P2pLoans - Revision history

Tim: /* Conclusions: */

2013-02-18T03:51:02Z

Conclusions:

← Older revision		Revision as of 23:51, 17 February 2013
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	====Conclusions:====		====Conclusions:====
	Who knows what FICO puts in its credit-worthiness formula? One could guess that many of the items that correlate with interest rate for the same FICO score are actually attributes that are part of FICO's secret formula. In that case are not really elements if of a multiple regression linear model but are just part of FICO anyway. Inquiries.in.the.Last.6.Months, Revolving.Credit.Balance and Home.Ownership fall into that category and their affect is likely encapsulated in the FICO score.		:Who knows what FICO puts in its credit-worthiness formula? One could guess that many of the items that correlate with interest rate for the same FICO score are actually attributes that are part of FICO's secret formula. In that case are not really elements if of a multiple regression linear model but are just part of FICO anyway. Inquiries.in.the.Last.6.Months, Revolving.Credit.Balance and Home.Ownership fall into that category and their affect is likely encapsulated in the FICO score.

	FICO doesn't know what you are going to do once you have your score. So here interest rate is correlated with things having nothing to with interest rate. Amount.Funded.By.Investors, Amount.Requested Loan.Length and Loan.Purpose have correlations to interest rate that are INDEPENDENT of FICO score and so they are more interesting and informative.		:FICO doesn't know what you are going to do once you have your score. So here interest rate is correlated with things having nothing to with interest rate. Amount.Funded.By.Investors, Amount.Requested Loan.Length and Loan.Purpose have correlations to interest rate that are INDEPENDENT of FICO score and so they are more interesting and informative.

	====References====		====References====

Tim at 03:50, 18 February 2013

2013-02-18T03:50:16Z

← Older revision		Revision as of 23:50, 17 February 2013
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	==Title: Lending Club Loan Interest: Factors Contributing Beyond FICO Score==		==Title: Lending Club Loan Interest: Factors Contributing Beyond Those Related to FICO Score==

	====Introduction:====		====Introduction:====

Tim: /* Statistical Modeling */

2013-02-18T03:49:01Z

Statistical Modeling

← Older revision		Revision as of 23:49, 17 February 2013
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	=====''Statistical Modeling''=====		=====''Statistical Modeling''=====
	:Once candidate characteristics of the data that had strong correlation to interest rate were identified, multiple regression was carried out using the 'R', 'lm' command. The 'lm' command used a formula of the type:		:Once candidate characteristics of the data that had strong correlation to interest rate were identified, multiple regression <cite>multiple</cite> was carried out using the 'R', 'lm' command. The 'lm' command used a formula of the type:
	<i><center>lm(LoansData$Interest.Rate ~ LoansData$FICO.Score + LoansData$Other.Loan.Attribute)</center></i>		<i><center>lm(LoansData$Interest.Rate ~ LoansData$FICO.Score + LoansData$Other.Loan.Attribute)</center></i>
	:which represents a weighted linear regression model of the type:		:which represents a weighted linear regression model of the type:

Tim at 03:48, 18 February 2013

2013-02-18T03:48:08Z

← Older revision		Revision as of 23:48, 17 February 2013
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	=====''Reproducibility''=====		=====''Reproducibility''=====
	All analyses performed were run from an R markdown file p2pLoan.Rmd using the full data set		:All analyses performed were run from an R markdown file p2pLoan.Rmd using the full data set

	====Results:====		====Results:====
			:FICO Score has a strong negative correlation to Interest Rate with P<.001. Aside from FICO, the clearest correlation found in the data was the positive correlation between Amount.Funded.By.Investors or Amount.Requested and Interest.Rate for borrowers with the same FICO score with a P<.001. This is strange because you would assume that the more you qualify to borrow, the lower your interest rate. From the data, this does not seem to be the case.

