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Pension Tension

Aadhaar and Social Assistance in Jharkhand

Rishabh Malhotra (rriishabh@gmail.com) and Anmol Somanchi (anmol.somanchi94@gmail.com) are independent researchers based in New Delhi, currently associated with Nomura Research Institute Consulting and Solutions and IDinsight respectively.

The Jharkhand government has made Aadhaar mandatory for social security pensions. It is claimed that this has resulted in the deletion of three lakh “fake” pensioners in 2016–17. A recent household survey in Khunti town, however, reveals that fakes and duplicates make up only a fraction of the deleted pensioners, and a very small proportion of all pensions. Instead, many genuine pensioners have been excluded
in the process.

The authors would like to thank Jean Drèze and Reetika Khera for their guidance and helpful discussions; members of the NREGA Sahayata Kendra in Khunti district of Jharkhand, Nazar Khalid, and all the student volunteers that participated in the survey; Inayat Sabhikhi for sharing information from an RTI query; Varun Gupta for useful discussions; and the local administration in Khunti for sharing data and providing clarifications. The opinions expressed here are personal.

Mangri Pahanain is an 85-year-old widow from Pahan Toli in Khunti town, Jharkhand. Frail, infirm, and severely hunched, she lives in a small hutment with her 60-year-old disabled son who walks with crutches. Mangri is so weak that she is barely able to speak. Her son explains that until recently she used to receive her monthly old-age pension of ₹600, which she critically depended on. However, since October 2016, the pension payments have stopped. Mangri’s only hope now is the benevolence of her family.

The elderly, widows, and disabled persons in Jharkhand often live a life plagued with uncertainty. They tend to have few employment opportunities (due to old age, illness or social restrictions) and limited family support. For many like Mangri, non-contributory pensions under the National Social Assistance Programme (NSAP) are a critical source of security and dignity.

While non-contributory pension schemes in India face significant implementation issues, including a complicated selection process and irregular payments, recent research indicates that they are performing well in crucial respects. The schemes are targeted progressively (Dutta et al 2010), raise expenditures and lower poverty (Kaushal 2014), and importantly, are highly valued by their recipients (Chopra and Pudussery 2014). Further, there is little evidence of a pressing problem of identity fraud (Drèze and Khera 2017).

In Jharkhand, the government has recently made Aadhaar compulsory for social security pensions. This means that pensioners must have an Aadhaar number, get it “seeded” in the pensions database and link it to their bank account (we shall refer to this entire process as “Aadhaar seeding”). It is claimed that “the use of technologies like Aadhaar are revolutionising the delivery of services” (Panda 2018).1 In Jharkhand, however, pensions have been transferred directly to bank accounts for some time, and the value addition from Aadhaar is questionable.2 Instead, recent ground reports suggest that Aadhaar seeding has created serious exclusion problems (Sen 2017; Kumar 2017; Biswas 2017; Bhatnagar 2018).

In September 2017, the Jharkhand government claimed that Aadhaar seeding had resulted in the deletion of close to three lakh “fake” pensioners in 2016–17, leading to savings of ₹200 crore (Press Trust of India 2017). This claim, widely relayed in the media, has been cited as evidence of the revolutionary capability of Aadhaar in welfare provision.

In December 2017, we conducted a survey in Khunti town (Khunti district) to verify some of these deletions. This article presents the findings.

Social Security Pensions

The NSAP was launched as a centrally funded scheme in 1995 to provide social assistance to the destitute. Over time, it has seen a series of revisions relating, for instance, to coverage, eligibility, implementing agencies, and pension amounts. Currently, the NSAP broadly covers three schemes: the Indira Gandhi National Old Age Pension Scheme (IGNOAPS), the Indira Gandhi National Widow Pension Scheme (IGNWPS), and the Indira Gandhi National Disability Pension Scheme (IGNDPS).3 The NSAP reaches more than 30 million4 persons across India and in 2016–17 (Government of India 2018), the central government spent around 0.06% of India’s gross domestic product on it (Drèze and Khera 2017).

The central government’s contributions to monthly pensions under the NSAP have remained stingy and stagnant for over a decade now (for instance, ₹200 per month for old-age pensions). The Jharkhand government, however, has supplemented them and also expanded the coverage of social security pensions with additional state-sponsored schemes. Table 1 presents an overview. Supplementary contributions by the state government have equalised pension amounts across schemes at ₹600 per month (raised to ₹700, in the case of old-age pensions, for those above 80 years). The age and income-related eligibility criteria for these schemes are presented in Table 1.

