After making claims about India's robust digital public infrastructure (DPI), comprising distinctive digital identification, a payments system, and a data exchange layer, the submission of State Bank of India (SBI) in the Supreme Court of India about its digital incapability cannot be deemed trustworthy. What happened to the claim made as part of G20 Digital Economy Working Group about India's Unified Payments Interface (UPI) having revolutionized digital payments?
A data scientist and a former student of the National Forensic Sciences University, a public international university located in Gandhinagar, Gujarat, and recognized as an Institution of National Importance by the Ministry of Home Affairs has decoded the indefensible claims made by State Bank of India (SBI).
He states the following:
- Digital Capabilities vs. Claims of Incapability: From a data viewpoint, the contradiction between SBI's existing digital infrastructure and its claims of incapability is striking. SBI's centralized banking system, likely built on a combination of modern relational database management systems (RDBMS) and legacy systems (possibly including COBOL-based applications), is capable of tracking and managing millions of transactions daily. These systems are designed with unique identifiers for transactions (e.g., transaction IDs) and robust query capabilities, facilitating rapid data retrieval and reporting. The assertion of difficulty in providing specific transactional information thus raises questions about procedural rather than technical limitations. This discrepancy raises questions about transparency and accountability, especially ahead of parliamentary elections.
- Technical Feasibility of Meeting the Court's Demands: The statement by an anonymous COBOL programmer that generating the required reports is a "one-day job" underscores the simplicity of the task from a technical standpoint. Accessing transactional databases and running SQL queries to extract and format the necessary data should be straightforward for a bank's IT department. The use of automated scripts for data extraction and report generation is a common practice, highlighting that the delay is likely not due to technical constraints.
- Misrepresentation to the Supreme Court: The request for an extension, in light of the bank's technical capabilities may suggest a strategic maneuver rather than a technological hurdle. In the daily practice of data science, the ethics of data handling and reporting are crucial. This scenario emphasizes the need for transparent data governance practices and the ethical responsibility of institutions to accurately report data, especially when it impacts public interest and governance.
The most prominent public sector bank (PSB) in India recently announced that it needs a 120-day time frame to collate 44,434 sets of data related to electoral bonds. It amounts to collation of 370 sets of data per day!
Unbelievably, given the state-of-the-art technology and operational capacities of institutions such as the SBI, this task can be completed within a single day.
It is worth noting that there are many Python libraries available and machine learning tools that are well-suited for large-scale data collection.
However, the fact that the largest PSB in India is unwilling to utilize these technological tools raises questions as to the efficiency and reason behind its stated timeline.
In view of the clear capabilities of the data science domain in India, the Supreme Court should consider collaborating with the data science community.
The extraction and collation of the required data can be expedited with the help of the community on a voluntary basis.
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*Source: Toxics Watch
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