			:Other significant correlations for numeric attributes is the positive correlation between Inquiries.in.the.Last.6.Months and Interest.Rate for people with the same FICO.Score with a P<.001, the positive correlation between Open.Credit.Lines and Interest.Rate for people with the same FICO.Score with a P<.001 and the positive correlation between Revolving.Credit.Balance and Interest.Rate for people with the same FICO.Score with a P<.001.

			:For qualitative attributes, the most striking correlation is that 36 month loans most always have a lower interest rate than 60 month loans with a p<.001 for people with similar FICO scores. People with similar FICO scores who have mortgages generally have a lower rate than those who rent (P=.01) and there is a barely significant correlation for rates for car loans and house and small-business loans rates. (p~.05, p~.03).

	====Conclusions:====		====Conclusions:====
			Who knows what FICO puts in its credit-worthiness formula? One could guess that many of the items that correlate with interest rate for the same FICO score are actually attributes that are part of FICO's secret formula. In that case are not really elements if of a multiple regression linear model but are just part of FICO anyway. Inquiries.in.the.Last.6.Months, Revolving.Credit.Balance and Home.Ownership fall into that category and their affect is likely encapsulated in the FICO score.

			FICO doesn't know what you are going to do once you have your score. So here interest rate is correlated with things having nothing to with interest rate. Amount.Funded.By.Investors, Amount.Requested Loan.Length and Loan.Purpose have correlations to interest rate that are INDEPENDENT of FICO score and so they are more interesting and informative.

	====References====		====References====

Tim at 02:59, 18 February 2013

2013-02-18T02:59:25Z

← Older revision		Revision as of 22:59, 17 February 2013
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	=====''Reproducibility''=====		=====''Reproducibility''=====
			All analyses performed were run from an R markdown file p2pLoan.Rmd using the full data set

	====Results:====		====Results:====

Tim: /* Statistical Modeling */

2013-02-18T02:55:57Z

Statistical Modeling

← Older revision		Revision as of 22:55, 17 February 2013
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	:: <math>I_i</math> is the Interest Rate for the <math>i</math>th sample borrower		:: <math>I_i</math> is the Interest Rate for the <math>i</math>th sample borrower
	:: <math>b_0</math> is the base Interest.Rate for all borrowers with the same FICO score		:: <math>b_0</math> is the base Interest.Rate for all borrowers with the same FICO score
	:: <math>~~b_1</math> is the base weight of the FICO score for the <math>i</math>th sample borrower~~		:: <math>b_j</math> is the weight of <math>A_j</math>th attribute contributing to Interest Rate
	~~:: <math>b_1~~</math> is the weight of <math>A_j</math>th attribute contributing to Interest Rate
	:: <math>A_j</math> is one of the attributes (besides Interest.Rate and FICO.score)		:: <math>A_j</math> is one of the attributes (besides Interest.Rate and FICO.score)
	:: <math>e_i</math> is everything else not accounted for in the model		:: <math>e_i</math> is everything else not accounted for in the model

Tim: /* Statistical Modeling */

2013-02-18T02:54:48Z

Statistical Modeling

← Older revision		Revision as of 22:54, 17 February 2013
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	<i><center>lm(LoansData$Interest.Rate ~ LoansData$FICO.Score + LoansData$Other.Loan.Attribute)</center></i>		<i><center>lm(LoansData$Interest.Rate ~ LoansData$FICO.Score + LoansData$Other.Loan.Attribute)</center></i>
	:which represents a weighted linear regression model of the type:		:which represents a weighted linear regression model of the type:
	<center><math>I_i = b_0 + sum{b_j*A_j} +e_i</math></center>		<center><math>I_i = b_0 + \sum{b_j*A_j} +e_i</math></center>
	:where		:where
	:: <math>I_i</math> is the Interest Rate for the <math>i</math>th sample borrower		:: <math>I_i</math> is the Interest Rate for the <math>i</math>th sample borrower