Exaggerated Hope of Aadhaar

The efficiency gains to be made from Aadhaar must be examined in relation to the levels of leakages and its sources. Leakages in pensions tend to be of three broad categories:5 (i) “quantity fraud” when pensioners do not receive their full pension amounts or must pay bribes; (ii) “eligibility fraud” when ineligible persons receive pensions; and (iii) “identity fraud” when “fake” or duplicate pensioners receive pensions. Aadhaar is generally toothless in tackling quantity or eligibility fraud. Its potential benefits are restricted to plugging identity fraud.

While research on pensions in Jharkhand has been limited, some broad patterns related to leakages emerge from a few recent, small-scale studies based on comparable methodologies. Notably, they suggest that identity fraud is very low. For instance, Aashish Gupta (2013) and Sambhavna Biswas (2017) found no fakes in a sample of pension lists in Latehar and Ranchi districts respectively. Similarly, the 2013 survey discussed in Drèze and Khera (2017), and Chopra and Pudussery (2014), covering eight randomly selected villages in Jharkhand, suggests “fakes” amount to at most 1%.6 A more important concern is that many pensioners in Jharkhand are affected by delayed and erratic pension payments, or have to pay a monthly bribe. Based on a survey in Khunti block in Khunti district, Marulasiddappa et al (2014) found 72% of pensioners reporting no clear pattern for their pension payments. Chopra and Pudussery (2014) found almost 50% of pensioners paying a monthly bribe.

Given this pattern of leakages, the imposition of Aadhaar seems to be based on a lack of understanding of the nature of corruption in pension schemes. It may also lead to a “displacement effect” (Khera 2017) brought about by the single-minded focus of the administration on Aadhaar (and implicitly on identity fraud), resulting in a neglect of urgent issues like bringing transparency in the selection process, checking bribes, and ensuring timely payments.

The Survey

As noted earlier, the Jharkhand government claims that Aadhaar seeding led to the deletion of three lakh fake names from pension lists in 2016–17. The government, however, has refused to release the list of deleted pensions, making it difficult to verify them.

The local administration in Khunti was kind enough to provide us with a list (henceforth, the “official list”) of all the names deleted from the pensioners’ list in Khunti town during the financial year 2016–17. Against each name, the official list mentions the relevant pension scheme and the reason for deletion (henceforth, the official reasons). There were 103 deletions, spread across 22 wards of Khunti town. In December 2017, with the help of the NREGA Sahayata Kendra in Khunti and student volunteers, we conducted a survey to verify these deletions and also to understand when and why pensions had been cancelled. We used the help of local residents, and knowledgeable citizens like ward members and anganwadi workers to locate the concerned pensioners. Wherever possible, we verified their bank passbooks.

Of the 22 wards with deletions, we selected those with three or more deletions, leaving us with 90 deletions (henceforth, the sample) across 13 wards (henceforth, the sample wards). Table 2 presents the scheme-wise breakdown of the sample, based on the official list. About three quarters of the deletions pertained to old-age pensioners, 22% to widow pensioners, and 2% to disability pensioners. Women accounted for about 75% of the deleted names.

The percentage distribution of official reasons for deletion is presented in Table 3. Two of the three reasons, “death” and “duplicate,” are self-explanatory and accounted for 16% of the sample. A third reason, vaguely worded as “discontinue,” accounted for the remaining 84%. Preliminary discussions with the local administration revealed that “discontinue” was a code for failed Aadhaar seeding.

 

Main Findings

Early into the survey, a clear pattern emerged: many respondents reported that they used to receive a pension, but the payments stopped after October 2016. It seems that from then on, the local administration in Khunti (and perhaps elsewhere in Jharkhand as well) stopped paying pensions to those who had not seeded their Aadhaar numbers. This was later confirmed by concerned officials at the district level. The survey revealed that, contrary to what the government had claimed in September 2017, many of these pensioners were alive and eligible, and had been unfairly deprived of their pensions.

Table 4 presents the reasons for deletion as ascertained from the field survey. While Aadhaar seeding was successful in identifying cases of identity fraud (which we found to be limited in extent), 35% of the deletions were cases of genuine pensioners who were victims of failed or faulty Aadhaar seeding, for no fault of their own. They were left to knock on the doors of various government and bank offices, begging for assistance to get their pensions resumed. Some have succeeded, some are still trying while others have given up hope.

