Is there a clear relationship between credit growth and market growth?
The fastest growing cities out of 112
Market Size
Growth rates Deposit Credit Growth
Growth
(CAGR) Growth Rate Rate
Rate
Silvassa 23 14 71
Gandhinagar 22 10 54
Bokaro 19 7 -4
Surat 17 11 18
Thiruvallur 17 11 28
Agartala 16 13 32
Chandigarh 16 13 7
Thanjavur 16 5 20
Kohima 15 9 26
Noida 15 28 43
The slowest growing cities out of 112
Market Size
Growth rates Deposit Credit Growth
Growth
(CAGR) Growth Rate Rate
Rate
Guntur 8 7 16
Gwalior 8 6 9
Jabalpur 8 3 0
Nellore 8 7 22
Varanasi 8 6 13
Kanpur 7 7 13
Kavaratti 7
Vijayawada 7 7 24
Dhanbad 6 12 15
Kancheepuram 2 16 22
With the exception of Bokaro, and to a certain extent Chandigarh, the 10 fastest growing cities grew
on the back of high credit growth. However, this is not a general rule as a look at the slower growing
cities reveal. Cities such as Vijaywada, Kancheepuram, Nellore and Guntur did not display a robust
growth in spite of high credit growth. Deposit growth, on the other hand is an effect of market growth
and in general grows in the wake of market growth. This is generally borne out by the facts, though a
few notable exceptions exist – Thanjavur, Kohima, Bokaro (among the fast growing cities) and
Dhanbad and Kancheepuram (slow growing cities)

Insights into the Financial landscape of the country
Indian Financial Scape provides insights into the financial landscape of the country. It
presents nearly 250 different variables atdistrict level. The product helps enhance a
professional’s understanding of the markets. A few samples of unusual insights are
presented below. There are many more interesting ones available in the product.
Fastest growing districts in terms of Personal Loans (Personal loans, as defined by
RBI includes all loans taken by individuals – secured and unsecured)
Unit %
2001-02 to
Year 2007-08
Personal loans
- growth rate of
SCB`s credit
State District
Karnataka Bangalore Rural 77
Meghalaya West Garo Hills 74
Arunachal Pradesh Changlang 72
Arunachal Pradesh East Siang 72
Arunachal Pradesh Papum Pare 72
Arunachal Pradesh West Kameng 72
Bihar Katihar 72
Uttar Pradesh Sant Kabir Nagar 71
Haryana Jhajjar 70
Assam Hailakandi 69
Gujarat Narmada 69
Haryana Panipat 68
Haryana Rohtak 67
Haryana Sonipat 67
Haryana Faridabad 62
Jammu & Kashmir Pulwama 62
Mizoram Champhai 60
Bihar Araria 57
Chhattisgarh Rajnandgaon 57
Uttar Pradesh Baghpat 56
Arunachal Pradesh is an unusual place. Not much is known about it and it has a small
base. Yet, on a sustained basis, over a 6 year period, four of its districts have figured
among the top 6 districts in India in terms of growth in personal credit. Haryana is
another place which has seen a boom with four of its districts figuring in the top 15.
Fastest growing districts in terms of Professional and other Services credit
Unit % %
2001-02 to 2001-02 to
Year 2007-08 2007-08
Professional & Personal
other Services - loans - growth
growth rate of rate of SCB`s
SCB`s credit credit
State District
Gujarat Rajkot 51 26
Chhattisgarh Korba 47 34
Punjab Bathinda 47 50
Andhra Pradesh Krishna 46 18

