Exploratory Data Analysis of Prosper Loan Data
John S. Olaobaju
February 28, 2018
Introduction
Prosper is America’s first marketplace lending platform, with over $10 billion in funded loans.
Prosper allows people to invest in each other in a way that is financially and socially rewarding. On loans, borrowers list loan requests between $2,000 and $35,000 and individual investors invest as little as $25 in each loan listing they select. Prosper handles the servicing of the loan on behalf of the matched borrowers and investors.
Prosper Funding LLC is a wholly-owned subsidiary of Prosper Marketplace, Inc.
Prosper Marketplace is backed by leading investors including Sequoia Capital, Francisco Partners, Institutional Venture Partners, and Credit Suisse NEXT Fund.
This Exploratory Data Analysis scope covers loan information for over a 100,000 people between the years 2006 and 2013.
The dataset has 81 original variables in the dataset.
This project is divided into 3 analytical segments which are Univariate Plots, Bivariate Plots, and Multivariate Plots, as well as a Reflection segment at the end that summarizes my experience and thoughts throughout this course.
Loading the Dataset and Setting Global Options
Set working directory
Getting and loading data
Prosper Loan data can be downloaded from this location: https://s3.amazonaws.com/udacity-hosted-downloads/ud651/ProsperLoanData.csv
Dataset Structure
Let’s take a look at the structure and contents of the dataset:
## 'data.frame': 113937 obs. of 81 variables:
## $ ListingKey : Factor w/ 113066 levels "00003546482094282EF90E5",..: 7180 7193 6647 6669 6686 6689 6699 6706 6687 6687 ...
## $ ListingNumber : int 193129 1209647 81716 658116 909464 1074836 750899 768193 1023355 1023355 ...
## $ ListingCreationDate : Factor w/ 113064 levels "2005-11-09 20:44:28.847000000",..: 14184 111894 6429 64760 85967 100310 72556 74019 97834 97834 ...
## $ CreditGrade : Factor w/ 9 levels "","A","AA","B",..: 5 1 8 1 1 1 1 1 1 1 ...
## $ Term : int 36 36 36 36 36 60 36 36 36 36 ...
## $ LoanStatus : Factor w/ 12 levels "Cancelled","Chargedoff",..: 3 4 3 4 4 4 4 4 4 4 ...
## $ ClosedDate : Factor w/ 2803 levels "","2005-11-25 00:00:00",..: 1138 1 1263 1 1 1 1 1 1 1 ...
## $ BorrowerAPR : num 0.165 0.12 0.283 0.125 0.246 ...
## $ BorrowerRate : num 0.158 0.092 0.275 0.0974 0.2085 ...
## $ LenderYield : num 0.138 0.082 0.24 0.0874 0.1985 ...
## $ EstimatedEffectiveYield : num NA 0.0796 NA 0.0849 0.1832 ...
## $ EstimatedLoss : num NA 0.0249 NA 0.0249 0.0925 ...
## $ EstimatedReturn : num NA 0.0547 NA 0.06 0.0907 ...
## $ ProsperRating..numeric. : int NA 6 NA 6 3 5 2 4 7 7 ...
## $ ProsperRating..Alpha. : Factor w/ 8 levels "","A","AA","B",..: 1 2 1 2 6 4 7 5 3 3 ...
## $ ProsperScore : num NA 7 NA 9 4 10 2 4 9 11 ...
## $ ListingCategory..numeric. : int 0 2 0 16 2 1 1 2 7 7 ...
## $ BorrowerState : Factor w/ 52 levels "","AK","AL","AR",..: 7 7 12 12 25 34 18 6 16 16 ...
## $ Occupation : Factor w/ 68 levels "","Accountant/CPA",..: 37 43 37 52 21 43 50 29 24 24 ...
## $ EmploymentStatus : Factor w/ 9 levels "","Employed",..: 9 2 4 2 2 2 2 2 2 2 ...
## $ EmploymentStatusDuration : int 2 44 NA 113 44 82 172 103 269 269 ...
## $ IsBorrowerHomeowner : Factor w/ 2 levels "False","True": 2 1 1 2 2 2 1 1 2 2 ...
## $ CurrentlyInGroup : Factor w/ 2 levels "False","True": 2 1 2 1 1 1 1 1 1 1 ...
## $ GroupKey : Factor w/ 707 levels "","00343376901312423168731",..: 1 1 335 1 1 1 1 1 1 1 ...
## $ DateCreditPulled : Factor w/ 112992 levels "2005-11-09 00:30:04.487000000",..: 14347 111883 6446 64724 85857 100382 72500 73937 97888 97888 ...
## $ CreditScoreRangeLower : int 640 680 480 800 680 740 680 700 820 820 ...
## $ CreditScoreRangeUpper : int 659 699 499 819 699 759 699 719 839 839 ...
## $ FirstRecordedCreditLine : Factor w/ 11586 levels "","1947-08-24 00:00:00",..: 8639 6617 8927 2247 9498 497 8265 7685 5543 5543 ...
## $ CurrentCreditLines : int 5 14 NA 5 19 21 10 6 17 17 ...
## $ OpenCreditLines : int 4 14 NA 5 19 17 7 6 16 16 ...
## $ TotalCreditLinespast7years : int 12 29 3 29 49 49 20 10 32 32 ...
## $ OpenRevolvingAccounts : int 1 13 0 7 6 13 6 5 12 12 ...
## $ OpenRevolvingMonthlyPayment : num 24 389 0 115 220 1410 214 101 219 219 ...
## $ InquiriesLast6Months : int 3 3 0 0 1 0 0 3 1 1 ...
## $ TotalInquiries : num 3 5 1 1 9 2 0 16 6 6 ...
## $ CurrentDelinquencies : int 2 0 1 4 0 0 0 0 0 0 ...
## $ AmountDelinquent : num 472 0 NA 10056 0 ...
## $ DelinquenciesLast7Years : int 4 0 0 14 0 0 0 0 0 0 ...
## $ PublicRecordsLast10Years : int 0 1 0 0 0 0 0 1 0 0 ...
## $ PublicRecordsLast12Months : int 0 0 NA 0 0 0 0 0 0 0 ...
## $ RevolvingCreditBalance : num 0 3989 NA 1444 6193 ...
## $ BankcardUtilization : num 0 0.21 NA 0.04 0.81 0.39 0.72 0.13 0.11 0.11 ...
## $ AvailableBankcardCredit : num 1500 10266 NA 30754 695 ...
## $ TotalTrades : num 11 29 NA 26 39 47 16 10 29 29 ...
## $ TradesNeverDelinquent..percentage. : num 0.81 1 NA 0.76 0.95 1 0.68 0.8 1 1 ...
## $ TradesOpenedLast6Months : num 0 2 NA 0 2 0 0 0 1 1 ...
## $ DebtToIncomeRatio : num 0.17 0.18 0.06 0.15 0.26 0.36 0.27 0.24 0.25 0.25 ...
## $ IncomeRange : Factor w/ 8 levels "$0","$1-24,999",..: 4 5 7 4 3 3 4 4 4 4 ...
## $ IncomeVerifiable : Factor w/ 2 levels "False","True": 2 2 2 2 2 2 2 2 2 2 ...
## $ StatedMonthlyIncome : num 3083 6125 2083 2875 9583 ...
## $ LoanKey : Factor w/ 113066 levels "00003683605746079487FF7",..: 100337 69837 46303 70776 71387 86505 91250 5425 908 908 ...
