Data Collection Strategy in the Exacting Informational Environment

Data Collection Strategy in the Exacting Informational Environment

Seminar on Statistical Data Collection(Geneva, Switzerland, 25-27 September 2013)

By Nana Aslamazishvili

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Agenda

• Introduction• Existing Practice and Strategic Vision• What is the best way to define what to collect?• SebStat as a new data production architecture• Streamlining the statistical production• Communication issues• Lessons learned • Concluding remarks and future plans

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Introduction

Following the international statistical standards, NBG produces the majority of the country’s most important official statistics:• Financial Sector Statistics (Monetary and Financial

Statistics, Financial Soundness Indicators, Interest Rates Statistics);

• External Sector Statistics (BoP, IIP, External Debt Statistics, International Reserves Statistics, Exchange rates Statistics).

“Change in all

things is sweet”.

Aristotle

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Introduction

Our Achievements: Participation in the Data Dissemination Initiatives Figure 1

Data Sets Participating Countries

(areas), total

Georgia: since -

IFS 190 Feb/2000

Financial Soundness Indicators 74 Apr/2012

Financial Access Survey 187 2010

Standardized Reporting Forms 127 1997

International Reserves and Foreign Currency Liquidity Template

76 Apr/2010

SDDS 145 May/2010

COFER 144 Q2/2011

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Existing Practice and Strategic Vision

In General, data can be produced in many ways and each mode has a different cost structure, advantages and disadvantages. It is worth emphasizing, however, that traditional reporting mode, used at the NBG, leaves much to be desired.

NBG’s current data collection and production system might be characterized as:• Excel spread sheets based reporting,• Decentralized between different units,• Unsupported data validation and processing by the compliant IT

technologies, and hence• Unaccompanied with a centralized data warehouse.

Decentralized and multi-dimensioned datasets led to weaknesses of appropriate metadata.

“Sound strategy

starts with having

the right goal”.

Michael Porter

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Existing Practice and Strategic Vision

In order to define the main framework of our strategic vision on NBG’s statistical business process transformation we had to focus on following complicated questions:• Statistical needs: What would be more comprehensive set of data

according to the international standards we want to have from financial institutions?

• Collection strategy: What kind of mode would be more reasonable to change excel spread sheet based reporting over to web-based collection, and how to collect different data by the standardized way to ensure centralized collection?

• Streamlining: How to optimize standard Statistical Business Process Model in order to reduce reporting burden as well as data validation and production costs?

“Sound strategy

starts with having

the right goal”.

Michael Porter

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What is the best way to define what to collect?

Statistical needs, in terms of quality, availability, and analytical usefulness of financial and external sectors data, in both in-country and international context are clearly formulated in worldwide recognized manuals and guidelines, such as SNA, BoP, MFSM, FSI, and so on.

To be in conformity with international standards and integrally linked to other macroeconomic statistical systems, as well as to FSI and macroprudential analysis, we decided in favour of balance sheet data structure for financial institutions, describing the unified framework for comprehensive analytical consideration.

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What is the best way to define what to collect?“Statistics is the

grammar of

science”.

Karl Pearson

The ideal way to collect data for balance sheet purposes can be easily found in a System of National Accounts fundamental idea regarding analysing flows and stocks, reflected under the question: “Who does what, with whom, in exchange for what, by what means, for what purpose, with what changes in stocks?”

“Answering these questions for all economic flows and stocks and operators in a given economy would provide an enormous amount of information describing the complete network of economic interrelations“ (2008 SNA, Chapter 2. p.2.8).

In this very vision is based our approach in a part of data collection from the financial institutions.

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Instrument

What is the best way to define what to collect?

Figure 2

Financial/Nonfinancial Instruments In national/foreign currency By resident sectors: Central bank Other depository corporations Other financial corporations Central government Local government Public non-financial corporations Private non-financial corporations Other resident sectors Non-residents

What is the most comprehensive data requirements in line of international guidelines? Figure 2 shows a structural breakdown requirements for financial data analytical

purpose, used by the balance sheet approach, we are focus on

Currency breakdown

Residency

Sectorization

Residency

Figure 3

Financial/Nonfinancial Instruments In national/foreign currency By resident sectors: Central bank Other depository corporations by subsectors Other financial corporations by subsectors Central government Local government Public non-financial corporations by type of economic activities Private non-financial corporations by type of economic activities Other resident sectors households NPISHs Non-residents by countries by sectors by type of economic activities

To deeper in-country

analysis structural

breakdown was

broadened

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SebStat as a new data production architecture: a. Collection strategy

What kind of mode would be more reasonable to change excel spread sheet based reporting over to web-based collection, and how to collect different data by the standardized way to ensure centralized collection, on one hand, and automation of whole statistical business process, on the other?

