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Product Management Analytics Question: Evaluating metrics for P2P lending platform's matching feature
Image of author vinay

Vinay

Updated Dec 4, 2024

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what metrics would you use to evaluate investree's borrower-lender matching feature?

Product Success Metrics Medium Member-only
Metric Selection Data Analysis Stakeholder Management Fintech Peer-to-Peer Lending Financial Services
Product Analytics User Acquisition Fintech Risk Management P2P Lending

Introduction

Evaluating Investree's borrower-lender matching feature 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.

Framework Overview

I'll follow a simple success metrics framework covering product context, success metrics hierarchy.

Step 1

Product Context

Investree's borrower-lender matching feature is a crucial component of their peer-to-peer lending platform. It aims to efficiently connect borrowers seeking loans with lenders looking to invest their capital. The key stakeholders include borrowers, lenders, Investree itself, and regulatory bodies.

The user flow typically involves:

  1. Borrowers submit loan applications with relevant financial information.
  2. The platform assesses borrower creditworthiness using proprietary algorithms.
  3. Approved loans are listed on the marketplace for lenders to review and invest in.
  4. Lenders browse available loans, assess risk-return profiles, and choose investments.
  5. Once fully funded, loan disbursement and repayment processes begin.

This feature is central to Investree's strategy of democratizing access to finance and generating returns for retail investors. Compared to traditional banks, Investree offers potentially higher returns for lenders and more accessible loans for borrowers.

In terms of product lifecycle, the borrower-lender matching feature is likely in the growth stage, with ongoing refinements to improve matching accuracy and user experience.

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