## $ TotalProsperLoans : int NA NA NA NA 1 NA NA NA NA NA ...
## $ TotalProsperPaymentsBilled : int NA NA NA NA 11 NA NA NA NA NA ...
## $ OnTimeProsperPayments : int NA NA NA NA 11 NA NA NA NA NA ...
## $ ProsperPaymentsLessThanOneMonthLate: int NA NA NA NA 0 NA NA NA NA NA ...
## $ ProsperPaymentsOneMonthPlusLate : int NA NA NA NA 0 NA NA NA NA NA ...
## $ ProsperPrincipalBorrowed : num NA NA NA NA 11000 NA NA NA NA NA ...
## $ ProsperPrincipalOutstanding : num NA NA NA NA 9948 ...
## $ ScorexChangeAtTimeOfListing : int NA NA NA NA NA NA NA NA NA NA ...
## $ LoanCurrentDaysDelinquent : int 0 0 0 0 0 0 0 0 0 0 ...
## $ LoanFirstDefaultedCycleNumber : int NA NA NA NA NA NA NA NA NA NA ...
## $ LoanMonthsSinceOrigination : int 78 0 86 16 6 3 11 10 3 3 ...
## $ LoanNumber : int 19141 134815 6466 77296 102670 123257 88353 90051 121268 121268 ...
## $ LoanOriginalAmount : int 9425 10000 3001 10000 15000 15000 3000 10000 10000 10000 ...
## $ LoanOriginationDate : Factor w/ 1873 levels "2005-11-15 00:00:00",..: 426 1866 260 1535 1757 1821 1649 1666 1813 1813 ...
## $ LoanOriginationQuarter : Factor w/ 33 levels "Q1 2006","Q1 2007",..: 18 8 2 32 24 33 16 16 33 33 ...
## $ MemberKey : Factor w/ 90831 levels "00003397697413387CAF966",..: 11071 10302 33781 54939 19465 48037 60448 40951 26129 26129 ...
## $ MonthlyLoanPayment : num 330 319 123 321 564 ...
## $ LP_CustomerPayments : num 11396 0 4187 5143 2820 ...
## $ LP_CustomerPrincipalPayments : num 9425 0 3001 4091 1563 ...
## $ LP_InterestandFees : num 1971 0 1186 1052 1257 ...
## $ LP_ServiceFees : num -133.2 0 -24.2 -108 -60.3 ...
## $ LP_CollectionFees : num 0 0 0 0 0 0 0 0 0 0 ...
## $ LP_GrossPrincipalLoss : num 0 0 0 0 0 0 0 0 0 0 ...
## $ LP_NetPrincipalLoss : num 0 0 0 0 0 0 0 0 0 0 ...
## $ LP_NonPrincipalRecoverypayments : num 0 0 0 0 0 0 0 0 0 0 ...
## $ PercentFunded : num 1 1 1 1 1 1 1 1 1 1 ...
## $ Recommendations : int 0 0 0 0 0 0 0 0 0 0 ...
## $ InvestmentFromFriendsCount : int 0 0 0 0 0 0 0 0 0 0 ...
## $ InvestmentFromFriendsAmount : num 0 0 0 0 0 0 0 0 0 0 ...
## $ Investors : int 258 1 41 158 20 1 1 1 1 1 ...The structure contains lots of information. Let’s take a look at the columns (variables) names.
