The Complete Guide to Using AI in the Financial Services Industry in Malta in 2025

Malta's financial sector is at a practical inflection point in 2025: the MFSA notes that

“use of artificial intelligence remains limited, with only a few institutions deploying AI for chatbots and fraud detection,”

even as the Government pushes a National AI Strategy to focus investment and scale capabilities across industries.

Global research warns that AI brings both big efficiency gains and regulatory scrutiny, so Maltese banks, fund administrators and fintechs are prioritising responsible, explainable deployments rather than headline-grabbing pilots.

Practical, job-ready skills - covering prompt design, tool selection and risk-aware rollouts - are now the fastest route from curiosity to measurable value; see the MFSA feedback on digitalisation in banking and consider training like Nucamp's AI Essentials for Work to bridge the gap between strategy and safe, revenue-driving AI projects.

Malta's national AI roadmap - published as the Strategy and Vision for Artificial Intelligence in Malta 2030 - is explicitly practical: it bundles three strategic pillars (investment, start‑ups and innovation; public‑sector adoption; private‑sector adoption) with three horizontal enablers (education and workforce, legal/ethical frameworks, and infrastructure) so the island can scale useful, trustworthy systems rather than chase novelty; see the official Malta AI Strategy and Vision 2030 (MDIA official) and the OECD summary of the plan for a concise action map.

Governance sits with the Malta Digital Innovation Authority, which is overseeing six pilot projects across health, education and traffic, while the strategy also builds in practical measures - a national AI certification scheme, a regulatory and data sandbox, support for SMEs and start‑ups, and incentives such as a Start‑up visa - to attract talent and capital.

Funding and monitoring are explicit too: OECD reporting notes an estimated annual expenditure of about €3.5M for implementation, and the plan even allocates public outreach funding to lift awareness; education reforms (AI Olympiad, AI Family Challenge) and reskilling programmes are front and centre so local workers can benefit as the private sector adopts AI at scale.

“This National AI Strategy aims to map the path for Malta to gain a strategic competitive advantage in the global economy.”

Who's who in Malta's AI oversight? The Malta Digital Innovation Authority (MDIA) is the island's focal point - leading national implementation of the EU AI Act, running voluntary certification and sandboxes, and anchoring Malta's effort to balance innovation with trustworthy systems (MDIA Artificial Intelligence services and certification); oversight is shared with the Information and Data Protection Commission (IDPC), which has been designated a Fundamental Rights Authority and is jointly identified as a Market Surveillance Authority, so privacy and rights monitoring will sit front and centre as high‑risk AI is deployed (Mamo TCV analysis of AI Act authority designations).

National implementation also names the MDIA and the National Accreditation Board as notifying authorities, which matters for firms preparing conformity assessments and third‑party audits (EU AI Act national implementation overview).

Sector supervisors such as the MFSA and MGA will remain influential for finance and gaming firms, and a group of nine public bodies (from the Competition & Consumer Affairs Authority to the Office of the Ombudsman) have explicit roles in protecting fundamental rights - in short, financial services teams should engage early with MDIA/IDPC, follow MFSA guidance, and budget for certification and compliance steps before scaling AI in production.

In Malta's financial services sector the most tangible AI wins are in credit decisions, risk scoring and accounts‑receivable workflows: machine‑learning models can detect payment patterns and extend credit faster, yet regulators view credit scoring as a high‑risk area that demands explainability - see the IE Insights piece on rethinking AI in credit decision‑making for why monotonicity constraints and techniques like SHAP or Shapley regressions help preserve transparency without materially hurting accuracy (IE Insights - Rethinking AI in Credit Decision‑Making).

At the operational edge, agentic AI agents are already reshaping collections and credit operations by ingesting real‑time signals, drafting personalised follow‑ups, proposing credit‑limit changes and surfacing at‑risk accounts so teams act before losses mount - Gaviti's research shows how autonomous A/R workflows can cut DSO and free staff for higher‑value work (Gaviti research on agentic AI in finance for credit and accounts receivable).

