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verify-tagShould This Loan be Approved or Denied?

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数据标识:D17222516312201143

发布时间:2024/07/29

以下为卖家选择提供的数据验证报告:

数据描述

Context

The dataset is from the U.S. Small Business Administration (SBA)

The U.S. SBA was founded in 1953 on the principle of promoting and assisting small enterprises in the U.S. credit market (SBA Overview and History, US Small Business Administration (2015)). Small businesses have been a primary source of job creation in the United States; therefore, fostering small business formation and growth has social benefits by creating job opportunities and reducing unemployment.

There have been many success stories of start-ups receiving SBA loan guarantees such as FedEx and Apple Computer. However, there have also been stories of small businesses and/or start-ups that have defaulted on their SBA-guaranteed loans.

Content

Shape of the data: 899164 rows and 27 columns

Data Dictionary

Variable Name Description
LoanNr_ChkDgt Identifier Primary key
Name Borrower name
City Borrower city
State Borrower state
Zip Borrower zip code
Bank Bank name
BankState Bank state
NAICS North American industry classification system code
ApprovalDate Date SBA commitment issued
ApprovalFY Fiscal year of commitment
Term Loan term in months
NoEmp Number of business employees
NewExist 1 = Existing business, 2 = New business
CreateJob Number of jobs created
RetainedJob Number of jobs retained
FranchiseCode Franchise code, (00000 or 00001) = No franchise
UrbanRural 1 = Urban, 2 = rural, 0 = undefined
RevLineCr Revolving line of credit: Y = Yes, N = No
LowDoc LowDoc Loan Program: Y = Yes, N = No
ChgOffDate The date when a loan is declared to be in default
DisbursementDate Disbursement date
DisbursementGross Amount disbursed
BalanceGross Gross amount outstanding
MIS_Status Loan status charged off = CHGOFF, Paid in full =PIF
ChgOffPrinGr Charged-off amount
GrAppv Gross amount of loan approved by bank
SBA_Appv SBA’s guaranteed amount of approved loan

Description of the first two digits of NAICS.

Sector Description
11 Agriculture, forestry, fishing and hunting
21 Mining, quarrying, and oil and gas extraction
22 Utilities
23 Construction
31–33 Manufacturing
42 Wholesale trade
44–45 Retail trade
48–49 Transportation and warehousing
51 Information
52 Finance and insurance
53 Real estate and rental and leasing
54 Professional, scientific, and technical services
55 Management of companies and enterprises
56 Administrative and support and waste management and remediation services
61 Educational services
62 Health care and social assistance
71 Arts, entertainment, and recreation
72 Accommodation and food services
81 Other services (except public administration) 92 Public administration

Acknowledgements

Original data set id from “Should This Loan be Approved or Denied?”: A Large Dataset with Class Assignment Guidelines. by: Min Li, Amy Mickel & Stanley Taylor

To link to this article: https://doi.org/10.1080/10691898.2018.1434342

Inspiration

Good luck with predictions!

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Should This Loan be Approved or Denied?
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