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Apply Design Thinking method into Problem Solving + PowerBI to generate insights related to Debt Collection of a bank

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LinhNguyen-MyLi/Collection-Analysis-PowerBi

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Collection_Anlysis_PowerBi

Introduction:

We have a dataset Operation Collection Performance of a Bank X in 2020 and 2021. One of their main core activities is collection debt via several smaller companies (partners).

Dataset structure:

Field Meaning Example
Year Year that the data is reported 2020, 2021
Month Month that the data is reported 1, 2, 3, 4, 5 .....
Os_company Companies that collect debt for Bank X GLX, DK, HMK, BFC....
Range_DPD Debt group by day 0-180, 360-720, 180-360, Deadloan....
Product_final Kind of debt Credit card, Securred Loan, ...
Payment_for_fee The amount of money that each companies collected at given month
PR_amount Principal Payment - The amount of money that you originally aggreed to pay back (remember that Interest is the cost for borrowing this Principal Payment and it won't be included in this dataset
Balance The total amount of money that need to be collected

Some definition of financial terms which help you deeply understand the meaning of insights:

  • Overdraft: an financial service that allow clients to withdraw more money from their checking bank account than what they really have in the account. Ex: if you have $100 in your bank account and make a purchase of $150, the bank may allow the transaction to go through, at the same time the bank create an overdraft of $50 and will charge interest on $50 until you pay it off.
  • Securred Loan: a loan that is given for clients who put their assests as a collateral for a loan.
  • Unsecurred Loan: the opposite of Securred Loan.
  • Deadloan: a loan that is written off since the borrower is unable to pay.

Task question:

Stakeholder of the bank want to know the effectiveness of debt collection of their partners. Base on the result stakeholder launch an efficent strategy for next fiscal quarter.

Solution:

Please first read file "Procedure of applying Design Thinking into Problem Solving Bank X case" to see how this method tackle the task question related to Bank X case. After that you can open file PowerBi Dashboard "Dashboard Collection Analysis ver 1" or "Dashboard Collection Analysis ver 2".

Note:

  • The difference between 02 version is how the data is interpreted (not about the design) but both of them generate the same insight which will be present below.

Insight about the effectiveness of debt collection:

"Overview:

  • 44% of debt is over 1080 days ( >3 years); 27% of debt is from 720 to 1080 days (2-3 years) and the rest is all Deadloans.
  • Creadit card product has the highest rate of payment (0.17%) and the following is Overdraft product (0.10%).
  • Secured loan product has the lowest rate of payment (0.02%) and it's ranked the third-highest outstanding balance, valued at 41 billion dollars. NDC company is the most successful collector related to this kind of product, their debt recovery rate is 0.03%. In 12/2020, the bank witness the highest debt recovery rate for this product (0.06%). In 10/2020, NDC company collect the most amount of payment which is over 950 million dollars. In 12/2020, FBI company collect the most amount of payment for the product which is over 1.1 billion dollars.
  • Unsecurred loan product has the highest amount of debt, which is account for nearly 50% of total debt, debt recovery average rate for this product is 0.07%. GLX, HMK and ASA are companies that well perform in collection payment for this product.

Detail: "TOP 1: NDC company

  • Their balance is highest among others which is around 45 billion dollars.
  • Debt recovery average rate: 0.09%. However, from 10/2020 NDC improved their rate to 0,15%, increased 0.06% compare to 9/2020. As the result, from 3/2021 to 5/2021, NDC ranked first in the total value of collection, nearly 5.5 billion dollars (in 3/2021).
  • NDC collect effectively with products: Credit card (debt recovery rate: 0.26%) and Others (0.32%)
  • NDC has ability for collecting bad debts. It continuously led in this field, for example, in 03/2021 it collected about 370 million dollars and in 04/2021 is over 640 million dollars."

"TOP 2: ASA company

  • Debt recovery average rate: 0.11%
  • Their rate is unstable, in 2021 their rate fluctuated in the corresponding period last year:
    • 1 and 2/2021: debt recovery rate lower than the rate of same period last year, in detail, 1/2020 = 0.2%, 1/2021 = 0.14%; 2/2020 = 0.28%, 2/2021 = 0.06%
    • 3, 4 and 5/2021: debt recovery rate is improved which increased significant, in detail, 3/2020 = 0.15%, 3/2021 = 0.17%; 4/2020 = 0.08, 4/2021 = 0.12%; 5/2020 = 0.11%, 5/2021 = 0.06%
  • ASA collect effectively with Overdraft product, their debt recovery rate is 0.26%

"TOP 3: GLX company

  • Debt recovery average rate: 0.11%. Their rate dropped dramatic in 2021
  • Their adventage is Overdraft và HHB products.

" Others:

  • Debt recovery rates 2021 of GLX, HNA, DK and AMG have an positive trend compare to 2021.
  • Debt recovery rate of FBI is quite low (0.03%), its adventage is HHB product.

Recomendation for Bank X based on generated insights:

  • Launch ranking strategy: give reward for those companies that have outstanding performance.

  • Allocation debt portfolio according to their strongest point:

    • NDC: Other, Credit Card, Secured Loan

    • ASA: Overdraft, Unsecured Loan

    • GLX: Overdraft, HHB, Unsecured Loan

    • FBI: HHB, Secured Loan

Please make proper credit if you want to use all my content (except the dataset)

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Apply Design Thinking method into Problem Solving + PowerBI to generate insights related to Debt Collection of a bank

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