For Maltese fund administrators and SMEs the immediate, low‑risk wins are automation of PO matching and late‑payment risk detection to reduce fees and improve supplier relationships; practical implementation guides and prompts for these use cases are collected in local Nucamp resources for firms planning pilots (Nucamp AI Essentials for Work - PO matching and late‑payment risk detection prompts & implementation guides).

Picture an AI agent that reads a supplier's financials, drafts a tailored reminder at 02:00, and flags the account for a credit review by the morning desk - small, explainable automations like that are where Maltese firms can capture measurable value while staying audit‑ready.

Malta's technical foundations for AI in 2025 mix local high‑performance compute, public data and cloud tooling in a way that suits the island's compact but ambitious ecosystem: the national strategy explicitly backs cost‑effective access to computing capacity - naming the supercomputing cluster AL.B.E.R.T and Malta's participation in EuroHPC - as well as a Malta Data Portal for open datasets and a Malta Hybrid Cloud procured by MITA to give public and private teams flexible deployment options; see the Malta AI Strategy report (European Commission AI Watch) for the implementation details and the University of Malta research laboratories - AL.B.E.R.T supercomputing cluster page for confirmation that the Albert supercomputing cluster and GPU resources are already part of local research infrastructure.

For financial services this blend matters practically - teams can pair open, government‑curated datasets with on‑island GPU time or hybrid cloud instances to prototype credit‑risk or PO‑matching models without starting from scratch - making compute bottlenecks less of a blocker and turning infrastructure from an obstacle into a predictable enabler for pilots and scaled systems.

Malta firms preparing to deploy AI should treat compliance as a practical checklist, not an afterthought: start by inventorying every AI system and deciding whether your role is a provider or a deployer (the distinction drives different obligations), then map each system to the AI Act's risk categories - prohibited, high‑risk, limited or minimal - and prioritise high‑risk systems for early conformity work; see the clear compliance roadmap in EU AI Act compliance regulations for businesses (compliance roadmap).

Key milestones matter: the AI Act entered into force in 2024, banned practices and literacy obligations are already effective, and the staged obligations for notifying authorities, general‑purpose models and high‑risk conformity come into force through 2025–2026, so timetable your audits and documentation accordingly.

Build required artifacts now - technical documentation, risk assessments, human‑oversight plans, post‑market monitoring and AI‑literacy training for staff - and factor in third‑party conformity assessments, certification and budget for potential audits; non‑compliance risks steep penalties (up to €35M or 7% of global turnover) and market surveillance by Maltese authorities.

Engage early with Malta's designated market surveillance and rights authorities to clarify national processes and ensure your rollout aligns with local oversight and sectoral regulators; for an overview of who will lead enforcement in Malta, see overview of Malta AI Act authority designations and enforcement.

Ethics and data protection are now the plumbing of any AI project in Malta's financial sector: the EU's AI Act builds on GDPR's safeguards (human oversight, transparency and the right not to be subject to wholly automated decisions) so banks and fund administrators must treat explainability, DPIAs and data‑minimisation as operational priorities rather than legal afterthoughts - see the IDPC's guidance on AI and GDPR for how these rules intersect in practice (IDPC guidance on artificial intelligence and GDPR in Malta).

Generative AI adds IP and confidentiality wrinkles: Maltese law treats source code as copyrightable but currently leaves a gap for works created solely by autonomous processes, while prompts and fine‑tuning recipes may be best protected as trade secrets - good primer in the national overview of AI law (Global Legal Insights overview of Malta AI, machine learning & big data laws).

Practically this means rigorous supplier contracts (back‑to‑back compliance with DORA/GDPR), strong anonymisation or federated learning where possible, clear user notices when chatbots or generative outputs are used, and human‑in‑the‑loop controls for high‑risk use cases such as credit scoring or automated onboarding so a customer can always demand meaningful human review rather than a silent, algorithmic denial.