Table 5 presents a cross-tabulation of the official reasons for deletion and those from the survey. The government, it seems, discontinued Aadhaar-less pensions without ascertaining the reasons for lack of Aadhaar seeding. As noted earlier, these were the cases classified as “discontinue” in the official list and made up 84% of the sample. Close to 40% of the discontinuation cases applied to persons who were alive and eligible but were victims of failed or faulty Aadhaar seeding.

Identity Fraud and Irregularities

Identity fraud in pensions is mainly of two types: (i) “duplicates” where two pensions are paid to the same person, and (ii) “fakes” where pension is drawn in the name of someone who does not exist.

Identifying duplicates in a household survey can be difficult because it is unlikely that anyone would self-report duplication. However, about 7% of the respondents reported no disruption in their pensions at all. It is quite likely that these were cases where a duplicate was detected—this was confirmed by the fact that almost all these cases were classified as “duplicates” on the official list. This does not necessarily mean, however, that fraud was involved (most of the respondents looked so helpless and powerless that it is hard to imagine them trying to trick the administration at the risk of losing their meagre pension altogether). More likely, some duplication happened because people repeat their pension application after waiting in vain for a response to the first one. What is not clear is whether any of the respondents actually ever received double payments, whether due to fraud or record-keeping problems.

About 20% of the sample included cases where the pensioner could not be traced and were not known to local residents. These could possibly be cases of “fakes.”7 However, almost half of these cases were from a single ward (“Khunti”) in the heart of the town. Locating persons in a crowded urban area with no further information than their names and wards (in particular, no address) can be extremely difficult. We also found some misclassification of wards: a few pensioners were found in a ward adjacent to the one they were supposed to live in as per the official list.8

Nonetheless, an upper bound on identity fraud can be worked out by considering all untraceable persons as fake, and all those who reported no pension disruption as duplicates and comparing these numbers with the total number of pensions in the sample wards. This would imply that about 2% of all pensions were fake and 1% duplicates, at most.9,10 This is consistent with earlier findings suggesting low levels of identity fraud in pension schemes.

As Reetika Khera (2017) notes, irregularities in updating administrative records, for example, to record cases of death or migration, create scope for leakages. In the case of deaths, for example, pensions continue to be deposited into the bank account until the family attempts to claim the balance and close the account. In principle, these leakages should be temporary, as the banks are supposed to revert excess payments at that time, based on the date of the death certificate. However, it is not clear to what extent this practice is followed.

The survey suggests that Aadhaar seeding was used as a one-off opportunity to weed out cases of death and migration, amounting to 19% and 3% of the deletions respectively (Table 4). This was possible because dead persons and migrants were not available to submit their Aadhaar numbers for seeding. From then on, however, the role of Aadhaar seeding is likely to be limited to preventing the entry of duplicates and fakes on pension lists. After the initial seeding exercise is complete, Aadhaar seeding on its own does not particularly help to identify pensioners who die or migrate.11 Discussions with the local administration indicate that such cases are usually identified through periodic surveys. Indeed, some in our sample (listed in the “death” category in Table 3) were discovered in that way.

Exclusion and Disruptions

While Aadhaar seeding can perhaps be credited with plugging some identity fraud, the process has led to the exclusion of many pensioners. Moreover, the technology-intensive system does not identify these exclusions.

Close to a fifth of the sample reported not receiving their pensions for even a single month after the Aadhaar imposition, that is, since October 2016. All of them possessed an Aadhaar number but they had failed to seed it before the deadline. While there can be numerous reasons for this, a few deserve highlighting. Many reported being unaware of the new mandate regarding Aadhaar and learning of it only when bank officials informed them that their pensions had been discontinued. With limited family support, many subsequently made multiple trips to the block office and bank to submit their Aadhaar details, but their pensions have still not resumed. Faulty or incorrect Aadhaar seeding was another problem that we encountered. To illustrate, Aamna Khatun, a 70-year-old woman who lives in the heart of Khunti town, stopped receiving her pension in October 2016. Enquiries at the bank revealed that the last digit of her Aadhaar number was incorrectly entered during the manual seeding process. Another respondent was told by bank officials that her pension had been discontinued because her name in the Aadhaar database did not match the bank records.

Due to budget constraints, there are fixed quotas for the total number of pensioners in each block. Eligible applicants are often put on a waiting list until a vacancy opens (for instance, after a pensioner dies).12 Discussions with the local administration suggest that some of the discontinued pensions were replaced with new pensioners from the waiting list. As a result, even after submitting their Aadhaar details, excluded pensioners find themselves back on the waiting list and must now wait helplessly for their pensions to resume.