Rajasthan Ajmer 46 31
Rajasthan Kota 44 25
Madhya Pradesh Katni 44 12
Chhattisgarh Kanker 44 34
Rajasthan Ganganagar 43 31
Sikkim South Sikkim 42 26
Sikkim North Sikkim 42 53
Arunachal Pradesh Lohit 42 -16
Rajasthan Jodhpur 42 36
West Bengal Haora 42 17
Sikkim East Sikkim 42 16
Rajasthan Sikar 41 51
Orissa Sambalpur 41 34
Haryana Rewari 40 -11
Andhra Pradesh Nalgonda 40 21
Haryana Mahendragarh 40 33
The growth in credit in this category has been much lower than in the personal credit
category. The districts that have grown fastest are those that are not in the top pecking
order, yet they are not very small either. Lohit, in Arunachal Pradesh is unusual
because it shows a negative growth in personal credit. Its possible that personal credit
were routed through Professional credit in reality. Rewariis another standout – high
growth in Professional combining with a negative growth in personal credit.
Fastest growing districts in terms of Trade Credit
Unit %
2001-02 to
Year 2007-08
Trade Credit -
growth rate of
SCB`s credit
State District
Tamil nadu Nagapattinam 49
Chhattisgarh Rajnandgaon 47
Meghalaya Jaintia Hills 44
Haryana Jhajjar 40
Karnataka Bangalore Rural 40
Uttar Pradesh Mahoba 40
Gujarat Kheda 39
Orissa Ganjam 39
Haryana Gurgaon 38
Himachal Pradesh Kinnaur 38
Gautam Buddha
Uttar Pradesh Nagar 38
Sikkim East Sikkim 37
Jammu & Kashmir Leh (Ladakh) 37
Bihar Madhubani 37
Arunachal Pradesh West Kameng 36
Uttaranchal Rudraprayag 35
West Bengal Medinipur 35
Andhra Pradesh Medak 35

Haryana Panchkula 34
Nagaland Mon 34
Economic Risk
The Economic Risk Index is an important variable to consider while doing business. In case of
financial products, it is important for marketers to consider the risks involved in addition to
market size, growth and demography. Indian Financial Scape is a product which has introduced
an Economic Risk index and rated districts based on variables such as economic offences,
credit penetration, and credit overdue per credit of district central cooperative banks, Gross
domestic product, GDP Growth, No. of Industrial Disputes (All strikes & Lockouts) and Maydays
Lost Due to Industrial, Disputes per worker..
The top ranking districts in terms of economic risk
State District
Dadra & Nagar Haveli Dadra & Nagar Haveli
Daman & Diu Daman
Daman & Diu Diu
Lakshadweep Lakshadweep
Madhya Pradesh Neemuch
Madhya Pradesh Jhabua
Rajasthan Ganganagar
Himachal Pradesh Kinnaur
Madhya Pradesh Shajapur
Madhya Pradesh Satna
The worst districts in terms of economic risk
State District
Pondicherry Mahe
Pondicherry Yanam
Pondicherry Pondicherry
West Bengal Kolkata
West Bengal Koch Bihar
West Bengal North 24 Parganas
West Bengal South 24 Parganas
Jharkhand Dumka
Arunachal Pradesh Tirap
West Bengal Puruliya
How are some of the top business centres ranked (out of nearly 600 districts of India)?
District Rank
Hyderabad 177
Delhi 104
Ahmadabad 35
Surat 33
Bangalore 110
Mumbai 72
Mumbai (Suburban) 70
Pune 74
Chennai 111
Coimbatore 112
Kolkata 581

Most of the major centres are ranked within the top 30%. However, there are wide differences.
The Western region (Mumbai, Ahmadabad, etc.) are clearly the safest. Kolkata stands out with
a very poor ranking.

