Examkin

Question

Difficulty: MediumPassage Assumptions and Underlying Premises

Read the following passage carefully:

'To reduce high rates of non-performing assets in state-owned agricultural banks, several regional development boards have introduced automated credit-scoring algorithms to evaluate smallholder farm loan applications. Administrative officials claim that replacing subjective manual evaluations with algorithmic risk scoring will significantly decrease loan default rates across rural districts. This policy relies on the premise that algorithmic models can objectively assess borrower creditworthiness using historical transaction records and regional crop yield data. However, a vast majority of smallholder farmers operate primarily within informal cash economies, leaving minimal digital footprints or official banking records. Consequently, algorithmic evaluations risk systematically misclassifying viable rural borrowers as high-risk, thereby restricting their access to institutional credit and forcing them back toward high-interest informal lenders.'

Which one of the following is the most crucial underlying assumption required for the author's conclusion to hold true?

  1. Automated credit-scoring algorithms interpret the absence of official banking records as an indicator of high credit risk.Answer
  2. B
    Smallholder farmers who borrow from informal lenders incur significantly higher interest costs than those accessing institutional bank credit.
  3. C
    Manual loan evaluation processes in state-owned banks are inherently corrupt and ineffective at assessing farmer creditworthiness.
  4. D
    Automated algorithms completely fail to incorporate regional crop yield data into their credit assessment calculations.

Answer

The author's argument relies on the assumption that automated credit-scoring algorithms interpret the absence of official banking records as an indicator of high credit risk.
The author argues that because smallholder farmers lack digital footprints and official banking records, algorithmic evaluation will misclassify them as high-risk borrowers. For this argument to hold, it must be assumed that the algorithm interprets a missing digital history as evidence of high credit risk rather than neutral or indeterminate risk. If the algorithm did not draw this negative inference from missing data, the premise would not lead to the author's conclusion.

Step-by-Step Solution

1
Identify the author's main conclusion and supporting premises.
Conclusion: Algorithmic evaluations risk systematically misclassifying viable rural borrowers operating in cash economies as high-risk. Premise: Cash-based smallholder farmers leave minimal digital footprints or banking records.
An assumption is an unstated link connecting the premise (lack of digital footprint) to the conclusion (systematic misclassification as high risk).
2
Apply the Negation Test to candidate assumptions.
Negate the statement: 'Automated algorithms do NOT treat the absence of banking records as high risk.'
If algorithms do not treat missing records as high risk, then a farmer's lack of digital footprint will not cause them to be misclassified as high-risk. The author's conclusion collapses, proving this assumption is logically required.

Key Concept

Passage Assumptions and Underlying Premises
Rate this question

Topics

Passage Assumptions and Underlying Premises

More questions from this topic