One of the challenging question we arose at the very beginning was:

SebStat as a new data production architecture: b. Data Structure Defining Approach

Bank: BBB 31-May-13F4-3-b Monthly report on consumer loans, collateralized by securities and granted in national currency GEL

LoansOf which to:

Annual Interest Rate, %

Resident legal entities

Resident Households

Total 9,852,349 5,410,323 4,442,026% 18.2% 18.1% 18.4%

16.0% 4,127,935 2,137,237 1,990,69817.0% 432,433 281,656 150,77817.5% 158,503 158,503

18.0% 2,153,075 1,329,062 824,012

19.0% 787,369 534,792 252,577

Does what?

Who?

With whom?

In exchange for what?

For what purpose?

By what means?

With what changes in stocks?

source frequency instrument currency

Frequency

residency sector Additional info on loans Interest rate Data valuecollateralize

Currency

BBB.MM.F04000.GEL.RR.S14000.L010000.LC3.18.00.824012.00.20130531.=

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As a result, the key recording criteria for all financial/nonfinancial instruments are formed as follows:

• Status of instrument (assets/liabilities);• Data type (Stock/flow);• Maturity;• Currency denomination;• Additional information in case of loans (loans categories, specific loan products, etc.);• Loans collateralization (for FSI purpose);• Ranging of loans/deposits;• Counterpart characteristics:

– Residency– Sector– Type of economic activity.

These criteria are intended for monthly financial and statistical data family (FIM).

However, the same approach to the data structure definition is used in case of other data families, which are formed for identifying other statistical data under the NBG mandate.

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By the SebStat concept, each data family includes set of specific keys, identifying specific variables.

Scheme 1. SebStat Conceptual Framework

FIM – monthly financial and statistical data;FID - daily balance sheets data;MTR – money transfers statistics;FEX – foreign exchange transactions;BPC – bank payments cards statistics.

Special Code Lists, created for each statistical domain (Data Family) allow establish clear rules for data definition.

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One of the main advantage of the SebStat is that there is no need to compose questionnaires for data submission. NBG’s data requirements are presented in form of list of keys, identifying specific data, intended for submission.

Next three slides illustrate how the web-based submission is organized and how the data requirements look like.

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SebStat as a new data production architecture: c. Web-site support

CodeLists

FIM - Monthly financial and statistical indicatorsFID - Daily financial indicatorsFEX - Foreign Currency OperationsMTR - Money TransfersBPC - Payment cards

Data Requirements NewsData

UploadedData

Uploader

Data Families

Methodology

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An example of data requirements for Loans

The required

data structure

Keys, identifying

the required

data

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An example of XML files intended for submission to the NBG

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Streamlining the Statistical Production

Streamlining: How to optimize standard Statistical Business Process Model in order to reduce reporting burden as well as data validation and production costs?

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Streamlining the Statistical Production

Consequently we streamlined GSBPM significantly:1

Specify needs

Standardization of data structure makes easy to identify new requirements within

the existing mode

2Design

3Build

4Collect

5Process

9Evaluate

8Archive

7Disseminate

6Analyze

Well structured raw data through the relevant

classifications simplifies processing procedures and

makes it more efficient

Well established algorithm for producing reliable time series and

other outputs makes more efficient and time saving output products;

there is more time for the promotion of

dissemination products and improvement of

communication with users

SebStat conceptual and IT architecture includes appropriate tools for designing final outputs; data collection and processing modes are

premeditated by the standardized way

SebStat makes flexible enough to

prepare draft outputs, redesign

existing ones and use other illustration

materials (graphs, diagrams, etc.)

SebStat concept itself connotes its step-by-step implementation, by financial

institutions, on one hand, and by statistical domains, on the other. It is

worth emphasizing, however that standardized procedures, established

initially allows to solve related challenges by the standardized way and

speed up evaluation process significantly.

Of course, when whole statistical business

process is automated, technically is makes easy to define archive rule and

implement it.

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Communication Issues

To ensure success of the SebStat project we needed to change our communication strategy dramatically.