Demand for Housing
The Housing Skyline of India estimates the demand for housing units in the top 30 cities to
grow by 6.36 million units during the next 7 years leading up to 2015. The current stock of
housing units in these 30 cities is estimated to be 25 million units, which implies a growth in
housing stock of over 25% within 7 years.
Demand between 2008 and 2015
Demand for
Demand for Demand for
Total Demand Plinth Area
Plinth Area Less Plinth Area More
for Housing Between 500-
than 500 Sq ft than 1000 Sq ft
1000 Sq ft
Top 10 cities 1,186,0
(alpha) 3,548,000 1,212,000 1,151,000 00
Next 20 cities 965,0
(beta) 2,815,000 930,000 921,000 00
Top 30 cities 2,151,0
(alpha + beta) 6,363,000 2,142,000 2,072,000 00
Current Stock
Current Housing Current Housing Current Housing
Current Housing Stock - Plinth Stock - Plinth Stock - Plinth
Stock Area Less than Area Between Area More than
500 Sq ft 500-1000 Sq ft 1000 Sq ft
4,458,0
Top 10 14,624,000 5,829,000 4,337,000 00
3,089,0
Next 20 10,413,000 4,179,000 3,145,000 00
Top 30 25,037,000 10,008,000 7,482,000 7,547,000
Whereas most of the attention of the building industry is on the upper segment, it is middle and
lower middle India which is driving demand -
 The demand for housing of size less than 1000 sq ft is 4.2 million units over 7 years,
which is 2/3rd of the demand
 The anticipated growth in percentage terms in the lower segments (24% combined) is
only marginally lower than the upper segment (28.5%)
 The pattern is similar for the alpha (top 10) and beta (the next 20) cities, implying a
uniform demand for affordable housing.
The above pattern indicates that a renewed focus on affordable housing is in order. There is
plenty of demand out there; supply is more likely to be the constraint.
Alpha cities are - Hyderabad, Delhi, Ahmadabad, Surat, Bangalore, Mumbai, Pune, Chennai,
Coimbatore, Kolkata
Beta cities are – Asansol, Bhopal, Faridabad, Indore, Jaipur, Jamshedpur, Kancheepuram,
Kanniyakumari, Kanpur, Kochi, Lucknow, Ludhiana, Madurai, Nagpur, Patna, Salem,
Thiruvallur, Urban Areas in North 24 Parganas, Urban Areas in Thane, Vadodara
The estimation process involved the following steps:
 Demographic parameters such as population across age-groups, change in household
sizes, and family structures were estimated using data from census and various large
scale data surveys.
 This data was used with large scale survey data on housing conditions (NSSO 49th and
58th rounds) to establish the relationship between housing demand and demographic
parameters.
 Independently the relationship between ownership and income was established.
Estimates of current income and growth from “The Market Skyline of India” were used
to estimate households across income levels for the two time periods.
 One of the major drivers of housing demand is the current and future rental markets.
This in turn is driven by growth in economy, employment and migration trends.
Estimates of GDP, employment growth and migration were used from “The District
Level GDP 2006-07” to define the relationship with housing demand.
 Another relationship established was the ease and extent of availability of finance and
housing demand. Data from RBI on housing loans for the last ten years were used to
determine the function.

 All these aspects were then combined to estimate the net demand in housing during
the period 2008-15. They were also used to determine the demand for housing across
various segments including income categories, plinth area, room size, etc.
 The entire exercise was validated at various stages using a primary survey of
households on income, demography, financial habits and housing conditions conducted
in July 2008. Secondary data such as housing stock estimates from NHB, proposed
construction data from various housing boards, etc. were also used to cross check
estimates at various intermediate steps.