Column names
## [1] "ListingKey"
## [2] "ListingNumber"
## [3] "ListingCreationDate"
## [4] "CreditGrade"
## [5] "Term"
## [6] "LoanStatus"
## [7] "ClosedDate"
## [8] "BorrowerAPR"
## [9] "BorrowerRate"
## [10] "LenderYield"
## [11] "EstimatedEffectiveYield"
## [12] "EstimatedLoss"
## [13] "EstimatedReturn"
## [14] "ProsperRating..numeric."
## [15] "ProsperRating..Alpha."
## [16] "ProsperScore"
## [17] "ListingCategory..numeric."
## [18] "BorrowerState"
## [19] "Occupation"
## [20] "EmploymentStatus"
## [21] "EmploymentStatusDuration"
## [22] "IsBorrowerHomeowner"
## [23] "CurrentlyInGroup"
## [24] "GroupKey"
## [25] "DateCreditPulled"
## [26] "CreditScoreRangeLower"
## [27] "CreditScoreRangeUpper"
## [28] "FirstRecordedCreditLine"
## [29] "CurrentCreditLines"
## [30] "OpenCreditLines"
## [31] "TotalCreditLinespast7years"
## [32] "OpenRevolvingAccounts"
## [33] "OpenRevolvingMonthlyPayment"
## [34] "InquiriesLast6Months"
## [35] "TotalInquiries"
## [36] "CurrentDelinquencies"
## [37] "AmountDelinquent"
## [38] "DelinquenciesLast7Years"
## [39] "PublicRecordsLast10Years"
## [40] "PublicRecordsLast12Months"
## [41] "RevolvingCreditBalance"
## [42] "BankcardUtilization"
## [43] "AvailableBankcardCredit"
## [44] "TotalTrades"
## [45] "TradesNeverDelinquent..percentage."
## [46] "TradesOpenedLast6Months"
## [47] "DebtToIncomeRatio"
## [48] "IncomeRange"
## [49] "IncomeVerifiable"
## [50] "StatedMonthlyIncome"
## [51] "LoanKey"
## [52] "TotalProsperLoans"
## [53] "TotalProsperPaymentsBilled"
## [54] "OnTimeProsperPayments"
## [55] "ProsperPaymentsLessThanOneMonthLate"
## [56] "ProsperPaymentsOneMonthPlusLate"
## [57] "ProsperPrincipalBorrowed"
## [58] "ProsperPrincipalOutstanding"
## [59] "ScorexChangeAtTimeOfListing"
## [60] "LoanCurrentDaysDelinquent"
## [61] "LoanFirstDefaultedCycleNumber"
## [62] "LoanMonthsSinceOrigination"
## [63] "LoanNumber"
## [64] "LoanOriginalAmount"
## [65] "LoanOriginationDate"
## [66] "LoanOriginationQuarter"
## [67] "MemberKey"
## [68] "MonthlyLoanPayment"
## [69] "LP_CustomerPayments"
## [70] "LP_CustomerPrincipalPayments"
## [71] "LP_InterestandFees"
## [72] "LP_ServiceFees"
## [73] "LP_CollectionFees"
## [74] "LP_GrossPrincipalLoss"
## [75] "LP_NetPrincipalLoss"
## [76] "LP_NonPrincipalRecoverypayments"
## [77] "PercentFunded"
## [78] "Recommendations"
## [79] "InvestmentFromFriendsCount"
## [80] "InvestmentFromFriendsAmount"
## [81] "Investors"There are 81 variables in the data set.
Top three record from the dataset
## ListingKey ListingNumber ListingCreationDate
## 1 1021339766868145413AB3B 193129 2007-08-26 19:09:29.263000000
## 2 10273602499503308B223C1 1209647 2014-02-27 08:28:07.900000000
## 3 0EE9337825851032864889A 81716 2007-01-05 15:00:47.090000000
## CreditGrade Term LoanStatus ClosedDate BorrowerAPR BorrowerRate
## 1 C 36 Completed 2009-08-14 00:00:00 0.16516 0.158
## 2 36 Current 0.12016 0.092
## 3 HR 36 Completed 2009-12-17 00:00:00 0.28269 0.275
## LenderYield EstimatedEffectiveYield EstimatedLoss EstimatedReturn
## 1 0.138 NA NA NA
## 2 0.082 0.0796 0.0249 0.0547
## 3 0.240 NA NA NA
## ProsperRating..numeric. ProsperRating..Alpha. ProsperScore
## 1 NA NA
## 2 6 A 7
## 3 NA NA
## ListingCategory..numeric. BorrowerState Occupation EmploymentStatus
## 1 0 CO Other Self-employed
## 2 2 CO Professional Employed
## 3 0 GA Other Not available
## EmploymentStatusDuration IsBorrowerHomeowner CurrentlyInGroup
## 1 2 True True
## 2 44 False False
## 3 NA False True
## GroupKey DateCreditPulled
## 1 2007-08-26 18:41:46.780000000
## 2 2014-02-27 08:28:14
## 3 783C3371218786870A73D20 2007-01-02 14:09:10.060000000
## CreditScoreRangeLower CreditScoreRangeUpper FirstRecordedCreditLine
## 1 640 659 2001-10-11 00:00:00
## 2 680 699 1996-03-18 00:00:00
## 3 480 499 2002-07-27 00:00:00
## CurrentCreditLines OpenCreditLines TotalCreditLinespast7years
## 1 5 4 12
## 2 14 14 29
## 3 NA NA 3
## OpenRevolvingAccounts OpenRevolvingMonthlyPayment InquiriesLast6Months
## 1 1 24 3
## 2 13 389 3
## 3 0 0 0
## TotalInquiries CurrentDelinquencies AmountDelinquent
## 1 3 2 472
## 2 5 0 0
## 3 1 1 NA
## DelinquenciesLast7Years PublicRecordsLast10Years
## 1 4 0
## 2 0 1
## 3 0 0
## PublicRecordsLast12Months RevolvingCreditBalance BankcardUtilization
## 1 0 0 0.00
## 2 0 3989 0.21
## 3 NA NA NA
## AvailableBankcardCredit TotalTrades TradesNeverDelinquent..percentage.
## 1 1500 11 0.81
## 2 10266 29 1.00
## 3 NA NA NA
## TradesOpenedLast6Months DebtToIncomeRatio IncomeRange
## 1 0 0.17 $25,000-49,999
## 2 2 0.18 $50,000-74,999
## 3 NA 0.06 Not displayed
## IncomeVerifiable StatedMonthlyIncome LoanKey
## 1 True 3083.333 E33A3400205839220442E84
## 2 True 6125.000 9E3B37071505919926B1D82
## 3 True 2083.333 6954337960046817851BCB2
## TotalProsperLoans TotalProsperPaymentsBilled OnTimeProsperPayments
## 1 NA NA NA
## 2 NA NA NA
## 3 NA NA NA
## ProsperPaymentsLessThanOneMonthLate ProsperPaymentsOneMonthPlusLate
## 1 NA NA
## 2 NA NA
## 3 NA NA
## ProsperPrincipalBorrowed ProsperPrincipalOutstanding
## 1 NA NA
## 2 NA NA
## 3 NA NA
## ScorexChangeAtTimeOfListing LoanCurrentDaysDelinquent
## 1 NA 0
## 2 NA 0
## 3 NA 0
## LoanFirstDefaultedCycleNumber LoanMonthsSinceOrigination LoanNumber
## 1 NA 78 19141
## 2 NA 0 134815
## 3 NA 86 6466
## LoanOriginalAmount LoanOriginationDate LoanOriginationQuarter
## 1 9425 2007-09-12 00:00:00 Q3 2007
## 2 10000 2014-03-03 00:00:00 Q1 2014
## 3 3001 2007-01-17 00:00:00 Q1 2007
## MemberKey MonthlyLoanPayment LP_CustomerPayments
## 1 1F3E3376408759268057EDA 330.43 11396.14