In order to ensure awareness of our new ideas and plans regarding

statistical business process transformation we carried out 7 joint meetings during the 2011-

2013 with banks representatives

In order to resolve specific reporting related problems of

individual banks we carried out more than 30 meetings with

single banks professionals and IT experts

FAQs practice was implemented in order

to justify specific issues arose in the particular banks

E-mail or telephone

communication is common for prompt reply

Skype or video conference is used for inter-country

(Ukraine, Turkey) communications, when

respondent-bank’s foreign partners are involved in the

SebStat Implementation processes

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SebStat GuideNational Nomenclature of Types of Economic ActivitiesBridge TableInstructions for data uploadingExamples of XML files for each Data FamilyCase studies for Loan products identificationNBG’s President Decree N350

Methodolodical Materials and Technical Tools

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In order to investigate bank’s short- and long-term needs and challenges they are facing we carried out SebStat Implementation Assessment survey.

The results are fruitful enough:Firstly, they show that bank’s expectations regarding SebStat project success are positive, andSecondly, they serve as recommendations for identifying priorities for future cooperation.

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However, there are several most pressing problems in the process of SebStat Implementation:inconsistency between SebStat methodology and

existing one within banks (41%); inadequacy of existing IT technologies at the banks

(29%). Probably because of this problem banks expectations regarding reporting burden are slightly negative (53%).

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On the whole, banks consider that methodological and technical support from the NBG side is sufficient enough for SebStat implementation (4.29; scope 1-5) and would be still continued in the future. Moreover, 29% of surveyed banks consider that there is a room for future enhancing of SebStat framework.

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Lessons Learned

Despite a fact, that implementation of a new statistical informational system of NBG takes place in condition of extremely limited resources, it is worth emphasizing, that SebStat is an ambitious project. However, it is successful thanks to number of well-considered points.

• Prerequisites: first of all, it should be analysed all prerequisites (existing practice, professional experience and skills, data collection environment, etc.) for changes.

• Confidence: to have a clear understanding of problem and ways how to solve it, before introduction of new idea, is essential in order to gain real trust and confident among stakeholders.

• Priorities: learn how to develop priorities, especially when resources are limited. It is essential to be sequent in actions.

• Working Team: Well organized working team plays important role for project success. Members of the team should be methodologists, analysts, national accountants, subject-matter statisticians (depending on Central Bank’s mandate), bankers, financial accountants, IT specialists, programmers, depending on the nature of problems to be solved.

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Lessons Learned

• Long-Term Aims: It is essential to focus own initiatives and ideas on a long-lifecycle statistical project; Statistics is too important to be taken lightly.

• Cooperation Strategy: Effective cooperation strategy with data providers and users is one of the important priorities of statistical production process organization.

• High level management support is essential for project success. It is crucial to understand, that “The only free cheese is in the mouse trap”. It is essential to convince the management that it is the exact.

Generally speaking we strongly believe that SebStat is the right direction to right positioning on the modern information market, and our strong expectation is that with SebStat we can produce timely, relevant and competitive statistics.

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Concluding Remarks and Future Plans

• Hence, it was our aim to create innovative informational system able to change dramatically “stove pipe” production into standardized procedures for each step of the data collection and production processes at the NBG. After the pilot round of collection, quality of data and uploading procedures are more than promising.

• The adoption of the new centralized collection standards makes it

easier to establish a flexible statistical data management system not only at central bank, but at the commercial banks also.

• The main advantage of SebStat is that it makes much easier, less

resource-intensive, and less burdensome on data providers.

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• SebStat as a system creates environment that facilitates enhancement of statistical data collection scope and quality, on one hand, and improvement of statistical capacity in terms of data presentation and dissemination, on the other. As one of the next step of implementation, other financial institutions will be

included in SebStat project.

• In a broad sense, SebStat as a statistical informational system connotes formation of the Integrated Meta-Informational System. It is essential to analyzing and interpreting SebStat-related data and to making meaningful decisions. Creation of the Integrated Meta-informational System will be one of the

important achievements of the SebStat project.

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• It is worth emphasizing, that SebStat, by its concept and architecture, intended to be a system with a long lifecycle. On the other hand, data production now-a-days requires significantly higher skills and professionalism, then before. So, it is crucial to establish a good, continuing knowledge transfer mechanism in order to ensure using of system’s capacity in a workmanlike manner. Elaboration of comprehensive training materials for data providers, as well

as for data producers and users is very important, and its realization is one of important part of our plans in the near future.

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Thank you___________________

For more information:Nana Aslamazishvili

Head of Monetary Statistics DivisionNational bank of Georgia

[email protected]: (995 32) 240 6251

mailto:[email protected]

Documents

Data Collection Strategy in the Exacting Informational Environment