Tim: /* Statistical Modeling */

2013-02-18T02:53:03Z

Statistical Modeling

← Older revision		Revision as of 22:53, 17 February 2013
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	<i><center>lm(LoansData$Interest.Rate ~ LoansData$FICO.Score + LoansData$Other.Loan.Attribute)</center></i>		<i><center>lm(LoansData$Interest.Rate ~ LoansData$FICO.Score + LoansData$Other.Loan.Attribute)</center></i>
	:which represents a weighted linear regression model of the type:		:which represents a weighted linear regression model of the type:
	<center><math>I_i = b_0 + ~~+ b_1A_0 + b_2~~A_j +e_i</math></center>		<center><math>I_i = b_0 + sum{b_j*A_j} +e_i</math></center>
	:where		:where
	:: <math>I_i</math> is the Interest Rate for the <math>i</math>th sample borrower		:: <math>I_i</math> is the Interest Rate for the <math>i</math>th sample borrower
	:: <math>b_0</math> is the base weight of the FICO score for the <math>i</math>th sample borrower		:: <math>b_0</math> is the base Interest.Rate for all borrowers with the same FICO score
			:: <math>b_1</math> is the base weight of the FICO score for the <math>i</math>th sample borrower
	:: <math>b_1</math> is the weight of <math>A_j</math>th attribute contributing to Interest Rate		:: <math>b_1</math> is the weight of <math>A_j</math>th attribute contributing to Interest Rate
	:: <math>A_j</math> is one of the attributes (besides Interest.Rate and FICO.score)		:: <math>A_j</math> is one of the attributes (besides Interest.Rate and FICO.score)

Tim: /* Statistical Modeling */

2013-02-18T02:48:55Z

Statistical Modeling

← Older revision		Revision as of 22:48, 17 February 2013
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	<i><center>lm(LoansData$Interest.Rate ~ LoansData$FICO.Score + LoansData$Other.Loan.Attribute)</center></i>		<i><center>lm(LoansData$Interest.Rate ~ LoansData$FICO.Score + LoansData$Other.Loan.Attribute)</center></i>
	:which represents a weighted linear regression model of the type:		:which represents a weighted linear regression model of the type:
	<center><math>I_i = b_0 + + b_1~~O_0~~ + b_2~~O_j~~ +e_i</math></center>		<center><math>I_i = b_0 + + b_1A_0 + b_2A_j +e_i</math></center>
	:where		:where
	:: <math>I_i</math> is the Interest Rate for the <math>i</math>th sample borrower		:: <math>I_i</math> is the Interest Rate for the <math>i</math>th sample borrower
	:: <math>b_0</math> is the base weight of the FICO score for the <math>i</math>th sample borrower		:: <math>b_0</math> is the base weight of the FICO score for the <math>i</math>th sample borrower
	:: <math>b_1</math> is the weight of <math>~~O_j~~</math>th attribute contributing to Interest Rate		:: <math>b_1</math> is the weight of <math>A_j</math>th attribute contributing to Interest Rate
	:: <math>~~O_j~~</math> is one of the attributes (besides Interest.Rate and FICO.score)		:: <math>A_j</math> is one of the attributes (besides Interest.Rate and FICO.score)
	:: <math>e_i</math> is everything else not accounted for in the model		:: <math>e_i</math> is everything else not accounted for in the model

Tim at 02:47, 18 February 2013

2013-02-18T02:47:59Z

← Older revision		Revision as of 22:47, 17 February 2013
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	<i><center>lm(LoansData$Interest.Rate ~ LoansData$FICO.Score + LoansData$Other.Loan.Attribute)</center></i>		<i><center>lm(LoansData$Interest.Rate ~ LoansData$FICO.Score + LoansData$Other.Loan.Attribute)</center></i>
	:which represents a weighted linear regression model of the type:		:which represents a weighted linear regression model of the type:
	<center><math>I_i = b_0 + b_1*O_j +e_i</math></center>		<center><math>I_i = b_0 + + b_1O_0 + b_2O_j +e_i</math></center>
	:where		:where
	:: <math>I_i</math> is the Interest Rate for the <math>i</math>th sample borrower		:: <math>I_i</math> is the Interest Rate for the <math>i</math>th sample borrower