Top 10 AI Prompts and Use Cases and in the Financial Services Industry in Portugal

AI is already changing finance in Portugal at two levels: customer experience and supervisory oversight. The Bank of Portugal's Alya platform (launched in 2023) automates document summarisation, complaint classification and market‐sentiment warnings and is being prototyped with the Bundesbank's Tia as “Tilya” to validate Pillar 3 reporting - Alya even flagged Credit Suisse in a news spike - showing how AI can scale supervision beyond manual sampling (Bank of Portugal Alya AI initiative details).

At the same time Portuguese users judge AI by service quality and security, so adoption hinges on trust, not just capability (study on AI adoption in Portuguese mobile banking).

The pragmatic takeaway: run safe pilots, combine document and sentiment tools with clear governance, and invest in workplace AI skills that teach prompts, evaluation and compliance.

Bootcamp	Length	Early bird cost	Registration
AI Essentials for Work	15 Weeks	$3,582	Register for AI Essentials for Work (15 Weeks)

“AI is revolutionizing the world of finance. I think there are many use cases, not only for the end customer, but also within the banks' infrastructure when it comes to applying it.”

The list was built by triangulating real Portuguese evidence, regulatory guidance and practitioner insight: priority use cases and prompts were chosen from documented deployments (notably the Bank of Portugal's Alya platform and its document‑and‑sentiment tooling), academic consumer research on trust and security in Portuguese mobile banking, and up‑to‑date legal/regulatory overviews that shape what banks must do to stay compliant.

Selection criteria were pragmatic - demonstrable Portuguese relevance, deployability in pilot form, measurable user impact (the FBJ study's N=452 survey, July–Oct 2024, shows security and service quality drive trust) and explicit governance controls to limit model and data risk - plus industry cautionary notes on third‑party dependence and model governance.

The intended readers are Portuguese banks, fintech teams, product managers and supervisors looking for compliance‑aware, pilotable prompts that map to real supervision needs; the so‑what is simple: pick prompts that can be tested end‑to‑end in a sandbox and produce an auditable signal (Alya, for example, even flagged Credit Suisse in a news spike), so pilots prove value without becoming hidden liabilities.

Method element	Example source
Central bank deployment	Bank of Portugal Alya AI initiative (central bank deployment)
Consumer evidence	AI adoption in Portuguese mobile banking study (N=452)
Regulatory context	Banking Regulation 2025 - Portugal regulatory overview

“So far, it has not been possible to automate the entire rules, but [Alya] has been a major accelerator for certain processes.”

Bank of Portugal's Alya is a practical example of how AI can shrink the manual toil of supervision in Portugal: launched in 2023, Alya combines natural‑language, audio, image and speech processing to summarise lengthy annual reports, classify complaints and suggest email replies, freeing supervisors to move beyond spot sampling towards more frequent, structured Pillar 3 checks - a key objective of EU disclosure work (see the EBA's Pillar 3 guidance).

In live tests Alya also powers market‑sentiment warnings (it identified Credit Suisse at the top of news and research during last year's crisis), and the platform's classification features already hit about 70% accuracy for request classification and reply suggestions, making it a fast, auditable preprocessing layer for downstream tools such as the Bundesbank's Tia (the Alya+Tia “Tilya” prototype aims to validate Pillar 3 coverage).

For Portuguese banks this means pilots can focus on auditable signals (summaries, exception lists, and content checks) rather than speculative “black‑box” automation - a pragmatic route to scale oversight while preserving explainability and governance.

“So far, it has not been possible to automate the entire rules, but [Alya] has been a major accelerator for certain processes.”

Tilya - the Alya+Tia prototype - turns the Bank of Portugal's document‑and‑sentiment stack into a practical early‑warning system for Portugal's financial sector: Alya preprocesses annual reports, news and multimedia into structured inputs and Tia applies deeper text analysis to validate Pillar 3 coverage and spot anomalies, so supervisors can scale checks beyond sampling and run near‑real‑time market surveillance (Central Banking coverage of the Bank of Portugal Alya AI initiative).

