Sunday, January 10, 2010

Leveraging existing database for UID project – a case of Gujarat

Leveraging existing database for UID project – a case of Gujarat

Providing all citizens with an identity card in three or four years is a part of the government's ambitious Unique Identity (UID) programme. For long, national identity cards have been advocated to enhance national security, prevent potential terrorist attacks and stop illegal immigration. This measure is expected to curtail frauds related to the identity of a person, enhance national security etc. Once the project is rolled out, each Indian citizen will have one unique identification number that will identify him/her. While the challenges in UID project are tremendous in terms of technology and scale of implementation, the social and cultural impact can be much larger.
The new agency / authority set up for the purpose will be responsible for maintaining the core database and laying down the procedure of issuance of smart cards, carrying the unique identification number (UID). Initially, the UID number will be assigned to all voters by building on current electoral roll data.

The UID will not only help the government track down individuals ( illegal immigrants), but will make life far easier for citizens as they will not have to submit so many documents each time they want to avail a new service — private or government. The scheme is designed to leverage intensive usage of the UID for multiple purposes. Photographs and biometric data will be added progressively to make the identification foolproof. Easy registration and information change procedures are envisaged for the benefit of the people, especially the poor, who often struggle with issues of identification, house address etc. However, it needs to be cautioned that this project is definitely no panacea to all problems, it will remove ONE major hurdle (problem of identification) if implemented successfully. The UID project is also expected to create 1, 00,000 new jobs in the country and business opportunities worth Rs 6500 crore in the first phase itself. The first phase of the project is likely to cover nine states and 4 Union territories in the country. The following paras suggest a few options that could be endeavoured to ensure smoother implementation of the UID project.

2. Where do they expect to start from?

These are some directions which the Government could plan / is planning on:

1. Using mobile number as UID. The government is planning to rework the current numbering plan along with C-DOT, and is already debating with the telecom regulator on the feasibility of offering 11- and 12-digit numbers can be offered. The only hitch being lack of transparency for the mobile number. The same logic also applies for landline telephony as well.
2. Synchronising unique ID numbers with mobile numbers, which could also serve, as a driving licence number is another option under consideration of the Government. This will entail collating data from different state Governments.
3. Another possibility is to use the databases (42 million) that are available with Employee Provident Fund, besides the Ministry could also offer the database of over 12 million of the Employee State Insurance Corporation (ESIC). The database could cover one segment ie; the salaried class in government jobs. The public Provident Fund could also an option worthy of consideration.
4. NREGS enrolments at the panchayats stated to be close to 65 million people could be option for the agency could effectively leveraged
5. Another state level database with Government is the details of the births registered with Registrars. However, these databases are often stated to be not comprehensive and reliable.
6. Similarly the village level information of land records (with talatis) and details of house tax with corporations / village offices could be data worthy of consideration.
7. The other available options could also suggest accessing Bank Deposit accounts of individuals with the banking system in India, which in many cases could be electronically stored in commercial banks and in RRBs. The database of post office savings account holders could also be accessed.
8. Another option is to leverage the Voter Identification Card, however, this is saddled with issues of many fake / non-genuine Voter IDs
9. Ration Cards and Pension cards issues by employers and Government.
10. The passports issued could be a reliable database that the UID could leverage, which is normally verified and could be digital form.
11. The PAN Cards issued could also be a reliable database that the UID could leverage; however, these are exclusive and very incomplete.
12. Gas connections and Public distribution cards (Ration cards) issued to households could be substantial and could be accessed.
13. Credit Cards issued by banks to its clients could be a sizeable database in digital form, which however, could be predominantly in the urban segment.
14. A similar analogy could be that of KCC issued to farmers by the banking system.