Financial Asset Penetration
On an average, only 16% of Indian households have taken loans from institutional agencies.
On the other hand, 22% of the households have taken loans from non institutional agencies.
There are two clear indications here – a) the bulk of the population is financially underserved
and rely on informal lending and b) the non institutional agencies have together achieved a
much higher penetration than the institutional agencies.
If we look at another indicator of financial inclusion, namely percentage of households who hold
stocks and debentures, we find that the penetration is just 5%.
There is no doubt that financial inclusion is extremely poor and financial institutions need to
focus more on expanding the market rather than flog the existing markets.
Here are the top districts in terms of penetration of institutional loans. These districts have
penetrations ranging from 37% to 68%. As many as 14 of these 20 are from Kerala. The
districts are Kottayam, Kannur, Idukki, Ernakulam, Pathanamthitta, Kasaragod, Wayanad,
Palakkad, Kollam, Thrissur, Kozhikode, Malappuram, Alappuzha and Thiruvananthapuram
from Kerala and Mahe, Udupi, Satara, Kolhapur, Wardha, Shajapur (MP).
The bottom twenty districts (all less than 1% penetration) are mainly from the hill districts
(Arunachal Pradesh, Manipur, Mehghalaya and J&K - Changlang, East Kameng, Lohit, Lower
Subansiri, Tirap, Dhubri, Kupwara, Bishnupur, Chandel, Churachandpur, Senapati,
Tamenglong, Thoubal, Ukhrul, East Garo Hills, Jaintia Hills, Ri Bhoi, South Garo Hills, West
Garo Hills
The picture changes substantially when one looks at the penetration of non institutional loans.
The top 24 districts have penetration ranging from 50-53%. These are - Tiruchirappalli,
Nagapattinam, Thiruvarur, Thanjavur, Karur, Pudukkottai and Perambalur from Tamil Nadu,
Mahe, Karaikal, Pondicherry, Yanam from Pondicherry, and Prakasam, Srikakulam, West
Godavari, Krishna, Nellore, Guntur, Visakhapatnam, Vizianagaram, East Godavari, Chittoor,
Cuddapah, Anantapur and Kurnool from Andhra Pradesh indicating a clear geographic pattern.
The bottom districts are again from the hill states. In fact of the bottom 64 (up to 7%
penetration) - 2 are from Andaman and Nicobar, 13 are from Arunachal, 14 are from J&K, 7
from Meghalaya, 8 from Mizoram, 4 from Sikkim, 13 from Uttaranchal, and 3 from West
Bengal.
At a broader level there is a clear need for enhanced services in the hill states. However, even
among the relatively well off districts, it is interesting to note that TN and Andhra seem to have
a very high penetration of non institutional loans as compared to institutional loans – clearly an
area for capturing the low hanging fruits for the formal sector.

How many people invest in stocks and shares?
We all know that penetration of shares and debentures is extremely low in India. Just how low
is it? The various data thrown around suggest around 30 million demat accounts. This however
does not account for multiple accounts of investors.
In our product, Indian Financial Scape, we have estimated the number of households (not
individuals) who own shares and debentures at district level. This is based on large scale
household surveys at various points in time conducted by Census of India, NSSO, and others.
Some of the top line results are as follows:
 Less than 5% of the households, about 12 million in number own shares and
debentures (note: this can translate into anywhere between 20-25 million individuals
and 30-40 million demat accounts)
 Region wise the penetration of shares and debentures (% of households) are – West
5.25%, North 4.52%, South 8.17%, and East 3.2%.
 West is dragged down by Rajasthan (3.6%) and MP (3.2%). The other states in the
West are Maharashtra (8.4%), Gujarat (6.1%) and the combined Goa, Daman and Diu,
Dadra Nagar Haveli (8.2%)
 At state level, the highest penetrations are in:
Goa,
Daman, Tamil
Delhi Kerala Karnataka Maharashtra Dadra Nadu Punjab Haryana
13.00 10.50 8.96 8.37 8.20 7.97 7.00 6.95
 The leading districts in terms of penetration are:
Maharashtra Karnataka Maharashtra Maharashtra Haryana
Mumbai
Mumbai Udupi (Suburban) Thane Panchkula
27 24 23 20 19
West
Chandigarh Bengal Goa Karnataka Kerala
Chandigarh Kolkata North Goa Bangalore Ernakulam
19 19 18 18 18
Tamil
Kerala Nadu Maharashtra Karnataka Karnataka
Dakshina
Thrissur Chennai Kolhapur Kannada Dharwad
18 18 17 17 17
Andhra Madhya
Pradesh Karnataka Kerala Gujarat Pradesh
Uttara
Hyderabad Kannada Kottayam Ahmadabad Indore
15 15 15 14 14
 The bottom 41 districts in terms of penetration are all from the East
 The bottom 249 districts (42% of the districts) are from the East, hill states or MP,
Rajasthan and UP. In fact, if we ignore the backward areas of Vidarbha and
Panchmahals, then we actually see that the bottom 50% (about 290 districts) are all
from the East, hill states or MP, Rajasthan and UP, clearly indicating an East-West
divide in penetration.