## 2 1D13370546739025387B2F4 318.93 0.00
## 3 5F7033715035555618FA612 123.32 4186.63
## LP_CustomerPrincipalPayments LP_InterestandFees LP_ServiceFees
## 1 9425 1971.14 -133.18
## 2 0 0.00 0.00
## 3 3001 1185.63 -24.20
## LP_CollectionFees LP_GrossPrincipalLoss LP_NetPrincipalLoss
## 1 0 0 0
## 2 0 0 0
## 3 0 0 0
## LP_NonPrincipalRecoverypayments PercentFunded Recommendations
## 1 0 1 0
## 2 0 1 0
## 3 0 1 0
## InvestmentFromFriendsCount InvestmentFromFriendsAmount Investors
## 1 0 0 258
## 2 0 0 1
## 3 0 0 41Summary of the dataset
## ListingKey ListingNumber
## 17A93590655669644DB4C06: 6 Min. : 4
## 349D3587495831350F0F648: 4 1st Qu.: 400919
## 47C1359638497431975670B: 4 Median : 600554
## 8474358854651984137201C: 4 Mean : 627886
## DE8535960513435199406CE: 4 3rd Qu.: 892634
## 04C13599434217079754AEE: 3 Max. :1255725
## (Other) :113912
## ListingCreationDate CreditGrade Term
## 2013-10-02 17:20:16.550000000: 6 :84984 Min. :12.00
## 2013-08-28 20:31:41.107000000: 4 C : 5649 1st Qu.:36.00
## 2013-09-08 09:27:44.853000000: 4 D : 5153 Median :36.00
## 2013-12-06 05:43:13.830000000: 4 B : 4389 Mean :40.83
## 2013-12-06 11:44:58.283000000: 4 AA : 3509 3rd Qu.:36.00
## 2013-08-21 07:25:22.360000000: 3 HR : 3508 Max. :60.00
## (Other) :113912 (Other): 6745
## LoanStatus ClosedDate
## Current :56576 :58848
## Completed :38074 2014-03-04 00:00:00: 105
## Chargedoff :11992 2014-02-19 00:00:00: 100
## Defaulted : 5018 2014-02-11 00:00:00: 92
## Past Due (1-15 days) : 806 2012-10-30 00:00:00: 81
## Past Due (31-60 days): 363 2013-02-26 00:00:00: 78
## (Other) : 1108 (Other) :54633
## BorrowerAPR BorrowerRate LenderYield
## Min. :0.00653 Min. :0.0000 Min. :-0.0100
## 1st Qu.:0.15629 1st Qu.:0.1340 1st Qu.: 0.1242
## Median :0.20976 Median :0.1840 Median : 0.1730
## Mean :0.21883 Mean :0.1928 Mean : 0.1827
## 3rd Qu.:0.28381 3rd Qu.:0.2500 3rd Qu.: 0.2400
## Max. :0.51229 Max. :0.4975 Max. : 0.4925
## NA's :25
## EstimatedEffectiveYield EstimatedLoss EstimatedReturn
## Min. :-0.183 Min. :0.005 Min. :-0.183
## 1st Qu.: 0.116 1st Qu.:0.042 1st Qu.: 0.074
## Median : 0.162 Median :0.072 Median : 0.092
## Mean : 0.169 Mean :0.080 Mean : 0.096
## 3rd Qu.: 0.224 3rd Qu.:0.112 3rd Qu.: 0.117
## Max. : 0.320 Max. :0.366 Max. : 0.284
## NA's :29084 NA's :29084 NA's :29084
## ProsperRating..numeric. ProsperRating..Alpha. ProsperScore
## Min. :1.000 :29084 Min. : 1.00
## 1st Qu.:3.000 C :18345 1st Qu.: 4.00
## Median :4.000 B :15581 Median : 6.00
## Mean :4.072 A :14551 Mean : 5.95
## 3rd Qu.:5.000 D :14274 3rd Qu.: 8.00
## Max. :7.000 E : 9795 Max. :11.00
## NA's :29084 (Other):12307 NA's :29084
## ListingCategory..numeric. BorrowerState
## Min. : 0.000 CA :14717
## 1st Qu.: 1.000 TX : 6842
## Median : 1.000 NY : 6729
## Mean : 2.774 FL : 6720
## 3rd Qu.: 3.000 IL : 5921
## Max. :20.000 : 5515
## (Other):67493
## Occupation EmploymentStatus
## Other :28617 Employed :67322
## Professional :13628 Full-time :26355
## Computer Programmer : 4478 Self-employed: 6134
## Executive : 4311 Not available: 5347
## Teacher : 3759 Other : 3806
## Administrative Assistant: 3688 : 2255
## (Other) :55456 (Other) : 2718
## EmploymentStatusDuration IsBorrowerHomeowner CurrentlyInGroup
## Min. : 0.00 False:56459 False:101218
## 1st Qu.: 26.00 True :57478 True : 12719
## Median : 67.00
## Mean : 96.07
## 3rd Qu.:137.00
## Max. :755.00
## NA's :7625
## GroupKey DateCreditPulled
## :100596 2013-12-23 09:38:12: 6
## 783C3371218786870A73D20: 1140 2013-11-21 09:09:41: 4
## 3D4D3366260257624AB272D: 916 2013-12-06 05:43:16: 4
## 6A3B336601725506917317E: 698 2014-01-14 20:17:49: 4
## FEF83377364176536637E50: 611 2014-02-09 12:14:41: 4
## C9643379247860156A00EC0: 342 2013-09-27 22:04:54: 3
## (Other) : 9634 (Other) :113912
## CreditScoreRangeLower CreditScoreRangeUpper
## Min. : 0.0 Min. : 19.0
## 1st Qu.:660.0 1st Qu.:679.0
## Median :680.0 Median :699.0
## Mean :685.6 Mean :704.6
## 3rd Qu.:720.0 3rd Qu.:739.0
## Max. :880.0 Max. :899.0
## NA's :591 NA's :591
## FirstRecordedCreditLine CurrentCreditLines OpenCreditLines
## : 697 Min. : 0.00 Min. : 0.00
## 1993-12-01 00:00:00: 185 1st Qu.: 7.00 1st Qu.: 6.00
## 1994-11-01 00:00:00: 178 Median :10.00 Median : 9.00
## 1995-11-01 00:00:00: 168 Mean :10.32 Mean : 9.26
## 1990-04-01 00:00:00: 161 3rd Qu.:13.00 3rd Qu.:12.00
## 1995-03-01 00:00:00: 159 Max. :59.00 Max. :54.00
## (Other) :112389 NA's :7604 NA's :7604
## TotalCreditLinespast7years OpenRevolvingAccounts
## Min. : 2.00 Min. : 0.00
## 1st Qu.: 17.00 1st Qu.: 4.00
## Median : 25.00 Median : 6.00
## Mean : 26.75 Mean : 6.97
## 3rd Qu.: 35.00 3rd Qu.: 9.00
## Max. :136.00 Max. :51.00
## NA's :697
## OpenRevolvingMonthlyPayment InquiriesLast6Months TotalInquiries
## Min. : 0.0 Min. : 0.000 Min. : 0.000
## 1st Qu.: 114.0 1st Qu.: 0.000 1st Qu.: 2.000
## Median : 271.0 Median : 1.000 Median : 4.000
## Mean : 398.3 Mean : 1.435 Mean : 5.584
## 3rd Qu.: 525.0 3rd Qu.: 2.000 3rd Qu.: 7.000
## Max. :14985.0 Max. :105.000 Max. :379.000
## NA's :697 NA's :1159
## CurrentDelinquencies AmountDelinquent DelinquenciesLast7Years
## Min. : 0.0000 Min. : 0.0 Min. : 0.000
## 1st Qu.: 0.0000 1st Qu.: 0.0 1st Qu.: 0.000
## Median : 0.0000 Median : 0.0 Median : 0.000
## Mean : 0.5921 Mean : 984.5 Mean : 4.155
## 3rd Qu.: 0.0000 3rd Qu.: 0.0 3rd Qu.: 3.000
## Max. :83.0000 Max. :463881.0 Max. :99.000
## NA's :697 NA's :7622 NA's :990
## PublicRecordsLast10Years PublicRecordsLast12Months RevolvingCreditBalance
## Min. : 0.0000 Min. : 0.000 Min. : 0
## 1st Qu.: 0.0000 1st