In live tests this kind of market‑sentiment coupling has already flagged acute coverage - for example, Alya detected Credit Suisse at the top of news and research during last year's crisis - a vivid, single‑line signal that lets teams prioritise investigations instead of wading through hundreds of pages.

For Portuguese banks and regulators the payoff is concrete: more frequent, auditable signals for disclosure checks, faster detection of reputational risks, and the option to plug in specialist tools or APIs for sentiment scoring (see examples such as Arya.ai financial sentiment analysis API for financial services) while keeping human oversight at the centre of decisioning.

“Alya could identify that Credit Suisse was at the top of news and research. It can be used to warn of critical situations and centralise the relevant information.”

ClickUp AI (ClickUp Brain) is a practical, low‑friction tool Portuguese banks can use to classify incoming customer queries, condense threads into clear summaries and generate brand‑consistent reply suggestions that human agents can review and send - all from inside ClickUp Docs or tasks via simple slash commands; see the ClickUp Brain CRM prompts for customer relationship management for examples of tailored prompts and workflows.

For compliance‑aware pilots this matters: prompts can pull CRM context, surface potential GDPR or data‑quality issues, and turn scattered feedback into prioritized tasks or templated responses so every reply is auditable and traceable (examples and templates are available for customer acquisition and conversational marketing).

In practice, that means less time triaging repetitive tickets and more time on exceptions - what once required wading through long threads can become a concise, human‑checked reply suggestion in seconds - helping Portuguese banks improve service speed while keeping human oversight and regulatory checks front and centre (see the ClickUp guide: how to use AI in customer service for practical steps and templates).

Caixa Geral de Depósitos (CGD) - fraud detection & transaction monitoring: Portuguese banks can get more accurate, operational fraud signals by pairing robust feature‑selection with real‑world transaction splits rather than chasing opaque black‑box scores; research shows methods like FID‑SOM (feature selection using Self‑Organising Maps) reduce dimensionality and lift detection metrics on highly imbalanced card datasets, helping models focus on the rare events that matter (FID‑SOM credit card fraud detection study (Journal of Big Data)).

The practical payoff for CGD is concrete: in benchmark tests FID‑SOM pushed F1 and PR‑AUC noticeably above baseline models, and the paper stresses time‑based splits and encoders tuned for imbalance to avoid optimistic results - a vivid reminder that fraud often sits below 0.5% of transactions (examples run as low as 0.17%), so feature engineering determines whether alerts overwhelm investigators or actually prioritise real risk.

Combine such methods with local transaction samples (public sets and synthetics are available for testing, e.g. the Kaggle bank transaction dataset for fraud detection), adopt time‑aware validation, and surface high‑variance SOM features as auditable signals that human teams can review and act on.

Dataset	Cases	Attributes	Fraud %
DataSet-A (Synthetic)	3,445,553	25	0.14%
DataSet-B (Sparkov)	1,852,394	11	0.52%
DataSet-C (Real European)	284,807	30	0.17%

Revolut Portugal is already shaping a practical route to personalised financial planning in‑app: a coming AI‑powered assistant promises tailored nudges and smarter money habits while the existing toolkit - Pockets, recurring buys for hands‑off investing, real‑time budgeting analytics and spending insights - helps customers turn goals into automated actions (Revolut 2025 AI assistant announcement and roadmap).

For Portuguese users who value clear outcomes, the combination of goal‑oriented features and loyalty signals (RevPoints across plans) makes advice actionable: recurring buys and simple budget automation can translate a modest monthly habit into long‑term wealth, while higher tiers (Premium, Metal, Ultra) layer greater limits, insurance and rewards for frequent travellers and savers (Revolut budgeting tools: Pockets, recurring buys, and analytics).

Security and scale are emphasised too - Revolut cites €36 billion in customer funds held and strong fraud prevention - so pilots that test personalised advice, explainability and audit trails can show measurable user value without sacrificing oversight.

