After making claims about robust India's 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:
1. 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.
2.
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.
4.
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 has 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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