Housing Stock and Demand
The Housing Skyline of India estimates the demand for housing units in the top 112 cities to be
10.5 million units during the next 7 years leading up to 2015. The current stock of housing units
in these cities is estimated to be 41.8 million units, which implies a growth in housing stock of
over 25% within 7 years
Of these 112, the top 30 cities will account for 60% of the demand and are expected to add
6.36 million units during the next 7. The current stock of housing units in these 30 cities is
estimated to be 25 million units.
Current stock of houses
with plinth area > 1000 sq
feet (figures in ‘000s)
Figures in
The top 112 Cities millions
Households with Plinth Area Less than 500 Sq ft 17.0
Households with Plinth Area Between 500-1000 Sq ft 12.5
Households with Plinth Area More than 1000 Sq ft 12.3
Demand for units (2008-2015) for Plinth Area Less than 500 Sq ft 3.5
Demand for units (2008-2015) for Plinth Area Between 500-1000 Sq
ft 3.4
Demand for units (2008-2015) for Plinth Area More than 1000 Sq ft 3.7
Figures in
The top 30 Cities millions
Households with Plinth Area Less than 500 Sq ft 10.01
Households with Plinth Area Between 500-1000 Sq ft 7.48
Households with Plinth Area More than 1000 Sq ft 7.55
Demand for units (2008-2015) for Plinth Area Less than 500 Sq ft 2.14

Demand for units (2008-2015) for Plinth Area Between 500-1000 Sq
ft 2.07
Demand for units (2008-2015) for Plinth Area More than 1000 Sq ft 2.15
Whereas most of the attention of the building industry is on the upper segment, it is middle and
lower middle India which is driving demand -
 The demand for housing of size less than 1000 sq ft is 6.2 million units over 7 years,
which is 2/3rd of the demand
 The anticipated growth in percentage terms in the lower segments (23% combined) is
lower than the upper segment (30%), but on a base which is nearly two and a half
times.
 The pattern is similar for the alpha (top 10) and beta (the next 20) cities, implying a
uniform demand for affordable housing.
The above pattern indicates that a renewed focus on affordable housing is in order. There is
plenty of demand out there; supply is more likely to be the constraint.

Demography – Age profile of the top 112 cities of India
The age profile of the top 112 cities (which account for a population of 200 million) does not
show too much variation. 69% are between the age of 18 and 60 and the proportions do not
vary much across different cities. The proportion of the aged in the larger cities is higher but
only marginally.
In sheer numbers, about 36 million people in the top 112 cities are above 60 years of age and
the alpha cities account for 35% of them. The under 18 population is significantly smaller at
about 26 million
under 18
years 18-35 years 35-60 years > 60 years
Alpha (top 10) 12.4% 34.3% 34.7% 18.6%
Beta (11th to 30th) 13.0% 34.7% 34.2% 18.1%
Gamma (31st to
50th) 14.1% 35.9% 32.7% 17.3%
Delta (51st to 112th) 14.3% 36.7% 31.6% 17.3%
Total (112 cities) 13.3% 35.3% 33.5% 17.9%
under 18
years 18-35 years 35-60 years > 60 years
8,306,88 23,052,69 23,318,89 12,456,12
Alpha (top 10) 8 8 0 8
6,714,66 17,926,72 17,642,44 9,352,40
Beta (11th to 30th) 1 3 8 0
Gamma (31st to 4,390,77 11,161,25 10,161,63 5,388,43
50th) 6 8 6 6
7,211,06 18,473,93 15,894,69 8,708,91
Delta (51st to 112th) 2 6 0 7
26,623,38 70,614,61 67,017,66 35,905,88
Total (112 cities) 7 5 4 1
under 18 years 18-35 years 35-60 years > 60 years
12,456,128
9,352,400 8,708,917
23,318,890
17,642,448 15,894,690
5,388,436
23,052,698 10,161,636
17,926,723 18,473,936
11,161,258
8,306,888 6,714,661 7,211,062
4,390,776
Alpha (top 10) Beta (11th to 30th) Gamma (31st to 50th) Delta (51st to 112th)

