Work

Leveraging big data analytics for competitive advantage in fintech: a cross-country strategic analysis

Year: 2026

Type: article

Abstract: Fintech organizations require integrated analysis of structured and unstructured data to maintain competitiveness. This study develops a Big Data Analytics framework combining technical indicators and machine learning to optimize strategic decision-making across multiple countries. Using open-source ETF data and rigorous walk-forward validation we demonstrate that a systematic analytical pipeline can generate above-random predictions across different markets. The framework provides a reproducible methodology for sector-level investment screening that small and medium enterprises can adopt without expensive proprietary tools. The study contributes to fintech strategy literature by showing how proper validation techniques prevent look-ahead bias in financial prediction research. The findings demonstrate that Big Data Analytics when combined with rigorous validation can inform strategic decision-making across different regulatory and market environments.

Source: Quality & Quantity

DOI: 10.1007/s11135-026-03056-7

Authors: Jamal Al Qundus, Bassam Al-Shargabi, Silvio Peikert

Institutions: German Jordanian University, Cardiff Metropolitan University, Fraunhofer Institute for Open Communication Systems

Language: English

Topic: Stock Market Forecasting Methods

Subfield: Management Science and Operations Research

Field: Decision Sciences

Domain: Social Sciences

Open Access status: hybrid

Estimated APC paid: $3,090

OpenAlex ID: W7203761884