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The complex architecture of DBT transactions is resulting in failures

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By: Srinivas Kodali


Technology failing is a universal fact, anyone claiming machines do not have errors is usually saying that to sell a machine to you. Aadhaar is no exception, it is not a mythical system that somehow will function without any error. UIDAI itself publishes around 95 types of errors with the Aadhaar authentication system on its website. Everything from biometrics not matching to, duplicate iris,, invalid Aadhaar number to even an unknown error with the code “999” are mentioned. While these have been defined in UIDAI’s own documents, there is not enough information otherwise on statistics of failures and what happens during a failure of authentication. Further, the UIDAI has always argued their failure rates are very minimal, without ever supplying any actual data. 

    The errors are not limited to UIDAI in the ecosystem, since Direct Benefit Transfer (DBT) involves multiple entities and departments. The first step in electronic delivery of subsidy is Aadhaar – and an error there can halt everything. The second phase of errors that are quite often seen are the with the Point of Sale (POS) machines not functioning properly. A Department of Fertilisers DBT manual shows how their Point of Sale systems have potential problems related to battery, software, and network issues. If everything works in these two stages of authenticating oneself at the PoS machines, with the Aadhaar gods also in favour, the table then belongs in the court of banks. 

    Banking systems are not straightforward in transactions where money is  transferred from the consolidated fund of India to the bank account of an individual beneficiary. The Aadhaar based DBT architecture created additional layers than had previously existed. DBT using NEFT has one middle layer between banks at RBI, whereas otherwise, the middle layer is at National Payments Corporation of India (NPCI) as they are clearing house. However with Aadhaar, an extra layer was introduced where NPCI was required to create an NPCI-Aadhaar mapper in order to facilitate the transfer of funds. This mapper is the backbone of Aadhaar Payments Bridge (APB) and Aadhaar-enabledPayment System (AePS). The Aadhaar Payments Bridge Manual records that the NPCI-Aadhaar mapper has 20 odd error codes. Withdrawing the DBT money using AePS is not straightforward either with around 200 errors as mentioned in an NPCI circular. There are more errors in the National Automated Clearing House when transactions fail and the amount is returned back. The standardization of error codes is not yet complete, and we don’t know the various numbers or types of  sub-errors.

    In all,the different permutations of errors that can result in failures of DBT is unknown and it won’t be easy to map this out for an outsider with the number of blackbox institutions involved. The Reserve Bank of India, which collects large scale data on payments within the country won’t tell us what is happening in general payments failure rates. These systems are complex and are blackboxes by design. A typical error every beneficiary is facing is with regard to the bank account to which their funds are being credited. This issue became apparent when DBT money started getting credited into Airtel payments bank accounts created without the knowledge and consent of over 31 crore individuals. NPCI and UIDAI had to scramble to fix a design problem with the NPCI-Aadhaar mapper by bringing in ‘offline consent’ into their architecture. The fragility of these banking systems got exposed with the Airtel payments banks case. 

With all of these error codes, it becomes important to look at DBT failures as a whole and attempt to rectify them. The DBT mission is tasked with ensuring these errors do not result in failure of payments to beneficiaries. Though, one doesn’t know what the mission is doing on the ground with their office strength being just 5 members. Regardless, the mission actively demands various institutions to share DBT – 09 reports which include failure details of every transaction at individual level. This data is unfortunately not public, while one can file a Right to Information request to obtain this information per scheme. 

While the DBT 09 failure data is not in the public domain, the DBT mission studied the data from the Public Financial Management System (PFMS) which is used to manage DBT transactions. The raw data from PFMS from 1st November to 13th December in 2018 was analysed, and involved 6.85 crore transactions. According to the mission, 0.91% transactions (i.e. 6.2 lakh) resulted in failures. A further analysis of these 6.2 lakh failures showed that 17,375 transactions (2.9%) were due to payment limits on small accounts; or accounts being inoperative/inactive/dormant, pending verification of KYC. 52,529 transactions had an unknown error code of “R11” being returned by the RBI. 