Once the system is in place, a whole lot of the financial and non-financial services could be converged, as listed below:

Finance related Non-financial or service related
1. Social Security
2. Pensions
3. Banking services / savings/ credit products including KCC
4. Insurance
5. Subsidy targeting – food / fertilizers etc (BPL)
6. Remittances
7. Investments – MF / shares / commodities / overseas investments/ bullion
8. Payments – online purchases
9. Payments - NREGS
10. Credit cards / Debit cards /ATM
11. Online trading 1. PAN – income and wealth tax assessment
2. Election / Voter card
3. Driving licence
4. Passport / VISA
5. PDS
6. Child health/ vaccination
7. Mobile/ telephone connections
8. Water connections
9. Electricity connections
10. Internet connections / email ID
11. Gas connections
12. Housing tax / registration
13. Admissions in courses
14. Job applications
15. Entrance / competitive Exams
16. Vehicle registration
17. Land revenue
18. land registrations
19. Death and Birth Registration
20. Asset base / wealth tax, assessments
21. Travel – overseas, ticketing
22. Migration data
23. Company / business/ enterprise registrations

3 How could the Government entice people to obtain an UID?

The biggest enticement as suggested by the Chairman of UIDA Shri Nandan Nilekani is ” enrol once and get an identity for life – this is the biggest USP”. UID being a one-shot hassle free system, you don’t need anything for getting a passport, a licence or exercising your franchise. Well all this sounds good for an urbanite, however, the rural masses and particularly the illiterate poor will may have to be enticed, the option on hand perhaps is to tempt them with what they generally look for / what they seek for …for eg kerosene (fuel), or a smokeless chula, a gas connection food, government subventions, pensions etc. One way of enticing rural masses to enrol for UID is ensure those who register (Take a UID) gets a special treatment
1. Ensuring quick release of payments due to them if they have a UID, ie; like NREGA/ pension / subsidy etc.
2. Subsidy related schemes (SGSY), make it mandatory to get an UID
3. Schemes like smokeless Chula – for registered candidates only.
4. Tree Patta / land patta to landless - only for registered candidates
5. Additional kerosene ( 1 lt) for registered candidates only.
6. Additional ration of wheat / rice ( 2 kgs ) or such commodities at less than normal rates in a PDS system(subsidised rates).
7. Fertilizers (NPK) at discounted rates – discounted coupons
8. Another option to entice could be to incentive the individual who normally could be responsible for delivery of services to a group of people in a limited geographical hinterland or a village. This could interalia involve to three major functionaries whom the government generally involve in many governmental tasks ie; 1) anganwadi worker for women and child related tasks in a village 2) post man who normally has a significant understanding of the local area and its people with the regular contacts 3) this could include the teachers in rural governmental schools, which has regular in its operations and significant enrolments.
9. Yet another option could be to entice a entire community or say a integrated unit like a village. Ie; Villages where all members are registered – gets an approach road completed in 6 months or a telephone connection or a farm pond is de-silted with government support.
10. Other option could be to ensure that, early registration of all villagers in a village fetches a quick release of funds to the panchayat from Zilla authorities without any hassles.
11. Yet another option could be to entice with non-monetary incentives- early registration of all villagers in a village fetches a merit certificate from the Tehsildar or a monetary reward like Rs 10,000/ - ( or say 50 % cost to be met by GOI for any development work initiated and completed in one year by the villagers in their village).

4 Gujarat initiatives:

Besides the option listed above, Gujarat has two unique efforts which also throw-up some lessons and also possibilities for leveraging an existing a data base that is comprehensive and reliable. The initiatives are Viz; the socio-economic survey of rural households which the government has attempted as an all inclusive data base 2) A few coastal villages (like valsad District) have initiated an effort at issuing ID cards to all villagers as an effort at Gram surekasha. While the latter was a limited initiative of select gram panachayats, to stop incursions and know your co-villagers concept, the former is a comprehensive list of all households and its socio-economic characteristics in the rural hinterlands of Gujarat state. A few details of the same is given in the following paras:

The socio-economic survey done by GoG in 2002 was initiated at the behest of the Ministry of Rural Development, Government of India, to prepare the list of all households in the rural hinterlands and categorised based on 13 socio-economic parameters. However, the Gujarat Government at its command added a three more parameters for undertaking the socio-economic survey. The parameters were:
1. Size group of operational holding of land
2. Type of house
3. Average availability of normal wear clothing (per person in pieces)
4. Food Security
5. Sanitation
6. Ownership of consumer * durables : Do you own
7. Literacy status of the highest literate adult
8. Status of the Household Labour Force
9. Means of livelihood
10. Status of children (5-14 years)
11. Type of indebtedness
12. Reason for migration from household
13. Preference of Assistance
14. Head lady a widow
15. Family lady dependent
16. Family member handicapped