A vivid test: an Ultra customer can earn 1 RevPoint per €1 spent while accessing bundled benefits worth over €5,000 a year, turning loyalty signals into tangible planning outcomes (Revolut pricing plans and RevPoints rewards).

Plan	Monthly fee	RevPoints rate
Standard	Free	1 per €10
Plus	€3.99	1 per €10
Premium	€8.99	1 per €4
Metal	€15.99	1 per €2
Ultra	€50	1 per €1

“2024 has been a significant year for Revolut, with millions of new accounts opened and innovative products launched across our markets. 2025 will be bigger and better. We want to revolutionise banking for the better and we're on the right path to achieve this.”

Millennium bcp shows how Portuguese banks can turn company financial analysis and forecasting from a slow, manual craft into an auditable, near‑real‑time capability by pairing decision engines with experienced credit teams: using FICO solutions the bank automated 91% of retail decisions and runs about 128 million automated decisions a year, letting credit professionals focus on exceptions and higher‑value analysis (FICO press release: Millennium bcp automates 91% of retail banking decisions).

For corporate and SME forecasting this approach matters because behaviour‑based account signals and coordinated account‑level decisions produce sharper risk pricing and faster, targeted offers - practical when supervisors warn that underwriting standards and data quality remain a systemic challenge in Europe (ECB supervisory note on underwriting standards and data quality).

Pilots in Portugal should mirror Millennium's pragmatic playbook: combine historical data, clear decision rules and human oversight, validate models with time‑aware splits, and run a GPU pilot roadmap to measure ROI safely (GPU pilot roadmap for Portugal financial services AI projects) - a vivid benchmark is that 7 million overdraft authorisations are automated annually at Millennium, with 99.7% self‑curing within three months, showing automation can scale without losing control.

Metric	Value
Automated retail decisions	91%
Automated decisions per year	128 million
Overdraft authorisations automated	7 million/year
Self‑cure rate (overdrafts)	99.7% within 3 months
Customers served	>5 million

“FICO offers its clients worldwide analytics and advanced decision engines that can enable more profitable decisions. With our solutions, Millennium bcp can turn customers who only use their current accounts for deposits and cash payments into clients with credit products that are more profitable.”

Banco de Portugal's Draft Notice (Public Consultation No. 2/2024) reframes how banks and fintechs must advertise in Portugal, splitting promotions into three distinct types (advertising financial products or services, advertising the activity, and institutional advertising) and demanding clearer, digital‑ready disclosures - for mortgages, consumer and business credit that means the APR or EAR and a representative example must be shown with prominence comparable to the product name or benefits (Banco de Portugal Draft Notice on Advertising Financial Products and Services - Abreu Advogados); the Draft Notice also plans to require firms to file all campaigns through the Bank's Advertising Reporting service on BPNet and to archive proof of approval for two years.

That national tightening sits alongside platform rules: showing financial services ads to Portuguese users now requires Google's Portugal verification process and evidence of local authorisation, so any multi‑modal marketing pilots (images, video, short copy or AI‑generated creative) must bake in automated checks for APR prominence, representative examples and archiving to pass both supervisor and ad‑platform gates (Google Ads Financial Services Verification for Portugal).

The bottom line for Portuguese teams: creative AI can speed campaigns, but a missed APR or a missing representative example risks regulatory pushback - keep human sign‑off, auditable templates and a two‑year archive as non‑negotiable controls.

Requirement	Key point
Advertising categories	Financial products/services; advertising the activity; institutional advertising (different rules apply)
Credit & mortgage adverts	APR/EAR and representative example must be shown with similar prominence to product name or highlighted benefits
Filing & archiving	Report campaigns via BPNet “Advertising Reporting” and keep proof of approval for 2 years

Santander Portugal's HR playbook shows how prompt‑driven automation can make talent management both faster and more humane: by combining RPA for repetitive admin (Santander cut onboarding time by 85%, from roughly six weeks to two days in a Blue Prism case study Santander Portugal onboarding reduced 85% - Blue Prism RPA case study) with clear, role‑specific learning and local adaptation, banks can free HR teams to coach and retain talent rather than chase paperwork (Santander Portugal human resources responsibilities and onboarding overview, Global onboarding best practices for HR: 7 strategies).