Qu.: 0.000 1st Qu.: 3121
## Median : 0.0000 Median : 0.000 Median : 8549
## Mean : 0.3126 Mean : 0.015 Mean : 17599
## 3rd Qu.: 0.0000 3rd Qu.: 0.000 3rd Qu.: 19521
## Max. :38.0000 Max. :20.000 Max. :1435667
## NA's :697 NA's :7604 NA's :7604
## BankcardUtilization AvailableBankcardCredit TotalTrades
## Min. :0.000 Min. : 0 Min. : 0.00
## 1st Qu.:0.310 1st Qu.: 880 1st Qu.: 15.00
## Median :0.600 Median : 4100 Median : 22.00
## Mean :0.561 Mean : 11210 Mean : 23.23
## 3rd Qu.:0.840 3rd Qu.: 13180 3rd Qu.: 30.00
## Max. :5.950 Max. :646285 Max. :126.00
## NA's :7604 NA's :7544 NA's :7544
## TradesNeverDelinquent..percentage. TradesOpenedLast6Months
## Min. :0.000 Min. : 0.000
## 1st Qu.:0.820 1st Qu.: 0.000
## Median :0.940 Median : 0.000
## Mean :0.886 Mean : 0.802
## 3rd Qu.:1.000 3rd Qu.: 1.000
## Max. :1.000 Max. :20.000
## NA's :7544 NA's :7544
## DebtToIncomeRatio IncomeRange IncomeVerifiable
## Min. : 0.000 $25,000-49,999:32192 False: 8669
## 1st Qu.: 0.140 $50,000-74,999:31050 True :105268
## Median : 0.220 $100,000+ :17337
## Mean : 0.276 $75,000-99,999:16916
## 3rd Qu.: 0.320 Not displayed : 7741
## Max. :10.010 $1-24,999 : 7274
## NA's :8554 (Other) : 1427
## StatedMonthlyIncome LoanKey TotalProsperLoans
## Min. : 0 CB1B37030986463208432A1: 6 Min. :0.00
## 1st Qu.: 3200 2DEE3698211017519D7333F: 4 1st Qu.:1.00
## Median : 4667 9F4B37043517554537C364C: 4 Median :1.00
## Mean : 5608 D895370150591392337ED6D: 4 Mean :1.42
## 3rd Qu.: 6825 E6FB37073953690388BC56D: 4 3rd Qu.:2.00
## Max. :1750003 0D8F37036734373301ED419: 3 Max. :8.00
## (Other) :113912 NA's :91852
## TotalProsperPaymentsBilled OnTimeProsperPayments
## Min. : 0.00 Min. : 0.00
## 1st Qu.: 9.00 1st Qu.: 9.00
## Median : 16.00 Median : 15.00
## Mean : 22.93 Mean : 22.27
## 3rd Qu.: 33.00 3rd Qu.: 32.00
## Max. :141.00 Max. :141.00
## NA's :91852 NA's :91852
## ProsperPaymentsLessThanOneMonthLate ProsperPaymentsOneMonthPlusLate
## Min. : 0.00 Min. : 0.00
## 1st Qu.: 0.00 1st Qu.: 0.00
## Median : 0.00 Median : 0.00
## Mean : 0.61 Mean : 0.05
## 3rd Qu.: 0.00 3rd Qu.: 0.00
## Max. :42.00 Max. :21.00
## NA's :91852 NA's :91852
## ProsperPrincipalBorrowed ProsperPrincipalOutstanding
## Min. : 0 Min. : 0
## 1st Qu.: 3500 1st Qu.: 0
## Median : 6000 Median : 1627
## Mean : 8472 Mean : 2930
## 3rd Qu.:11000 3rd Qu.: 4127
## Max. :72499 Max. :23451
## NA's :91852 NA's :91852
## ScorexChangeAtTimeOfListing LoanCurrentDaysDelinquent
## Min. :-209.00 Min. : 0.0
## 1st Qu.: -35.00 1st Qu.: 0.0
## Median : -3.00 Median : 0.0
## Mean : -3.22 Mean : 152.8
## 3rd Qu.: 25.00 3rd Qu.: 0.0
## Max. : 286.00 Max. :2704.0
## NA's :95009
## LoanFirstDefaultedCycleNumber LoanMonthsSinceOrigination LoanNumber
## Min. : 0.00 Min. : 0.0 Min. : 1
## 1st Qu.: 9.00 1st Qu.: 6.0 1st Qu.: 37332
## Median :14.00 Median : 21.0 Median : 68599
## Mean :16.27 Mean : 31.9 Mean : 69444
## 3rd Qu.:22.00 3rd Qu.: 65.0 3rd Qu.:101901
## Max. :44.00 Max. :100.0 Max. :136486
## NA's :96985
## LoanOriginalAmount LoanOriginationDate LoanOriginationQuarter
## Min. : 1000 2014-01-22 00:00:00: 491 Q4 2013:14450
## 1st Qu.: 4000 2013-11-13 00:00:00: 490 Q1 2014:12172
## Median : 6500 2014-02-19 00:00:00: 439 Q3 2013: 9180
## Mean : 8337 2013-10-16 00:00:00: 434 Q2 2013: 7099
## 3rd Qu.:12000 2014-01-28 00:00:00: 339 Q3 2012: 5632
## Max. :35000 2013-09-24 00:00:00: 316 Q2 2012: 5061
## (Other) :111428 (Other):60343
## MemberKey MonthlyLoanPayment LP_CustomerPayments
## 63CA34120866140639431C9: 9 Min. : 0.0 Min. : -2.35
## 16083364744933457E57FB9: 8 1st Qu.: 131.6 1st Qu.: 1005.76
## 3A2F3380477699707C81385: 8 Median : 217.7 Median : 2583.83
## 4D9C3403302047712AD0CDD: 8 Mean : 272.5 Mean : 4183.08
## 739C338135235294782AE75: 8 3rd Qu.: 371.6 3rd Qu.: 5548.40
## 7E1733653050264822FAA3D: 8 Max. :2251.5 Max. :40702.39
## (Other) :113888
## LP_CustomerPrincipalPayments LP_InterestandFees LP_ServiceFees
## Min. : 0.0 Min. : -2.35 Min. :-664.87
## 1st Qu.: 500.9 1st Qu.: 274.87 1st Qu.: -73.18
## Median : 1587.5 Median : 700.84 Median : -34.44
## Mean : 3105.5 Mean : 1077.54 Mean : -54.73
## 3rd Qu.: 4000.0 3rd Qu.: 1458.54 3rd Qu.: -13.92
## Max. :35000.0 Max. :15617.03 Max. : 32.06
##
## LP_CollectionFees LP_GrossPrincipalLoss LP_NetPrincipalLoss
## Min. :-9274.75 Min. : -94.2 Min. : -954.5
## 1st Qu.: 0.00 1st Qu.: 0.0 1st Qu.: 0.0
## Median : 0.00 Median : 0.0 Median : 0.0
## Mean : -14.24 Mean : 700.4 Mean : 681.4
## 3rd Qu.: 0.00 3rd Qu.: 0.0 3rd Qu.: 0.0
## Max. : 0.00 Max. :25000.0 Max. :25000.0
##
## LP_NonPrincipalRecoverypayments PercentFunded Recommendations
## Min. : 0.00 Min. :0.7000 Min. : 0.00000
## 1st Qu.: 0.00 1st Qu.:1.0000 1st Qu.: 0.00000
## Median : 0.00 Median :1.0000 Median : 0.00000
## Mean : 25.14 Mean :0.9986 Mean : 0.04803
## 3rd Qu.: 0.00 3rd Qu.:1.0000 3rd Qu.: 0.00000
## Max. :21117.90 Max. :1.0125 Max. :39.00000
##
## InvestmentFromFriendsCount InvestmentFromFriendsAmount Investors
## Min. : 0.00000 Min. : 0.00 Min. : 1.00
## 1st Qu.: 0.00000 1st Qu.: 0.00 1st Qu.: 2.00
## Median : 0.00000 Median : 0.00 Median : 44.00
## Mean : 0.02346 Mean : 16.55 Mean : 80.48
## 3rd Qu.: 0.00000 3rd Qu.: 0.00 3rd Qu.: 115.00
## Max. :33.00000 Max. :25000.00 Max. :1189.00
## Dimension of the dataset
## [1] 113937 81There are 81 columns (variables) and 113,937 rows (loan takers) in Prosper Loan Data.
Install and Load Necessary Libraries
Cleaning Data
Convert CreditScoreRangeLower and CreditScoreRangeUpper into a single CreditScore value (calculate average of the two variables).
