What metrics would you use to evaluate QI Tech's automated loan origination platform?

Introduction

Evaluating QI Tech's automated loan origination platform requires a comprehensive approach to product success metrics. To address this challenge effectively, I'll follow a structured framework that covers core metrics, supporting indicators, and risk factors while considering all key stakeholders. This approach will help us gain a holistic view of the platform's performance and impact.

Step 1

Product Context

QI Tech's automated loan origination platform is a software solution designed to streamline the process of evaluating and approving loan applications. The platform leverages artificial intelligence and machine learning algorithms to analyze applicant data, assess creditworthiness, and make rapid lending decisions.

Key stakeholders include:

1. Lenders (banks, credit unions, fintech companies)
2. Loan applicants (individuals and businesses)
3. Regulatory bodies
4. QI Tech's internal teams (product, engineering, sales)

The user flow typically involves:

1. Applicant submission: Users input their personal and financial information through a digital interface.
2. Data verification: The platform automatically verifies the submitted information against various databases and credit bureaus.
3. Risk assessment: AI algorithms analyze the applicant's data to determine creditworthiness and assign a risk score.
4. Decision-making: Based on the risk assessment, the platform either approves, denies, or flags the application for manual review.
5. Offer generation: For approved applications, the platform generates loan terms and conditions.

This platform aligns with QI Tech's broader strategy of digitizing and optimizing financial services processes. It competes with traditional manual underwriting methods and other automated lending platforms like Upstart and Blend. The product is in the growth stage, with increasing adoption among lenders but still facing challenges in market penetration and regulatory compliance.

Software-specific considerations:

• Platform: Cloud-based SaaS solution
• Integration points: Core banking systems, credit bureaus, fraud detection services
• Deployment model: Customizable white-label solution for lenders