The “so what?” is vivid: automate the boring, standardise the essentials, and use smart prompts to surface the human exceptions that really need a manager's judgement - making onboarding faster, fairer and auditable for Portuguese teams.

Novo Banco's layered governance - a monthly General and Supervisory Board supported by five specialised committees (Financial Affairs/Audit, Risk, Compliance, Nomination and Remuneration) and an Executive Board with its own suite of committees - creates a clear, practical opportunity for AI to turn dense corporate documents into timely, auditable board and management reporting.

By indexing the bank's Articles of Association, committee regulations and Remuneration Committee reports, an AI-assisted pipeline can surface the KPIs the Remuneration Committee already defines, flag exceptions against the risk and compliance rules that the GSB monitors, and produce concise, traceable briefs for the Executive Board's transformation and CALCO meetings so directors spend meeting time on judgement not paperwork; see Novo Banco's governance overview and company‑documents repository for the formal sources that feed this work (Novo Banco corporate governance overview, Novo Banco company documents and regulations repository).

For Portugal's supervisory context, such summaries help ensure board packs link directly to audited policies (remuneration, AML, succession and ESG) and create an auditable trail that supports both internal committees and external reporting to investors and regulators.

Board body / committee	Key oversight focus
General and Supervisory Board (monthly)	Overall supervision, risk management, compliance
Financial Affairs (Audit) Committee	Internal control, reporting, statutory auditor oversight
Risk Committee	Risk appetite, credit & liquidity, capital monitoring
Compliance Committee	AML, conduct, regulatory compliance
Remuneration Committee	KPI definition, deferral rules, clawback/malus

Crédito Agrícola can turn routine surveys, eNPS pulses and open customer comments into an auditable, action‑oriented feed by combining reliable national data practices with lightweight AI pilots: use supervised classifiers and sentiment scoring to collapse thousands of free‑text replies into a short, prioritized list of service issues for branch managers (for example, a two‑line alert that flags a systemic mortgage disclosure concern), then link those signals to time‑aware validation and governance so alerts aren't just noise.

Portugal's public statistical frameworks (see the IMF's DQAF overview for Portugal) remind teams to anchor models to trustworthy, versioned datasets, while a practical GPU pilot roadmap helps measure ROI and control model risk before scaling.

By treating eNPS and survey outputs as auditable signals - not final decisions - Crédito Agrícola can boost retention and operational fixes without sacrificing explainability or compliance under emerging EU rules.

Beginners in Portugal should prioritise small, auditable pilots that map directly to supervision and customer value - start with document summarisation, complaint classification or market‑sentiment monitoring (the kinds of use cases deployed by the Bank of Portugal's Alya) and run them inside a regulatory sandbox or ZLT so legal, privacy and DORA/AIA obligations are checked early; see the Portugal AI 2025 guidance (Chambers Practice Guides) for the evolving EU AIA and national context (Portugal AI 2025 guidance (Chambers Practice Guides)) and the Bank of Portugal Alya AI initiative (Central Banking) for a concrete blueprint (Bank of Portugal Alya AI initiative (Central Banking)).

Use time‑aware validation, keep humans in the loop, log outputs for explainability, and pair pilots with practical skills training - programmes such as the Nucamp AI Essentials for Work bootcamp syllabus provide prompt design, evaluation and governance training that makes pilots safe and effective (Nucamp AI Essentials for Work bootcamp syllabus).

A pragmatic rule: prove an auditable signal (exceptions, summaries, or ranked alerts) before automating decisions.

Recommended starter	Length	Early bird cost	Register
AI Essentials for Work	15 Weeks	$3,582	Register for Nucamp AI Essentials for Work bootcamp (Registration)

“Alya could identify that Credit Suisse was at the top of news and research. It can be used to warn of critical situations and centralise the relevant information.”