Convert ListingCategory from numeric to factor variable using the keys given in the Google Spreadsheet.
## Debt Consolidation Home Improvement
## 58308 7433
## Business Personal\n Loan
## 7189 2395
## Student Use Auto
## 756 2572
## Baby & Adoption Boat
## 199 85
## Cosmetic\n Procedure Engagement Ring
## 91 217
## Green Loan Household Expenses
## 59 1996
## Large\n Purchases Medical/Dental
## 876 1522
## Motorcycle RV
## 304 52
## Taxes Vacation
## 885 768
## Wedding Other
## 771 10494
## Not Applicable
## 16965Convert dates to date class using lubridate’s ymd_hms() function
Convert LoanOriginationQuarter to begin with the year using tidyr to make sure that any plot axis will put it in increasing order of year
CreditGrade was used to store credit rating pre-2009 while ProsperRating..Alpha. was used to store credit rating post-2009. I combined the two variables into one. They are not exactly the same thing but pretty close to make meaningful sense and make data plots easier.
Let’s look at the structure of newly created CreditRating
## Ord.factor w/ 7 levels "AA"<"A"<"B"<"C"<..: 4 1 7 1 5 3 6 4 2 2 ...Format Date Columns As.Date
Split date variables by day, month and year to enable easy analysis of dates
Merge the Split Dates with Prosper Loan Data
View New Prosper Loan Data
Modified Dataset
New Columns
## [1] "ListingKey"
## [2] "ListingNumber"
## [3] "ListingCreationDate"
## [4] "CreditGrade"
## [5] "Term"
## [6] "LoanStatus"
## [7] "ClosedDate"
## [8] "BorrowerAPR"
## [9] "BorrowerRate"
## [10] "LenderYield"
## [11] "EstimatedEffectiveYield"
## [12] "EstimatedLoss"
## [13] "EstimatedReturn"
## [14] "ProsperRating..numeric."
## [15] "ProsperRating..Alpha."
## [16] "ProsperScore"
## [17] "ListingCategory..numeric."
## [18] "BorrowerState"
## [19] "Occupation"
## [20] "EmploymentStatus"
## [21] "EmploymentStatusDuration"
## [22] "IsBorrowerHomeowner"
## [23] "CurrentlyInGroup"
## [24] "GroupKey"
## [25] "DateCreditPulled"
## [26] "CreditScoreRangeLower"
## [27] "CreditScoreRangeUpper"
## [28] "FirstRecordedCreditLine"
## [29] "CurrentCreditLines"
## [30] "OpenCreditLines"
## [31] "TotalCreditLinespast7years"
## [32] "OpenRevolvingAccounts"
## [33] "OpenRevolvingMonthlyPayment"
## [34] "InquiriesLast6Months"
## [35] "TotalInquiries"
## [36] "CurrentDelinquencies"
## [37] "AmountDelinquent"
## [38] "DelinquenciesLast7Years"
## [39] "PublicRecordsLast10Years"
## [40] "PublicRecordsLast12Months"
## [41] "RevolvingCreditBalance"
## [42] "BankcardUtilization"
## [43] "AvailableBankcardCredit"
## [44] "TotalTrades"
## [45] "TradesNeverDelinquent..percentage."
## [46] "TradesOpenedLast6Months"
## [47] "DebtToIncomeRatio"
## [48] "IncomeRange"
## [49] "IncomeVerifiable"
## [50] "StatedMonthlyIncome"
## [51] "LoanKey"
## [52] "TotalProsperLoans"
## [53] "TotalProsperPaymentsBilled"
## [54] "OnTimeProsperPayments"
## [55] "ProsperPaymentsLessThanOneMonthLate"
## [56] "ProsperPaymentsOneMonthPlusLate"
## [57] "ProsperPrincipalBorrowed"
## [58] "ProsperPrincipalOutstanding"
## [59] "ScorexChangeAtTimeOfListing"
## [60] "LoanCurrentDaysDelinquent"
## [61] "LoanFirstDefaultedCycleNumber"
## [62] "LoanMonthsSinceOrigination"
## [63] "LoanNumber"
## [64] "LoanOriginalAmount"
## [65] "LoanOriginationDate"
## [66] "LoanOriginationQuarter"
## [67] "MemberKey"
## [68] "MonthlyLoanPayment"
## [69] "LP_CustomerPayments"
## [70] "LP_CustomerPrincipalPayments"
## [71] "LP_InterestandFees"
## [72] "LP_ServiceFees"
## [73] "LP_CollectionFees"
## [74] "LP_GrossPrincipalLoss"
## [75] "LP_NetPrincipalLoss"
## [76] "LP_NonPrincipalRecoverypayments"
## [77] "PercentFunded"
## [78] "Recommendations"
## [79] "InvestmentFromFriendsCount"
## [80] "InvestmentFromFriendsAmount"
## [81] "Investors"
## [82] "CreditScore"
## [83] "ListingCategory"
## [84] "LoanOriginationQuarterF"
## [85] "CreditRating"
## [86] "ListingYear"
## [87] "ListingMonth"
## [88] "ListingDay"
## [89] "OriginationYear"
## [90] "OriginationMonth"
## [91] "OriginationDay"
## [92] "ClosedYear"
## [93] "ClosedMonth"
## [94] "ClosedDay"Dimension of new dataset
## [1] 113937 94Prosper Loan Data now has 94 variables comprising of the original 81 variables and 13 newly created/modified variables
Univariate Plots
Let’s plot some of the variables and see what information they have.
The first variable I will like to look at is LoanOriginalAmount
Bulk of the loans given were below 15,000. Also, most loans were in multiples of $5,000 as seen in number of loans at $5,000, $10,000, $15,000, $20,000, $25,000, $30,000 and $35,000 points. It could also support the fact that loans were not granted based on values of underlying assets but mostly to refinance existing debts. We will see more as I plot reasons why loans were taken.
Plot of ListingYear
Most loans in the dataset were booked in 2013 followed by 2012. The lowest number of loans were booked in 2009.Let’s look at the percentage distribution.
## Percentage Distribution of Listing Year
## 2005 2006 2007 2008 2009
## 0.0002018659 0.0545301351 0.1014332482 0.0988528748 0.0193615770
## 2010 2011 2012 2013 2014
## 0.0485355942 0.1004239185 0.1716387126 0.3108121155 0.094209958131% of all loans were listed in 2013. There was a big dip in 2009 before loans started picking up from 2010 which peaked in 2013
Plot of ListingCreationMonth
Loans listed in January are more than in other months. Listings were lowest in March and April and rose steadily through December.