Thus, the uniqueness of the initiative of GOG (Commissioner of Rural Development, Government of Gujarat) has been that a) Though the survey was to be conducted based on 13 different parameters as specified by GoI, it was further expanded to cover more crucial elements in the list ( Sl no 14-16 listed above) 2) the entire exercise has been done with the help of enumerators ( school teachers ) in a short period as a socio-economic survey and not as a BPL survey which is normally the approach adopted in other states 3) the data has been captured at the field level in a codified 1-page alpha-numerical format 4) the entire data sheets were scanned so to capture the same in soft form using Intelligent Character Recognition technology, thus obviating the issues of data re-entry errors and ensuring achieve maximum accuracy 5) the data has been uploaded on website of the department allowing people to report mistakes if any in data collection and compilation , thus ensuring transparency.

Department had a series of training programmes for the associated staff to explain about the filling up the forms to have maximum accuracy. Various parameters were also coded to have minimum errors while filling up the forms. All (68 lakh) rural households data collected at the field level were captured by scanning of field schedules and data was converted into soft form. For each parameter the households were further categorised as follows:

Sr. No. Characteristic Scores: 0 to 4 (Code)
0 (A1) 1 (B2) 2 (C3) 3 (D4) 4 (E5)
1 Size group of operational holding of land Nil Less than 1 ha. of un-irrigated land (or less than 0.5 ha. of irrigated land) 1 ha.-2 ha. of un-irrigated land (or 0.5- ha. of irrigated land) 2 ha. -5 ha. of un-irrigated land (or 1.0-2.5 ha. of irrigated land) More than 5 ha. of un-irrigated land (or 2.5-ha. of irrigated land)
2 Type of house Houseless Kutcha Semi-pucca pucca Urban type
3 Average availability of normal wear clothing (per person in pieces) Less than 2 2 or more, but less than 4 4 or more, but less than 6 6 or more, but less than 10 10 or more
4 Food Security Less than one square meal per day for major part of the year Normally, one square meal per day, but less than one square meal occasionally One square meal per day throughout the year Two square meals per day, with occasional shortage Enough food throughout the year
5 Sanitation Open defecation Group latrine with irregular water supply Group latrine with regular water supply clean group latrine with regular water supply and regular sweeper Private latrine
6 Ownership of consumer * durables : Do you own Nil Any One Two items only Any three or all items All items and/or Ownership of any one **
7 Literacy status of the highest literate adult Illiterate Upto primary (Class V) Completed secondary (Passed Class X) Graduate / Professional Diploma Post Graduate/Professional Graduate
8 Status of the Household Labour Force Bonded Labour Female & Child Labour Only adult females & no child labour Adults males only Others
9 Means of livelihood Casual labour Subsistence Cultivation Artisan Salary Others
10 Status of children (5-14 years) [any child] Not going to School@ and working Going to School@ and working Going to School@ and NOT working
11 Type of indebtedness For daily consumption purposes from informal sources For production purpose from informal sources For other purpose from informal sources Borrowing only from Institutional Agencies No indebtedness and possess assets
12 Reason for migration from household Casual work Seasonal Employment Other forms of livelihood Non-migrant Other purposes
13 Preference of Assistance Wages Employment Self Employment Training and Skill Upgradation Housing Loan / Subsidy more than Rs. one lakhs or no assistance

14 Head lady a widow

Three parameters added by the GoG
15 Family lady dependent
16 Family member handicapped

10 % of the data so collected were subjected to checks by DRDA staff to ensure its correctness. Based on the scoring patterns (the scores could vary between 0-52 for each household) the households were grouped into separate segments. Households with a scoring pattern 0-16 where classified as very poor household and those with 17-20 were classified as poor households. The entire set of data has been uploaded / stored on the website and also displayed at government offices. The data could be accessed from the webpage Another uniqueness of the data storage has been the query mode, which enables greater transparency and facilitates anyone to check the correctness of the data complied. Grievances if any addressed to ensure that the information is not static one. The state Government had envisaged to use this set of rural household data for targeting households for all its social sector programmes, be it for housing, poverty related or microFinance or any other programme of the Government.

While its unlikely that the UIDA will access the existing data even though it’s a comprehensive one, as in the instant case, however, the agency could use such comprehensive information for any crosscheck exercise that it may endeavour.

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Works at NABARD for poor HH / was Research Affiliate at CDS, Tvm / was Visiting Faculty on microFinance for MBA students NMIMS, Mumbai.