring for predictive accuracy
• Ethical and compliant data-use considerations

B. Designing Decision Models

• Credit risk model architecture
• Predictive scoring variables
• How we train and validate models
• The role of human-in-the-loop oversight

C. Workflow Automation & Integrations

• Automating loan origination processes
• Integrating AI into existing bank/fintech systems
• Eliminating friction in decision-making

D. The Tech Stack (Non-technical Explanation)

• What tools we use
• Why we chose them
• Speed, scalability, and reliability factors

IV. Real Business Cases: AI in Action

Case 1 — AI-Driven Credit Scoring Improvement

• Better approval decisions
• Lower default ratios
• Faster turnaround time

Case 2 — Automated Loan Origination (US Use Case)

• Reduction of underwriting time
• Improved customer experience
• Cost savings

Case 3 — Predictive Portfolio Risk Alerts

• Early warning detections
• Prevention of portfolio deterioration

Case 4 — Startup Valuation Predictive Model

• More accurate pre-revenue valuations
• Better investor decision support

V. Demo: Inside the AI Engine

VI. Opportunities to Collaborate With Us

Structured collaboration options:

A. Strategic Partnership

Co-development, shared IP, long-term cooperation.

B. Joint Investment Opportunities

Build and scale new solutions together.

C. White-Labeling or Licensing Our AI Models

Banks, fintechs, lenders, advisory firms, and investment companies.

D. Custom AI Solutions

Tailored models built for specific business problems.

E. Pilot Programs (Limited Spots)

VIII. Open Q&A

IX. Closing & Next Steps