Governor Dr. Subbarao, Prof. Bimal Roy, Prof. Richard Smith, Prof. B.L.S. Prakasa Rao, Prof. Subhashis Ghoshal, Deputy Governor Dr. Patel, Deputy Governors, colleague Executive Directors, Shri A. B. Chakraborty, distinguished guests from the financial sector and academia, members of the press, colleagues from the Department of Statistics and Information Management (DSIM) and friends. I extend a warm welcome to all of you to this 7th Statistics Day Conference.

Since 2007, we in the Reserve Bank have been celebrating Statistics Day in the honour of Prof. P.C. Mahalanobis. Professor Mahalanobis was not only an outstanding statistician, but a great visionary. He is regarded as the father of the Indian statistical system. While we honour the sterling contribution of Prof. Mahalnobis, this event has turned out to be an important occasion for focusing on further development of statistics in the Reserve Bank.

Prof. Mahalanobis was the founder director of the Indian Statistical Institute (ISI). We are happy that two ISI Directors - Prof. Bimal Roy and Prof. B. L. S. Prakasa Rao - are here with us today. Prof. Mahalanobis studied and spent his early years in Cambridge. We are delighted that Prof. Smith, a leading econometrician from Cambridge is with us today. We also have with us Prof. Ghoshal from North Carolina University who represents the new generation of statisticians. I once again welcome our guest speakers.

The year 2013 has added significance for statistics as it has been declared as the International Year of Statistics. Primary objectives of this worldwide event, supported by several organizations, are to increase public awareness of the power and impact of statistics on all aspects of society, to nurture statistics as a profession, especially among young people, and to promote creativity and development in the sciences of probability and statistics.

In the Reserve Bank, we treat statistics as a public good. It is necessary not only to aid our decision making but also for empowerment of citizens. Our statistics department is playing an important role by making available macro-financial statistics in the public domain, conducting forward looking surveys and generating forecasts of macroeconomic variables for supporting monetary policy making. The department is also providing statistical support to other functions of the Bank.

In the wake of the recent financial crisis, there is renewed focus on availability of information and statistical gaps globally. The department is actively engaged with other international bodies such as the IMF, G20, BIS and FSB in strengthening our financial statistics and adopting international best practice.

Notwithstanding various achievements, there are challenges. I take this opportunity to focus on three of those:

• How to make the best use of granular data from banks?
• How to enhance the scope and coverage of corporate finance statistics?
• How to further develop asset price statistics?

First, the requirement of disaggregated granular banking data on a more frequent basis for policy and research has increased. For example, we have been compiling account level data on deposit, credit and interest rates on an annual basis through Basic Statistical Returns (BSRs). These data are an important source for understanding monetary transmission. Hence, there is a need to obtain these data on a higher frequency, at least on a quarterly basis, electronically from the banks’ source systems. Moreover, data on similar items obtained through various statistical returns show significant differences. Hence, there is need to harmonise data definition across various returns submitted to different departments of the Bank. This will require a close coordination between statisticians and regulatory departments to identify, harmonise and mitigate data gaps.

On the part of the banks, implementation of core banking solution has created the potential for banks to provide granular data electronically, both for statistical and supervisory purposes, directly from their source systems. It is important for reporting entities to adopt straight through processing without manual intervention so as to maintain data integrity. This will also help rationalisation of various returns thereby reducing the reporting burden on banks. Of course, as granularity increases data size becomes large. I am happy to note that today we have two special talks on big data which will have practical relevance for our data analysis.

Second, the Reserve Bank is compiling data on corporate finance such as production, sales and profitability. These data are also used to generate corporate saving and investment at the national level. From a financial stability perspective, the corporate balance sheet data are important for assessing risk parameters such as leverage and unhedged foreign currency borrowings. Corporate performance data is also important to understand the micro foundation of pricing power and hence inflation dynamics. There is, therefore, a need to expand our sample size and the coverage of financial details. We should also establish links with Ministry of Corporate Affairs (MCA) database to improve our coverage of corporate statistics.

Third, asset prices, particularly house prices are assuming greater importance in monetary transmission. While development of housing finance in advanced countries has a long history, the expansion of housing finance by the formal financial sector in India is of relatively recent origin. Keeping in view the demand-supply gap, our favourable demography, increasing urbanisation and growth prospects, the demand for housing finance will continue to grow. At the same time risks also arise to household and bank balance sheets with fluctuation in prices and changes in the business cycle. Hence, there is a need for developing a data base on housing finance.

Availability of statistics on housing finance has been limited. We have two publicly available house price indices (HPIs): (i) NHB-Residex compiled on survey based information for 20 cities, and (ii) RBI-HPI based on registration prices information for 9 cities. However, to assess the impact of house prices on the broader economy such information as loan to value (LTV) ratio, equated monthly instalment (EMI) to income ratio, price to income ratio, borrowers’ characteristics and other important attributes of the property dealings becomes important. Recently the department has launched a new statistical survey to capture such information based on housing loan transaction as available with banks and housing finance companies (HFCs). I hope this survey can be placed in public domain quickly after it is examined by our technical advisory committee on surveys.

On this occasion of the Statistics Day I congratulate colleagues from the statistics department for the good work they are doing. I once again extend a hearty welcome to all our speakers and all our invitees, and look forward to the intellectual fare ahead.

Thank you.

Granular banking data: mandate higher frequency electronic reporting and harmonised definitions to strengthen policy and supervision. The address sets three operative priorities: obtain higher frequency electronic granular banking data with harmonised definitions and straight through processing; expand and link corporate finance statistics to assess balance sheet risks and pricing dynamics, including linkage with the Ministry of Corporate Affairs; and develop comprehensive housing finance and asset price statistics covering LTV, EMI to income, price to income and borrower characteristics, backed by a new housing loan transaction survey and timely public release.