Plot of ListingCreationDate
Listing were lowest on 31st day of the month.
Plot of Loan Origination Year
More loans were originated in 2013 than any other year. Let’s take a look at the percentage distribution.
## Percentage Distribution of Origination Year
## 2005 2006 2007 2008 2009
## 0.0001930892 0.0518356636 0.1005819005 0.1013893643 0.0179660690
## 2010 2011 2012 2013 2014
## 0.0496063614 0.0985456875 0.1716123823 0.3014385143 0.106830968030% of all loans were originated in 2013 followed by 17% in 2012. Only about 1.8% originated in 2009. It will be interesting to look at what happened to Prosper Loan in 2009.
Plot of Loan Origination Month
Loans originated in January were more than in other months with a dip in March and April.
More loans were also originated on the 30th of the month. This could be due to employees attempt to meet performance requirement for the month.
Plot of Loan Closed Year
It makes sense that more loans would be closed in 2013 than any other years following the fact that more loans were originated in 2013 as well.
Plot of Loan Closed Month
More loans were closed on the 2nd of the month than other days.
Plot of Loans Closed Day
More loans closed on the 30th of the month also.
Let take a step further and view Listing Year, Origination Year and Closed Year together
Plots and Grid Arrangement of Origination, Listing and Closed Year
Most loans in the data were listed, originated and were closed in 2013 than any other years.
Plot of Borrowers Occupation
Below is the visualize of borrowers’ occupation:
‘Other’ and ‘Professional’ stood out in the occupation chart. This shows that many borrowers decided to choose “other” and “professional” instead of their real occupation.
Plot of Borrowers States
California has the largest number of borrowers. This could be because Prosper Loan was founded and local to CA and being the state with one of the highest state debt per capital. The other popular states include Florida, New York, Texas and Illinois.
Next let’s look at some financial information:
Plot of Borrowers IncomeRange
This plot approximate Normal distribution with borrowers with zero income and not employed constituting the lowest number of borrowers as expected. I do not think loans were given to $0 income earner or employed. This could be borrowers that lost their jobs after getting the loans or have loans secured by other assets.
Plot of CreditScore
Median credit score was 700
Plot of ProsperRating…Alpha
This grid shows ‘CreditGrade’ which is pre-2009 rating, and ‘ProsperRating’ which post-2009 rating side by side. One thing that stood out is that both plots is that there are less borrowers in the both ends of the credit rating. This is because most people with super good credit are financially stable and do not usually take loans while people at the tail-end of the credit rating don’t always get approved for credits. To me, that makes sense.
Plot of Borrowers APR
The bulk of the loans seem to be near the 0.2 mark, which coincides with the credit rating histograms that show that majority of the users are in the middle of the risk ratings. There is a strange spike in the 0.35-0.37 bin which indicates a strangely popular fee rate for primarily higher risk borrowers.
Plot of Lender Yield
The lender yield plot is similar to borrower APR because they’re two sides of the same coin. I do notice, however, that the peak count is slightly lower than the one in the borrower APR plot, and I presume it is because of the losses that are made when borrowers default loans or get charged off on late payments.
Plot of DebtToIncomeRatio
## Min. 1st Qu. Median Mean 3rd Qu. Max. NA's
## 0.000 0.140 0.220 0.276 0.320 10.010 8554Most of the borrowers have a debt-to-income ratio below 0.8 with the median being 0.22
Most of the borrowers have 0 current delinquencies which is a good thing.
Plot of LoanStatus
Most loans seem to still be ongoing, which is indicative of their booming growth.
Debt Consolidation seems by and far the most popular choice, with the rest of the non-ambiguous (or ’Not Applicable) occupation much below the 10,000 mark.
Time Series Plots
I’m going to do some Time Series plots to see the performance of loans since it launched and show any interesting trends in Prosper’s loans business.
Let’s take a look at the summary of the ‘LoanStatus’ variable to see what the grouping/coloring will look like:
## Cancelled Chargedoff Completed
## 5 11992 38074
## Current Defaulted FinalPaymentInProgress
## 56576 5018 205
## Past Due (>120 days) Past Due (1-15 days) Past Due (16-30 days)
## 16 806 265
## Past Due (31-60 days) Past Due (61-90 days) Past Due (91-120 days)
## 363 313 304Plot of LoanOriginationQuarter
This plot provides us with information on the growth of the company through it’s increasing loan openings. We can also see the performance of loans over time.
This plot shows the same time series data from the plot above, but with a line instead of a stacked bar chart.
Bivariate Plots
Plot of CreditScore vs ProsperRating..Alpha
The boxplots above show the relationship between borrower’s Prosper rating (note - this is only post-2009 data) and their credit score, and the variation in each rating category. A person’s credit score is one of the key factors in determining their Prosper Rating, so it’s no surprise that as we climb the rating categories, the credit score of the borrowers also tend to increase. ‘HR’ has a slightly higher median and IQR than ‘E’ despite being a riskier category - in fact, it’s on par with borrowers with a ‘D’ rating.
Plot of BorrowerAPR vs ProsperRating…Alpha
The boxplots above show the relationship between borrower’s Prosper rating and their assigned Annual Percentage Rate (APR). It’s very clear that as we go down the ladder of risk - from a ‘High Risk’ to an ‘AA’ rating - the APR for the borrower reduces drastically. In fact, looking at the results of a by() function, it goes from a median APR of 35.8% for High Risk all the way to a median value of 9% for ‘AA’.
The variation in APRs also decreases as the loans get less riskier as displayed by the decreasing size of the boxes in the boxplots when going from ‘HR’ to ‘AA’. There is also a reduction in the number of outliers, which is visible by the shortening lines of yellow rings.
Plot of Quarter vs LoanStatusGroup
The line graph above shows the number of loans that were defaulted over time. This is important for Prosper because they can see how frequently bad loans are made, and more importantly, to judge whether any policies - like the minimum credit score - are improving the likelihood of payment.
The 2 times the line veers below the 200 mark are misleading. The first is because of the ‘quiet’ period mentioned before, and therefore expected. The second one, however, in 2013, is because most of the loans in that period are with the ‘Current’ or ‘FinalPaymentInProgress’ status, and there just hasn’t been enough time to know whether loans are ‘Completed’ or ‘Defaulted’. Over time, that line should go higher.
In fact, a better way to show defaulted loans would be to show the rate at which loans are being defaulted. Let’s do that next:
This looks more systematic. I can see that between 2006 and 2008, the default rate hovered between 30%-40% - a pretty high rate. Once again, we see that drop, but it does not go to zero this time, and we can now see that during that period (which also happens to be after the financial crisis) there were borrowers unable to pay back their loans.
Plot of DelinquenciesLast7Years vs AmountDelinquent
The over plotting and general dispersion of data doesn’t really reveal much trend in this plot.