By the time of the survey (December 2017), it had been about 14 months since these persons received any pensions. By then, they had been deprived of about ₹8,000 each, not a small sum by any means for these vulnerable and disadvantaged persons. Three quarters of these cases were old-age pensioners.

About 17% of the sample reported disruption in payments for some (not all) months between October 2016 and November 2017, because of failed or faulty Aadhaar seeding. Upon realising that their pensions were not being deposited in their accounts, they made several trips to the bank and block office, which fortunately resulted in their pensions resuming. However, they were deprived of eight months of pensions (close to ₹5,000) on average. Verification of passbooks confirms that these “arrears” have not been paid.

Conclusions

The experience of pensioners in Khunti town helps to understand as to what happened when Aadhaar was made compulsory for pensions in Jharkhand. The exercise has been coercive and high-handed. A deadline for Aadhaar seeding was fixed and those who failed to comply were deemed “fake” and deleted from pension lists. Subsequently, these aged, widowed, and disabled pensioners have been left in a Kafkaesque bureaucratic limbo to prove their existence. Besides the monetary costs involved, this has caused a lot of physical and mental strain to many of them.

The findings also raise questions about the potential and impact of Aadhaar as a policy tool to enhance efficiency. Contrary to the government claims, fakes and duplicates were found to make up only a fraction of deleted pensions (28% as an upper bound), and 3%, at the most, of all pensions in the sample wards. Aadhaar imposition has instead led to significant exclusion and disruption, where 35% of the deletions, that is, about 3% of pensions in the sample wards, were found to be genuine pensioners who reported failed or faulty Aadhaar seeding. Contrary to the claims of empowerment, Aadhaar imposition has meant increased hardships for many.

The Jharkhand government seems disconnected from the real-world implications of making Aadhaar compulsory for social security pensions. It is particularly worrying that the government does not even acknowledge the resulting exclusions. Worse, the expenditure reductions resulting from these exclusions are projected as valuable Aadhaar-enabled savings. In reality, poor information dissemination, coercive deadlines, increased hurdles, and limited grievance redressal have left pensioners in a state of heightened vulnerability. Many of them are paying the price for obsessive and misguided attempts to eradicate “identity fraud” where it hardly exists.

Postscript

As it turns out, the Jharkhand government’s own data suggests that “identity fraud” in pension schemes is very limited. After publication in the media, of the government’s claim regarding deletion of three lakh “fake” pensioners, a right to information (RTI) application was filed by Sabhikhi (in September 2017) requesting the breakdown of reasons for deletions. A full breakdown of the reasons has been received for three districts (Sahibganj, Bokaro and Palamu) so far.13 In all three, no “fakes” have been reported, and duplicates amount to 0.14%, 0.003%, and 0.4% of all pensions in the respective districts (data provided by the local administration for Khunti district suggest similar trends). As in Khunti, a large proportion of the deletions (30% to 70%) in these districts are classified as “discontinue.” The Khunti findings suggest that many of these are cases of exclusion due to failed or faulty Aadhaar seeding.

Notes

1 Similar views are expressed by Ajay Bhushan Pandey (2018).

2 This was being done via the National Electronic Funds Transfer payment system.

3 Two other schemes, the National Family Benefit Scheme and the Annapurna Scheme, are also part of the programme, but are in the process of being phased out.

4 NSAP website (nsap.nic.in).

5 For more on this, see Khera (2017).

6 The authors note that 93% of those on Jharkhand’s pension lists were alive and receiving pensions (Drèze and Khera 2017) and 6% were alive but not receiving pensions (Chopra and Pudussery 2014). This leaves about 1% as possible fakes.

7 Given that, in Jharkhand, pensions are paid directly into bank accounts, it is not easy for corrupt officials to introduce “fakes” in the pension lists. This would require the collusion of bank staff to open a bank account in the name of a fictitious person and then withdraw the pensions deposited in it.

8 It is possible that some of them had been deleted from the pension list precisely because they had been mislocated and thus eluded the official verification drives.

9 Data on the total pensions at the ward-level on the NSAP website are available only for the current month. For January 2018, the total was 906. To estimate identity fraud, we can take two extreme cases of what may have happened between October 2016 (when the deletions happened) and January 2018: (i) no new pensions were added, implying the total pensioners in October 2016 to be roughly equal to the total in January 2018 plus the total number of deletions (90); (ii) new pensioners, equal in number to the deletions, were added, implying that the total in October 2016 would be similar to the total in January 2018. The latter seems more likely, given the practice of abiding by the “ceiling” on total pension numbers (discussed further in the text). The estimates, however, do not vary much—“fakes” and “duplicates” amount to 1.9% and 0.6% respectively in the first case and 2.1% and 0.7% respectively in the second.

