FROM FINANCIAL LITERACY TO AI LITERACY: PREPARING COMMERCE STUDENTS FOR ALGORITHM-DRIVEN FINANCIAL DECISION-MAKING

Artificial intelligence is becoming increasingly visible in everyday financial activities. Students and consumers now encounter automated financial recommendations, digital investment platforms, personalised financial information and AI-based tools when making or evaluating financial choices. This changing environment raises an important question for Commerce education: is conventional financial literacy sufficient when financial information is increasingly mediated by algorithms? The present study examines financial literacy, AI literacy and awareness of ethical issues associated with AI-supported financial applications among Commerce students, and investigates their relationship with algorithmic financial decision quality. The study follows a descriptive and analytical research design and considers 250 student observations. Data were examined using descriptive statistics, Pearson correlation and multiple linear regression. Four major constructs were considered in the analysis: financial literacy, AI literacy, ethical awareness and algorithmic financial decision quality. The findings show that financial literacy recorded the highest mean score (M = 3.56), while AI literacy recorded a comparatively lower mean score (M = 3.33). AI literacy demonstrated the strongest correlation with algorithmic financial decision quality (r = .705, p ≤ .01), followed by financial literacy (r = .623, p ≤ .01) and ethical awareness (r = .605, p ≤ .01). The regression model explained 67.2% of the variation in algorithmic financial decision quality. AI literacy emerged as the strongest predictor (β = .443), followed by financial literacy (β = .376) and ethical awareness (β = .199), with all three predictors statistically significant at p ≤ .001. The findings suggest that financial knowledge remains essential, but it needs to be complemented by the ability to understand, question and evaluate AI-generated financial information. Commerce education therefore needs to move towards an integrated approach in which financial literacy, AI competence and ethical awareness support independent and responsible financial judgement.

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Journal
Interdisciplinary Perspectives of Education
Published
2026-11-02
DOI
https://doi.org/10.65525/ipe.v3i2.129
Primary Topic
Financial Literacy and Behavior
Type
article
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article

FROM FINANCIAL LITERACY TO AI LITERACY: PREPARING COMMERCE STUDENTS FOR ALGORITHM-DRIVEN FINANCIAL DECISION-MAKING

Asha R Nair
2 links
Interdisciplinary Perspectives of Education
Financial Literacy and Behavior
article

FROM FINANCIAL LITERACY TO AI LITERACY: PREPARING COMMERCE STUDENTS FOR ALGORITHM-DRIVEN FINANCIAL DECISION-MAKING

Asha R Nair
article en

Abstract

Artificial intelligence is becoming increasingly visible in everyday financial activities. Students and consumers now encounter automated financial recommendations, digital investment platforms, personalised financial information and AI-based tools when making or evaluating financial choices. This changing environment raises an important question for Commerce education: is conventional financial literacy sufficient when financial information is increasingly mediated by algorithms? The present study examines financial literacy, AI literacy and awareness of ethical issues associated with AI-supported financial applications among Commerce students, and investigates their relationship with algorithmic financial decision quality. The study follows a descriptive and analytical research design and considers 250 student observations. Data were examined using descriptive statistics, Pearson correlation and multiple linear regression. Four major constructs were considered in the analysis: financial literacy, AI literacy, ethical awareness and algorithmic financial decision quality. The findings show that financial literacy recorded the highest mean score (M = 3.56), while AI literacy recorded a comparatively lower mean score (M = 3.33). AI literacy demonstrated the strongest correlation with algorithmic financial decision quality (r = .705, p ≤ .01), followed by financial literacy (r = .623, p ≤ .01) and ethical awareness (r = .605, p ≤ .01). The regression model explained 67.2% of the variation in algorithmic financial decision quality. AI literacy emerged as the strongest predictor (β = .443), followed by financial literacy (β = .376) and ethical awareness (β = .199), with all three predictors statistically significant at p ≤ .001. The findings suggest that financial knowledge remains essential, but it needs to be complemented by the ability to understand, question and evaluate AI-generated financial information. Commerce education therefore needs to move towards an integrated approach in which financial literacy, AI competence and ethical awareness support independent and responsible financial judgement.

Interdisciplinary Perspectives of EducationVol. 3(2)
Sri Ramakrishna College of Arts and Science (IN)
Quality education
Openalex Percentile: Top 9%
Financial Literacy and Behavior
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FROM FINANCIAL LITERACY TO AI LITERACY: PREPARING COMMERCE STUDENTS FOR ALGORITHM-DRIVEN FINANCIAL DECISION-MAKING — Asha R Nair · Interdisciplinary Perspectives of Education (2026) | TGRS Research Map | TGRS