commercial vehicles. contents commercial vehicles – an overview objective of the analysis ...

Commercial Vehicles

Contents

Commercial Vehicles – An Overview

Objective of the Analysis

Preliminary Analysis of CV Pools – All Originators

Preliminary Analysis of CV Pools – Only AU Financiers Ltd.

Detailed Analysis of CV Pools – All Originators

Market Outlook

Conclusion

Commercial Vehicles – An Overview

Commercial Vehicles

What is a Commercial Vehicle (CV)?

A Commercial vehicle is a type of motor vehicle that may be used for transporting goods or passenger.

Importance on CV Industry in India

Trucks can access remote and hilly areas where rail lines cannot be constructed.

The CV industry enables quick, easy departure of goods and accepts smaller loads than railways.

The industry has captured short-haul goods transport and a major chunk of long-haul goods transport where quick delivery from railways is essential.

Major Classification of CV Industry

Light Commercial Vehicle (LCV) – Goods & Carriage Vehicle with light capacity with Minimum Permissible Capacity (MPC) of 7 – 11 tons

Medium Commercial Vehicle (MCV) – Single Axle Vehicle used mainly for the carriage of perishable goods with MPC of 16 tons of Mass

Heavy Commercial Vehicle (HCV) – Dingle Axle Vehicle used mainly for the carriage of non-perishable goods with MPC of 17 to 25 tons of Mass

Major CV Financiers in India

Cholamandalam Finance, Sundaram Finance, AU Finance, Shriram Transport Finance, Magma, L&T, M&M, Religare, Tata Motors, Reliance

Objective of the Analysis

Objectives

Identify the factors which significantly affect the pool performance (delinquencies)

Illustrate the way in which these factors affect the delinquencies

Preliminary Analysis of CV Pools – All Originators

Data Used – An Overview

Securitized CV pool details from the Pool Performance reports (Sep’12) of Rating Agencies (CARE, ICRA and CRISIL)

Total number of Transactions (Data Points) - 190

Period of Transactions - 2008-2012

Number of Originators - 16

Major Originators used for Analysis

Shriram - 58 Transactions

Magma - 34 Transactions

AU - 21 Transactions

Tata Motors - 18 Transactions

Sundaram - 13 Transactions

Religare - 12 Transactions

Reliance Cap - 9 Transactions

Collection Details & Methodology Used

Parameters Collected for Analysis:

Transaction Details : Transaction month, Transaction Name, Originator, Transaction Structure, Type of Transaction, Rating Assigned for Seniors and Junior

Initial Pool Details : Pool Principal, Pool Composition, Credit Enhancement (% of Initial POS), EIS (% of Initial POS)

Pool Performance Details : Cumulative Collection Efficiency (CCE)

Methodology Used:

Collection of data from the Pool Performance (Sep’ 12) reports of Rating Agencies

Identification of factors, which are to be used for the analysis of transactions

Regression Analysis of these factors with respect Sep’12 CCE and Scatter plots to capture trends

Observe the significance level of factors which affects CCE

Findings from Preliminary Analysis of CV Pools (All Originators)

Pools having greater NCV Exposure (>40%) tend to

have better collection efficiency and lower credit

Enhancement (Figure 1)

Cumulative Collection Efficiencies of transactions are

continuously declining with respect to the year of

transactions during 2008-2012 (Figure 2)

Au pools seems to have the lowest CCE when

compared to its competitors in CV Industry (Figure 3)

Figure 2

2008 2009 2010 2011 20120

10

20

30

40

50

60

93%

94%

95%

96%

97%

98%

99%

100%

2

28

52 52

28

CCE by year of securitization

Total Transaction Collection EfficiencyYear

0

10

20

30

40

50

60

70

88%

90%

92%

94%

96%

98%

100%Originators and CV Analysis

No. of securities WCE

Figure 3

Figure 1

Preliminary Analysis of CV Pools – AU only

Data & Methodology Used

Data Used:

Securitized CV pool details from the Pool Performance reports (Sep’12) of Rating Agencies (CARE, ICRA and CRISIL)





Initial Pool Details : Pool Principal, Pool Composition, Credit Enhancement (% of Initial POS), EIS (% of Initial POS), Weighted Average Seasoning (Months), Tenure (Years)

Pool Performance Details : Cumulative Collection Efficiency (CCE)

Methodology Used:

Collection of data from the Pool Performance reports of Rating Agencies & Identification of factors, which are to be used

for the analysis of transactions

Single & Multiple Regression of these factors with CCE, Scatter plots for trend capture

Observe the significance level of factors affecting the delinquencies

Findings from Preliminary Analysis of CV Pools (AU Only)

Average CCE is better for the pools with Short Tenure

(<3 years) and High WAS (> 3months)

Average CCE is the lowest (around 92%) when the

pool mix is CV,AUTO and Tractors when compared to

other mixes

Average CCE, with respect to CV and Auto mix, is

ranging around 94%.