“preparing for this responsibility by ensuring that we introduce the necessary legislative amendments and build the required expertize.” - Ian Deguara, IDPC

Move from pilot to production in Malta by treating compliance and technical assurance as the backbone of every rollout: start with a tight use‑case inventory and AI‑Act risk classification, then design a Residency Plan and Sandbox Blueprint and apply to the MDIA Technology Assurance Sandbox so regulators, auditors and engineers can align early (the MDIA provides phased guidance and checklists and recommends appointing a Technical Officer and an approved Technical Expert to run initial and periodic technical‑soundness reviews).

During the monitored residency expect iterative Technical Soundness Assessments, a tri‑party review within months of approval, change‑request controls, and mandatory forensic logging (MDIA requires an audit node that records system operations) so every model decision is traceable - think of the log as a flight‑recorder for model behaviour.

Budget the small admin fee and systems‑auditor assessments (tech.mt notes the TAS is designed for SMEs and offers grant routes to cover auditor costs), gather sandbox documentation to feed your eventual conformity assessment, and remember EU guidance: national sandboxes shield good‑faith innovators from administrative fines but do not remove liability, so keep human‑in‑the‑loop controls and clear post‑market monitoring.

For teams that want practical help, pair sandbox residency with local implementation guides and the Nucamp implementation roadmap to turn regulatory alignment into measurable efficiency gains.

By 2025 AI will be doing the heavy lifting in Malta's finance sector: intelligence‑led, near real‑time transaction monitoring and pre‑transaction screening will automate customer clustering and segmentation, reduce false positives by more than 70% in some deployments, and narrow investigator queues to the handful of genuinely risky cases (making compliance teams far more surgical).

These capabilities feed directly into the FIAU's stepped‑up supervisory focus for 2025–2026 - a risk‑based monitoring plan that targets high‑risk sectors and uses CASPAR data to prioritise interventions - so AI becomes both an efficiency tool and a compliance enabler (FIAU Supervisory Plan 2025–2026 (Malta Financial Intelligence Analysis Unit)).

At the same time, generative and ML models are driving faster credit‑risk modelling and fraud detection but bring transparency challenges; Maltese firms that pair advanced models with explainability, integrated data flows and real‑time analytics will meet regulators' expectations for traceable, auditable outputs - as argued in recent industry analysis on banking readiness for 2025 (Banking in 2025: Risk, Regulation and Strategic Readiness (Wolters Kluwer)).

In practice, expect AI to surface contextual, explainable risk scores and visual link‑analysis for suspicious entities while human specialists retain final review and remediation responsibility, turning regulatory pressure into measurable operational advantage (Real‑time Transaction Monitoring in Malta (Eastnets)).

“the main aspect of on-going monitoring is that of scrutinising unusual, anomalous and suspicious transactions detected through the systemic and continuous review of customers' transactions.”

Conclusion: Malta's path from strategy to tangible value is straightforward - catalogue your AI use‑cases, classify them under the AI Act, and engage the Malta Digital Innovation Authority early so sandbox residency and certification de‑risk scale‑ups; start with the MDIA's guidance on services and sandboxes (MDIA - Malta Digital Innovation Authority official site) and align projects to the National Strategy for Financial Services to lock in regulatory and market support (MFSAC National Strategy for Financial Services - FinanceMalta strategy document).

Invest in practical upskilling (short, job‑focused courses such as Nucamp AI Essentials for Work - bootcamp syllabus cover prompt design, tool choice and governance) and appoint a Technical Officer to own documentation, human‑in‑the‑loop controls and post‑market monitoring;

think of the sandbox as a rehearsal space where your model's “flight‑recorder” logs are checked before full operations.

These steps - clear inventory, early regulator dialogue, technical ownership and targeted training - turn compliance obligations into measurable operational gains and a competitive edge in Malta's compact financial market.