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Commercial Vehicles - PowerPoint Presentation

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Commercial Vehicles - PPT Presentation

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 ID: 150925

pool transactions performance analysis transactions pool analysis performance amp factors figure originators details pools collection transaction data rating average

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Slide1

Commercial VehiclesSlide2

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

ConclusionSlide3

Commercial Vehicles – An OverviewSlide4

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, RelianceSlide5

Objective of the AnalysisSlide6

Objectives

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

Illustrate the way in which these factors affect the

delinquenciesSlide7

Preliminary Analysis of CV Pools – All OriginatorsSlide8

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 TransactionsSlide9

Collection Details & Methodology Used

Parameters Collected for Analysis:

Transaction Details :

T

ransaction 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 Slide10

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

Figure

3

Figure 1Slide11

Preliminary Analysis of CV Pools – AU onlySlide12

Data & Methodology Used

Data Used:

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

Total number of Transactions (Data Points) - 21

Period of Transactions -

2010-2012

Parameters

Collected for Analysis:

Transaction Details :

T

ransaction 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),

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

Observe the significance level of factors affecting the delinquencies Slide13

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 1Slide14

Detailed Analysis of CV Pools – All OriginatorsSlide15

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)

Total number of Transactions (Data Points) -

194

Period of Transactions - 2008-2012

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 TransactionsReligare - 12 TransactionsReliance Cap - 9 TransactionsSlide16

Collection Details & Methodology Used

Parameters Collected for Analysis:

Transaction Details :

T

ransaction 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),

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 transactionsSingle & Multiple Regression of these factors with 90+ and 180+ delinquenciesObserve the significance level of factors affecting the delinquencies Slide17

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+ DelinquencySlide18

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 Slide19

Market OutlookSlide20

Recent Study by ICRA

Asset

Quality of

CV

U

CV

–    90+ DPD

6.8% and 180

+ DPD 3.8%

N

CV

-    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 monthsTN & Maharashtra contributed around 35% of total disbursementMHCV weaker performance than other asset classesHigh Tenure Contract (3 Years) showed weaker performanceContracts originated in Orissa and Goa is affected a lot because of Mining IssuesContracts with higher interest rates performed weakly

Repossession Loss37% 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 Slide21

ConclusionSlide22

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 HCVsSlide23

Questions ??