*CI in Figure 1 & 2 represent Confidence Interval

Figure 2 Figure 1

Detailed Analysis of CV Pools – All Originators

Data Used – An Overview

Securitized CV pool details from the Pool Performance reports (from Jun’ 08 to Dec’12) of Rating Agencies (CARE, ICRA

and CRISIL)



Number of Originators - 14

Quarterly data is collected for Cumulative Collection Efficiency and Quarterly Average Collection, starting from the first data

to the latest one available.

Major Originators used for Analysis

Shriram - 58 Transactions

Magma - 34 Transactions

AU - 21 Transactions

Tata Motors - 18 Transactions

Sundaram - 13 Transactions

Religare - 12 Transactions

Reliance Cap - 9 Transactions

Collection Details & Methodology Used



Initial Pool Details : Pool Principal, Pool Composition, Credit Enhancement (% of Initial POS), EIS (% of Initial POS), Weighted Average Seasoning (Months), Average Loan to Value, Average

Loan Size

Pool Performance Details : Cumulative Collection Efficiency (CCE), Quarterly Average Collection, 90+ & 180+ Delinquency Loss

Methodology Used:

Collection of data from the Pool Performance reports of Rating Agencies & Identification of factors, which are to be used

for the analysis of transactions

Single & Multiple Regression of these factors with 90+ and 180+ delinquencies

Observe the significance level of factors affecting the delinquencies

Findings from Detailed Analysis of CV Pools (All Originators)

In the transactions, Originators have greater impact on

delinquencies than the other parameters (Figure 1)

None of the other pool parameters are found to have

significant impact on the pool performance in multiple

regression (Figure 1)

Individual regression results suggest that more % of

NCV (less % of UCV), high Weighted Average

Seasoning and high Loan Size have positive impact on

delinquencies (Figure 2)

Figure 1 – Multiple Regression with 180+ Delinquency

Figure 2 – Individual Regression with 180+ & 90+ Delinquency

Limitations & Future Works

Limitations

Data Collected for only those transactions that are done after June 2008.

Reporting format was not uniform across all the rating agencies.

Inferences are based on small sample size.

Future Works

Time Series analysis of Delinquencies and Cumulative Collection Efficiency of earlier transactions to date and also from the

perspective of an originators can be done

All the originators should be analysed according to the individual assets of the pools (type of underlying vehicles).

Analysis of relation between the closely related independent factors viz. Loan size and % of NCV so as to figure out that

which of the two factors actually impacts the performance

Comparing the rating rationales, for similar rated transaction with different credit enhancement or vice versa, more deeply to

understand the factors seen by rating agencies

Market Outlook

Recent Study by ICRA

Asset Quality of CV

UCV – 90+ DPD 6.8% and 180+ DPD 3.8%

NCV - 90+ DPD 6.2% and 180+ DPD 1.5%

Macro-Economic Indicators

Correlation between GDP vs. 90+ DPD = -83% (-91% with three months lag of 90+dpd)

Correlation between IIP vs. 90+ DPD = -91%

Portfolio Analysis

In FY13, Average Tenure is 43 months

TN & Maharashtra contributed around 35% of total disbursement

MHCV weaker performance than other asset classes

High Tenure Contract (3 Years) showed weaker performance

Contracts originated in Orissa and Goa is affected a lot because of Mining Issues

Contracts with higher interest rates performed weakly

Repossession Loss

37% in New LCV and 39% in New MHCV

Loss due to repossession in UCV is slightly lower than New CV’s (Probably because of Lower LTV)

Repossession Rates in FY13 is ranging around 30-50%

Resale Value is reduced by 10-20% due to demand decline and discount on new vehicles

Conclusion

Concluding Remarks

Originators play an important role compared to other parameters when it comes to the

performance of CV Pools.

Also, with fair degree of confidence, it can be said following parameters have an

impact in a pool’s performance

% of NCV Exposure

Weighted Average Seasoning

Tenure of the pool

Loan Size (May be correlated with other factors like % of NCV)

GDP and IIP are the major indicators of CV industry

LCV - Safer bet than MCVs and HCVs

Questions ??

commercial vehicles. contents commercial vehicles – an overview objective of the analysis ...

Documents

transactions slide

analysis slide

commercial vehicle cv

transactions au

detailed analysis of

transactions sundaram

transactions religare

transactions magma