10 We have, however, not heard of any action taken anywhere against any of the guilty responsible for such fraud.

11 It might help if, say, Aadhaar-based biometric authentication is made compulsory for pension payments. That, however, would be very unfair, considering that biometric authentication failures are common for the elderly.

12 Based on the 2011 census data, Inayat Sabhikhi (2017) estimates that around 45% of all persons eligible for a pension in Jharkhand are excluded in this manner.

13 For the rest, either responses are yet to be received, or only incomplete information has been received.

References

Bhatnagar, Gaurav Vivek (2018): “Aadhaar Glitch: Another Woman Dies of Hunger in Jharkhand after Being Denied Ration, Say Activists,” Wire, 2 February, https://goo.gl/Y2Qp8d.

Biswas, Sambhavna (2017): “Struggles of Pensioners in Jharkhand,” Economic & Political Weekly, Vol 52, No 52, pp 39–43.

Chopra, Saloni and Jessica Pudussery (2014): “Social Security Pensions in India: An Assessment,” Economic & Political Weekly, Vol 49, No 19, pp 68–74.

Drèze, Jean and Reetika Khera (2017): “Recent Social Security Initiatives in India,” World Development, Vol 98, pp 555–72.

Dutta, Pooja, Stephen Howes and Rinku Murgai (2010): “Small but Effective: India’s Targeted Unconditional Cash Transfer,” Economic &
Political Weekly,
Vol 45, No 52, pp 63–70.

Government of India (2018): “Dashboard wrt Data Digitized–NSAP Scheme,” NSAP, Ministry of Rural Development, Government of India, 24 August, http://nsap.nic.in/.

Government of Jharkhand (2018): “Applications for Various Kinds of Social Security Pension—Eligibility,” Jharkhand Rajya Seva Dene ki Guarantee Adhiniyam, Government of Jharkhand, http://jhr2.nic.in/rtgs/service_details.aspx?a=Af7AbsOpDdO8%2Bf1zqiIEKwLQD%2BvSJ4gZbp38jGgjX6KWFPUfiF4U1I4gAIDXoTUB.

Gupta, Aashish (2013): “Old-age Pension Scheme in Jharkhand and Chattisgarh,” Economic & Political Weekly, Vol 48, No 34, pp 54–59.

India Today (2016): “Widow Pension Scheme to Cover 18-yrs and Above: Minister,” 23 February, https://www.indiatoday.in/pti-feed/story/widow-pension-scheme-to-cover-18-yrs-and-above-minister-561044-2016-02-23.

Kaushal, Neeraj (2014): “How Public Pension Affects Elderly Labor Supply and Well-being: Evidence from India,” World Development, Vol 56, pp 214–25.

Khera, Reetika (2017): “Impact of Aadhaar on Welfare Programmes,” Economic & Political Weekly, Vol 52, No 50, pp 61–70.

Kumar, Raj (2017): “From Pillar to Post for Rs 600 Pension,” Telegraph, 29 December, https://goo.gl/4CgzwV.

Marulasiddappa, Manisha, Pallavi Raonka and Inayat Sabhikhi (2014): “Social Security Pensions for Widows and the Elderly,” Indian Journal of Human Development, Vol 8, No 1, pp 49–63.

Panda, Baijayant “Jay” (2018): “Can ModiCare work? Critics Doubt Its Funding but a Sharp, Counterintuitive Strategy May Ensure Funds,” Times of India, https://goo.gl/smeLBD.

Pandey, Ajay Bhushan (2018): “Aadhaar, the Most Trusted ID, Empowers People,” LiveMint, 31 January, https://goo.gl/5Pszu9.

Press Trust of India (2017): “Saved Rs 200 Crore by Linking Aadhaar to Pension Schemes, Says Jharkhand Government,” NDTV, https://goo.gl/CBC9Ar.

Sabhikhi, Inayat (2017): “Jharkhand Shows Why Old Age Pension Scheme Needs Legal Framework,” Wire, 23 March, https://goo.gl/gqJtdi.

Sen, Jahnavi (2017): “In Rural Jharkhand, Aadhaar Link to Welfare Schemes Is Excluding the Most Needy,” Wire, 18 July, https://goo.gl/HM4xmm.

Updated On : 7th Sep, 2018

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