The summary of the data analysis gives us the following sub issues encountered with DBT failures:

  1. 53,270 (8.6%) transactions of 6.2 lakhs failures were because of accounts being blocked by banks.
  2. 52,529 (8.5%) transactions of 6.2 lakhs failures were because of unknown error of R11 in NEFT.
  3. 15,505 (2.5%) transactions of 6.2 lakhs failures were because of limits on small accounts
  4. 1554 (0.3%) transactions of 6.2 lakhs failures were because of inoperative/dormant accounts.
  5. 316 (0.1%) transactions of 6.2 lakhs failures were because of first transactions pending by account holders
  6. 271 (0.1%) transactions of 6.2 lakhs failures were because of KYC pending
  7. 6 0.0% transactions of 6.2 lakhs failures did not have a return code for credit transactions 
  8. 4,97,593 (80.2%) transactions of 6.2 lakhs failures were because of other issues not listed above. The statistical details of these error codes were not available in concerned files inspected under RTI.

But with the errors in this complex ecosystem causing failures, the department of financial services identified 12 types of failures for DBT payments that could be fixed. DBT Mission asked banks to follow the NPCI’s Standard Operating Procedure on Aadhaar Payments Bridge to eliminate 6 types of errors. These errors include i) Aadhaar number not mapped to the Account number ii) Account closed/transferred. iii) Account Holder expired. iv) Invalid Account v) Account under litigation and vi) Documents pending for Account holder turning major

The banks were also asked to follow the instructions from RBI, NPCI and the Department of Financial Services to fix the 6 other types of DBT return failures. These 6 are i) Account reached maximum credit limit set on account by bank ii)Amount exceeds limit set on Account by Bank for Credit per Transaction iii) Customer to refer to branch iv) Dormant Account v) Account inoperative and vi) Network failure. Explaining these errors to the normal public is nearly impossible when all institutions claim that there are no problems with their systems and processes. Further, holding any one particular institution responsible for a DBT failure transaction is near impossible when we don’t know at which exact stage the transactions failed. 

While the exact errors are unknown to the public, the data for this exists in part of the DBT portal and is available with every ministry. The PFMS portal with Controller General of Accounts has the raw data for all DBT transactions, and is the institution tasked with carrying out subsidy delivery. The lack of this information in public domain is concerning and directly effects beneficiaries who are unable to receive benefits. RTI requests filed with ministries have so far resulted in some information being shared. This information is being gathered and archived for public consumption. 

An analysis of DBT 09 statistical data for years 2017-18 and 2018-19 of National Rural Health Mission obtained under RTI gives us the following insights.

  1. Out of 1,82,76,676 DBT transactions in 2017-18, 9,76,487 transactions have failed. Of these transactions 51,73,674 DBT transactions were Aadhaar based transactions and 2,45,298 transactions were failures. 1,31,03,002 DBT transactions were non-Aadhaar based DBT and 7,31,189 transactions were failures. 
  2. Out of 2,19,16,789 DBT transactions in 2018-19, 18,07,862 transactions have failed. Of these transactions 58,60,495 DBT transactions were Aadhaar based transactions and 4,39,109 transactions were failures. 1,60,56,294 DBT transactions were non-Aadhaar based DBT and 13,68,753 transactions were failures. 

    The number of DBT failures due to non-Aadhaar transactions is equally as high as Aadhaar based transactions. With a lack of information about how non-Aadhaar DBT transactions are carried out, no comment on its architecture is being made, apart from it being bad too. It is unfortunate that the statistical data does not tell us exactly who is not receiving their benefits, but the ministries and other departments have this information. Even with all the information, the errors in DBT transactions could mean that people are starving, suffering because of poor healthcare, or even dying. No amount of technology or data can stop that, we must audit these systems to make them accountable to the people. The current mechanisms  have been reduced to a black-box full of errors.

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