Skip to content

The Head of Finance at "Bank X" wants to analyze the debt recovery efficiency of its partners. This analysis will help them decide on the allocation of the debt portfolio in the next quarter and determine an appropriate cooperation strategy. The goal is to ensure optimal debt recovery rates and maximize profits.

Notifications You must be signed in to change notification settings

iposoon/Collection-Analysis

Repository files navigation

[POWER BI] Collection Analysis

I. Introduction

1. Introduction to Dataset

  • Dataset: OS Collection Performance
  • The dataset includes one table containing information on debt collection by partners, organized by month for the years 2020 and 2021.

2. Data Dictionary

image

3. Business Questions

  • Which partners are the most efficient at debt recovery, and what factors contribute to their success?
  • How can the Head of Finance at Bank X optimize the allocation of the debt portfolio to maximize profits and minimize risk?
  • What strategies can the Head of Collection at Bank X implement to improve debt recovery rates and enhance cooperation with its partners?

II. Design Thinking Method

Here are the five steps of design thinking:

Step 1 - Empathize

image

Step 2 - Define

image

Step 3 - Ideate

image

Step 4 - Prototype

image

Step 5 - Review

image

III. Visualization

1. Overview

image

2. Debt Profile

image

3. (Insights) Effective debt recovery

image

IV. Insights

1, In terms of total collection

  • ASA, HMK, GLX, NDC, TCG are the top companies with a lot of debt.
  • BFC, FBI, TDO companies collect the least amount of debt.

2, In terms of Range_DPD

  • Mid-term: the companies with the highest total collection are: ASA> HMK>NDC>TCG>GLX
  • Long-term: the companies with the highest total collection are: GLX>HMK>ASA>NDC>TCG
  • Short-term: the companies with the highest total collection are: GLX>HMK>ASA>TCG>NDC
  • Deadloan: the companies with the highest total collection are: NDC>FBI>GLX>ASA

3, In terms of Recovery rate

  • The top companies with high revocery rates are: AMG>FBI>DK>HMK ., respectively.

4, Customers have a high demand for mid-term loans 37.79%, then short-term: 28.49%, long-term: 20.82%.

5, Short-term is the easiest loan to claim (the highest recovery rate).

6, In contrast, Long-term has the lowest return rate.

7, Deadloan has the highest loan ratio: unsecured Loan, Secured Loan, Credit Card.

V. Recommendations

1, If you want to collect a lot of debt (total collected): Debt allocation according to loan term to OS_company

  • Long-term: ASA, HMK, NDC
  • Mid-term: ASA, GLX, NDC
  • Short-term: GLX, ASA, HMK
  • Deadloan: NDC, FBI, GLX

2, If you want high recovery_rate Debt allocation by loan term to OS_company Long-term: TDO Mid-term: FBI, NDC

  • Short-term: AMG (super high claim rate 82.43%), FBI, NDC
  • Deadloan: HMK, NDC

3, It is necessary to consider whether the following companies should cooperate in the future because of the inefficient debt collection index: DK, HNA, BFC.

4, NDC is a company that handles debts well: like Deadloan vs other of Product_final.

5, Deadloan accounts have a high payout ratio in the last months of the year 10, 11, 12.

6, December is the month with the highest repayment rate of the year, then it drops to the lowest in February.

7, The bank should expand and promote the Mid-term loan package because it has the highest recovery rate.

About

The Head of Finance at "Bank X" wants to analyze the debt recovery efficiency of its partners. This analysis will help them decide on the allocation of the debt portfolio in the next quarter and determine an appropriate cooperation strategy. The goal is to ensure optimal debt recovery rates and maximize profits.

Topics

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published