Multivariate Plots
Plot of DebtToIncomeRatio vs BorrowerAPR
This is a great plot with a lot of information. Here we have a scatter plot of borrower’s APR and the debt to income ratio of the borrower, with the colors describing the risk category given to the particular loan. I’ve given the legend a continuous color scale despite it being discrete variables because it displays the progression from a safe green to a risky red. I’ve also decided to include all points in the y-axis (including outliers) to show the range of rates, and I’ve limited the x-axis by removing 0.05% of the points furthest away from the median (i.e. removing outliers that spread the graph).
The first thing I noticed and found interesting was that ‘A’ category loans seem to have a lower APRs and a smaller range of debt-to-income ratios, both of which indicate less risk. The rest of the plot follow the color palette and APR increases as the rating gets riskier. Another thing is that most people tend to have debt-to-income ratios below 1, regardless of risk category. Also, there is this unusual horizontal line in the ‘HR’ category that extends past 1 and all the way to 1.5, while lower ratings tend to be sparse in the 1.0+ debt-to-income ratio range.
Plot of LoanOriginalAmount vs LenderYield
This plot shows the relationship between a lender yield on the loans and the amount that a borrower has loaned. I then made individual graphs to show that relationship based on the status of the loan - Defaulted, Past Due, Current and Completed - and finally colored it based on risk rating.
Plot of CurrentDelinquencies vs BorrowerAPR
This plot was made to see if there were any distinct differences in terms of completing and defaulting loans when it came to current delinquencies. Unfortunately, there doesn’t seem to be any tell-tale signs and both plots look pretty similar. However, I do notice that higher rated loans seem less diverse in terms of delinquencies and APR, and customarily lumped in the bottom left corner. As the loans gets riskier, the points get more varied and diverse, and tend to be all over the graph.
Final Plots
Plot One: Quarter vs LoanStatusGroup
I have chosen this plot because of its combination of detail and simplicity. It makes for an easy way to evaluate the performance of Prosper loans. I’m going to compare it as pre-2009 and post-2009, because 2009 was when they went into a ‘quiet’ period and changed their business model and also mandated a minimum credit score of 640. This plot is one way of visually seeing whether their changes have resulted in a more Prosperous lending platform.
First let’s look at pre-2009. They were still a young company at the time, and we can see that with the sub-5000 loans per quarter figure. More importantly, though, all the loans originated at the time are either completed or defaulted (i.e. none are still ongoing). Now I can compare the relative sizes of the red and green bars, and I can easily tell that approximately half, or a bit less than half the loans that were granted, defaulted.
That’s not good, especially when they have to convince investors that they’re making solid investments. Now let’s look at post-2009. Right when they restarted servicing loans, for about the next year, we can see that the size of the red bar is much smaller relative to the green bar. That tells me that their minimum credit policy seems like it’s working - defaults look pretty low in number.
I chose to look at only the next year because there seem to be no, or an insignificant amount of loans still currently active. After that - 2011 onwards - we see the number of loans being originated rise tremendously. The red bar to green bar ratio seems to be increasing slowly, but it’s difficult to tell with the growing ‘Current’ blue bar in between. But a few questions arise - how many of those current loans will end up in the green, completed group in the future? How many will instead dive into the yellow of ‘Past Due’? And out of those, how many will make it out and enter green, and how many will fall into the dreadful red of ‘Defaulted’?
It’s difficult to say whether their new policies have improved investment quality - the first year certainly suggests so, but scaling up quickly invariably leads to some new problems. Only time can tell what color the blues in the plot will convert to.
Plot Two: Quarter vs LoanStatusGroup
I’ve chosen this plot because it’s clear-cut and delivers its message precisely. The graph shows the default rate (in percentage) of loans over the years. In a way, it continues from the Plot One above, accurately showing the default rates instead of approximating from a colored bar. And I can validate some of the estimations I made earlier.
Pre-2009, we can see that the rate generally hung around the 30-40% mark, which is considerably high and a definite area for improvement. 2008 Quarter 4 was when Prosper stopped making new loans, which lasted until 2009 Quarter 3. That might be the reason for the steep drop during that period. However, the interesting thing is that they continued performing at that low default rate for the entirety of 2010, when they restarted their service with new policies.
During 2011 it went back up to around 30% and stayed in that region up until 2012. It is important to point out that 2011 onwards, there are still loans that are still currently running, and we cannot make conclusions based on the data. Especially 2013 onwards, where most of the loans are still ongoing, and very few loans are either completed, defaulted, or past due.
Hence, that downward spike occurring around the end of 2012 until 2014 is quite misleading. However, we can say that default rates for complete data (pre-2011) has improved, as they are no longer touching 40%. The hovering around 30% is still quite unfavorable, though, and I’m sure Prosper would like to see that number drop over the coming years.
Plot Three: LoanOriginalAmount vs LenderYield vs CreditRating
This plot was chosen to answer some questions on Prosper Loans. It shows that defaulted category doesn’t have loans $25,000 and below. There are not many loans above $25,000. In the Current category, however, I see much more loans being taken past the $25,000 mark and even past the $30,000 mark and veering towards the maximum of $35k.
The Current category shows a neat ordered rows of colors. It was noted that ‘A’ rating has lower yields. This is understandable as borrowers with good credit rating will have lower APR which return lower yields. Could this be one of the reasons why lenders love to book subprime credits? That a $1m question. Also, borrowers with a riskier rating got approved for lower loan amounts, which makes sense considering the fact that they may be under tremendous financial pressure.
Reflection
This was somehow challenging but a good way to have a firm grasp on doing exploratory data analysis with R. much more difficult than I thought it would be, but in the end, it was incredibly rewarding. Before this project, I have done some EDA work on “marriage age”, death by gun violence, etc. but with this project I was able to touch many knowledge areas of EDA.
Prosper is a peer-to-peer lending with main business rival being Lending Club. Prior to this project work, I have not heard about Prosper. I explored Prosper data through the eyes of one of the three main stakeholders: borrowers, investors, and the company itself.
Over plotting was one of the challenges encountered for which coloring was used to address.
This project made me to appreciate wonderful visualizations and a good way to understand the underlining information in a dataset. Th experience gained with this dataset definitely improved my EDA skills.
There are a number of different ways to take this project further. Firstly, I’ve focused on a small subset of the variables available in the dataset, and there is a vast amount of data I’ve chosen not to explore. I think I’d like to explore the investors side a bit more; look at investor profit and losses and their general activity in the peer-to-peer lending industry. Also, I would like to learn about the kind of plots and graphs specifically used by the finance industry, so that I can incorporate that knowledge into any future datasets I may explore. I wish to apply lessons learned in the rest of this program and projects participation.
Resources used:
- https://tinyurl.com/y9zssy6t
- (R-Tutorial)[http://www.r-tutor.com/r-introduction]
- (Quick-R)[http://www.statmethods.net/stats/withby.html]
- (R-bloggers)[https://www.r-bloggers.com/]
- Prosper Loan website: https://www.prosper.com/plp/about/