Data integration would further strengthen the benefit delivery system

The mismatch between the targeted beneficiaries and those who receive the benefits provided by governments is well known. The government in question faces five major challenges. First, it is difficult for it to estimate how much it should budget for each program because it does not have reliable data on the number of eligible citizens.

Secondly, citizens find it difficult to know at all times which schemes they are entitled to and which they can benefit from. Third, even with access to such information, it would be an overstatement to expect vulnerable sections of society to be aware of the processes needed to obtain the benefits intended for them. Fourth, obtaining documents, travel to submit applications, etc., entails costs that potential beneficiaries may not be able to afford. Thus, they end up having to spend a substantial part of the profits in the process itself. Five understaffed departments are struggling to reach intended program beneficiaries and deliver benefits to them.

But if a government already had significant data on citizens in vulnerable sections of society, why can’t it provide benefits on a suo motu basis? Why should there be a need for citizens to constantly apply, spend money to apply, and follow up with a multitude of departments? Why can’t the government identify the needy and disburse benefits directly to their bank accounts using Aadhaar as a financial address, without compromising privacy and data protection principles? These are questions that the government of Karnataka asked itself before implementing these principles about three years ago.

To start, the government of Karnataka has created a virtual federated social registry, Kutumba, which continuously extracts citizens’ eligibility data from various government databases in all departments to identify those who need government support. ‘State. This also contributes to achieving transparent and corruption-free governance. Each citizen data point is “owned” by a single source within the department so there is no data conflict.

For example, the caste details of citizens are taken from the IRS database. This allows the government to leverage the list of people and families who need government support, using data science, and helps them better design and budget schemes, all within the framework of the section 4(4)(b)(ii) ) of the Aadhaar Law. Individual and family attributes are securely stored and used to effectively deliver benefits to citizens from taxpayer dollars in a fair and transparent manner.

However, creating such a social register of Kutumba and using it suo motu to create a list of eligible citizens is only part of the solution. With limited budgets, the state may have to prioritize eligible citizens who can receive benefits within the budget. Thus, the priority of eligible citizens’ needs must be assessed. This is done by the Suvidha system which calculates their “need score” and prioritizes providing benefits to those with a higher need score.

Suvidha is a fully automated beneficiary eligibility and entitlement identification system. There may also be cases where the government needs to “manually” identify a specific sub-category of beneficiaries, taking into account requirements that cannot be entered into an electronic database. The Suvidha system provides a mechanism to meet these requirements first. Then it runs automated algorithms for selecting the remaining beneficiaries combining the best of human intervention and algorithmic precision.

The Kutumba ecosystem is now used by the Kerala government also to clean payment databases. The Raitha Vidyasiri scheme, which provides scholarships for children of farmers, was the first to use this framework to provide benefits on a suo motu basis to 2.5 lakh female students in grades 8, 9 and 10 and 3.5 lakh class 11 and 12 students in their bank accounts seeded by Aadhaar.

The government was able to identify 6.7 lakh likely recipients of old age pensions. Compensation for crop loss was paid suo motu to 10.5 lakh farmers. 2.82 lakh of ineligible ration card holders have been identified and weeded out, along with 1.42 lakh of ineligible Social Security retirees. Nearly 5 lakh of deceased beneficiaries have been removed from the systems. The savings for the public purse and for the beneficiaries have been significant.

Many other improvements are in the works. Better integration with other data sources, including central government data, would further strengthen the system. Kutumba and Suvidha is truly evidence-based policymaking and benefit delivery in action.

About Michael G. Walter

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