What does this research mean for the field?

Quantum computing offers significant potential across multiple financial domains, but its practical implementation requires addressing existing constraints and focusing future research on explainability, robustness, and trustworthy AI. Novelty: ClaimNovelty.SYNTHESIS. Consensus alignment: ConsensusAlignment.NEUTRAL.

What question did this study set out to answer?

To synthesize recent scientific literature on quantum computing applications across financial domains and identify actionable research directions for trustworthy artificial intelligence.

August 30, 2026Frontiers in Artificial IntelligenceOpen Access

Quantum computing in finance: a literature review and future directions for trustworthy financial AI

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Authors

SMSilvia Muzzioli FRFarhana Raheem MFMassimiliano Ferrara

Discussion

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Overview

Literature review uncovers key computational gaps and governance challenges across financial domains, highlighting opportunities for trustworthy quantum artificial intelligence in Europe.

Key Points

To synthesize recent scientific literature on quantum computing applications across financial domains and identify actionable research directions for trustworthy artificial intelligence.
Conducted an integrated review of literature spanning seven core areas: portfolio optimization, derivative pricing, fraud detection, credit risk, actuarial science, econometrics, and cryptocurrency security.
Assessed theoretical methods against empirical testing constraints, economic significance, and cross-cutting governance issues such as explainability and robustness.
Identified five macro-gaps limiting the empirical testing, governance, and practical deployment of quantum algorithms in finance.
Proposed seven concrete research directions leveraging emerging European quantum computing infrastructure and regulatory frameworks for trustworthy AI.

Cite This Study

Muzzioli et al. (2026) studied this question.

synapsesocial.com/papers/6a93f00a6c1a8fb52e79c06d https://doi.org/10.3389/frai.2026.1929828

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August 30, 2026Frontiers in Artificial IntelligenceOpen Access

Quantum computing in finance: a literature review and future directions for trustworthy financial AI

View Full Paper

Ask AI

Bookmark

Authors

SMSilvia Muzzioli FRFarhana Raheem MFMassimiliano Ferrara

Discussion

Member takes

Overview

Literature review uncovers key computational gaps and governance challenges across financial domains, highlighting opportunities for trustworthy quantum artificial intelligence in Europe.

Key Points

To synthesize recent scientific literature on quantum computing applications across financial domains and identify actionable research directions for trustworthy artificial intelligence.
Conducted an integrated review of literature spanning seven core areas: portfolio optimization, derivative pricing, fraud detection, credit risk, actuarial science, econometrics, and cryptocurrency security.
Assessed theoretical methods against empirical testing constraints, economic significance, and cross-cutting governance issues such as explainability and robustness.
Identified five macro-gaps limiting the empirical testing, governance, and practical deployment of quantum algorithms in finance.
Proposed seven concrete research directions leveraging emerging European quantum computing infrastructure and regulatory frameworks for trustworthy AI.

Cite This Study

Muzzioli et al. (2026) studied this question.

synapsesocial.com/papers/6a93f00a6c1a8fb52e79c06d https://doi.org/10.3389/frai.2026.1929828

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