Baselight

BigQuery Fintech Dataset

Comprehensive fintech data for loan and customer analysis.

@kaggle.mustafakeser4_bigquery_fintech_dataset

Loan
@kaggle.mustafakeser4_bigquery_fintech_dataset.loan

  • 22.29 MB
  • 270299 rows
  • 18 columns
loan_id

Loan Id

customer_id

Customer Id

loan_status

Loan Status

loan_amount

Loan Amount

state

State

funded_amount

Funded Amount

term

Term

int_rate

Int Rate

installment

Installment

grade

Grade

issue_d

Issue D

issue_date

Issue Date

issue_year

Issue Year

pymnt_plan

Pymnt Plan

type

Type

purpose

Purpose

description

Description

notes

Notes

1079b'\x8d\x1es\xf1\xfep\xba\xfb/\x18,i\xbd\xd5 L4\xf3\xeds(\x13z\xe82\x81h\xad\xbb\xa6\xa9Z'Fully Paid1000MI1000 36 months0.229538.689999FJun-13June 20132013INDIVIDUALmovingMoving loandesc
1613b"-3\xd4(\x15\xe4@\x08\xab\x11|\xf7\x01\xe8\x86\\me\xd6\x0f\x80\xf1Bd\xa2\xdc\xfe\xd9\x15{'\x1c"Fully Paid1200AZ1200 36 months0.162942.369999DSep-14September 20142014INDIVIDUALmovingMoving and relocationdesc
1865b'\x87\xa7\xb6\x9aW\n(P\x08\xbb?@~\x8c\xe1\x04i\x98\x1b\x94\xc1\np\xff\xc24\xfc\xdd\xcdF\x1a\x0f'Fully Paid1400NV1400 36 months0.111445.93BOct-12October 20122012INDIVIDUALmedicalmedical expensesdesc
3575b'\xc5\xf4\xfe\xd8k\xced_*uq\x9a\xd6\x8c?t\x18\xad\x1c\x8a\xff\xd8\xe1/\x1eD\xfaD\xef\x8a\xba\xd0'Current1975NY1975 36 months0.104964.190002BDec-14December 20142014INDIVIDUALmajor_purchaseMajor purchasedesc
5259b"\x13\xe7@\xa2F\xe7S\xf9'\rlv<i*\x04\xd0uQ\xe5\x89U\xb4\t\x19\xf2\xa3G\x80\x89\xb60"Fully Paid2000GA2000 36 months0.187573.059998DJan-13January 20132013INDIVIDUALmajor_purchaseMajor purchasedesc
5943b"\xa4w\xfdm\xc7Ud\xa6\xdd_\xaeS_\xcbe\xcc\xa6\xf7O\x08\xda\xd1\xdc\xac\xaa\xbb\xf95\x12\x07'-"Charged Off2200LA2200 36 months0.211583.059998EAug-13August 20132013INDIVIDUALotherConsolidatingdesc
6025b'r\xdc\x19[\xfdL\xb2?Q\xd2\xe2\xe89\x95\x85|\n\x8a\x8eBu\x9d\x85\xf8\x1d\xe9\x1d\x1a\x059w~'Fully Paid2300FL2300 36 months0.066270.620003AApr-13April 20132013INDIVIDUALmajor_purchaseAR15 Purchasedesc
6205b'\xcf\x1aL3\xdf%\xb8\x94B\xa5\x1ds\xe3\x08\x01\xc2\x9f\xa4\xdd\xfc\xc8>\xf3x\x01,\xba\x14\x81\xe6\x8d#'Fully Paid2400OR2400 36 months0.07975.099998AOct-12October 20122012INDIVIDUALdebt_consolidationDebt consolidationdesc
7365b'\xa0EH\x17y\x03P\xe7v"\x9f\x12w\x19\xd7\xd3\xfet\x8au\xe8\xdcs\xdd\xb7C=\ng\x08c\xd6'Charged Off2500TN2500 36 months0.121283.18BMar-13March 20132013INDIVIDUALdebt_consolidationpayoff billdesc
7464b'\x0cR\xb0K\x06K\xc8\x9c\xff\x8a\xa3\xc5\x86sU\x91\x12\x17\xce\xfa\x1f\xe1\xff\xfb\xbc\x10M\x97:^\xf6\x91'Current2500IN2500 36 months0.129984.230003CSep-14September 20142014INDIVIDUALhome_improvementHome improvementdesc

CREATE TABLE loan (
  "loan_id" BIGINT,
  "customer_id" VARCHAR,
  "loan_status" VARCHAR,
  "loan_amount" DOUBLE,
  "state" VARCHAR,
  "funded_amount" DOUBLE,
  "term" VARCHAR,
  "int_rate" DOUBLE,
  "installment" DOUBLE,
  "grade" VARCHAR,
  "issue_d" VARCHAR,
  "issue_date" VARCHAR,
  "issue_year" DOUBLE,
  "pymnt_plan" BOOLEAN,
  "type" VARCHAR,
  "purpose" VARCHAR,
  "description" VARCHAR,
  "notes" VARCHAR
);

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