under 18 years 18-35 years 35-60 years > 60 years
18.6% 18.1% 17.3% 17.3%
32.7% 31.6%
34.7% 34.2%
35.9% 36.7%
34.3% 34.7%
12.4% 13.0% 14.1% 14.3%
Alpha (top 10) Beta (11th to 30th) Gamma (31st to 50th) Delta (51st to 112th)

Income and Savings in Urban India
The top 112 cities account for about 200 million Indians which is more than 60% of urban India. These
cities constitute a market of consumers whose combined annual incomes are Rs 13.26 billion. Their
combined savings are Rs 3.5 billion which is about 26.5% of income. However there is considerable
heterogeneity in the income and savings pattern across these cities.
If we look at four classes of cities (by size), we get the following picture:
Total Income (Rs Total Savings Savings/
billions) (Rs billions) Income Ratio
Alpha (Top 10) 5,912 1,296 21.9%
Beta (11th to 30th) 2,887 931 32.2%
Gamma (31st to 50th) 1,774 519 29.3%
Delta (The balance 62) 2,688 771 28.7%
Top 112 cities 13,261 3,516 26.5%
The large cities have a significantly lower savings rate. The top 10 cities have a savings rate of under
22%, whereas the gamma and delta cities (82 in number) have savings rate around 29%. Clearly the
EMI culture hasn’t percolated down to too many cities in India. An interesting piece of statistics is that
the 2nd rung of cities are the biggest savers – the beta cities save as much as 32% of their income and
reinforce the old adage that savings and investment are the route to growth.
If we look at the same set of data through the regional prism, we get the following picture:
Total Income (Rs Total Savings Savings/
billions) (Rs billions) Income Ratio
East 2,011 522 25.9%
West 5,167 1,191 23.0%
North 2,849 797 28.0%
South 3,233 1,007 31.1%
The Southerners are by far the largest savers with a savings rate of over 31%. The West (it includes
Rajasthan and MP) has the lowest savings rate of just 23%. Within West, Gujarat is a high saver with
27% savings rate whereas Maharashtra saves only 18%. Madhya Pradesh is a very high saver with
savings rate of 38%.
Contrary to popular wisdom, the North is not exactly spendthrift, they are second only to the South in
savings rate.
What do the figures look like for some of the major cities?
Total Income (Rs Total Savings Savings/
billions) (Rs billions) Income Ratio
Mumbai 1,608 216 13.4%
Delhi 1,264 289 22.8%
Bangalore 602 192 31.9%
Urban Areas in Thane 569 132 23.2%
Pune 446 111 24.9%
Ahmadabad 429 109 25.3%
Chennai 393 88 22.2%
Kolkata 350 68 19.3%
Surat 318 82 25.8%
Hyderabad 295 87 29.3%
Mumbai has the lowest savings rate. Delhi, Kolkata and Mumbai’s neighbours are also low savers.
Bangalore and Hyderabad are high savers, much higher than average.
The heterogeneity of India is well reflected in the savings patterns. There are no clear regional patterns.
However, it is evident that the economically vibrant cities are lower in savings rate as compared to their
regional brethrens which reinforces the theory that consumerism is one of the key pivots of the recent
surge in economic growth and erosion in consumer confidence will impact economic growth negatively.