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

AI is no longer an experiment in Singapore's financial sector - it's the engine of competitive advantage: DBS alone created roughly $750 million of AI value in 2024 and is eyeing more than $1 billion in 2025, a vivid signal that personalised services, intelligent automation and massive efficiency gains are tangible outcomes (DBS $1 billion AI transformation case study (2024–2025)).

Legacy and regional banks aren't standing still: UOB deployed intelligent automation years ago as a core digital strategy (UOB intelligent automation digital transformation case study), while industry writing stresses the need for strong AI governance and cybersecurity as capabilities scale.

For professionals and teams in SG, this means upskilling is urgent - practical, workplace-focused training in prompts, tools and use cases turns abstract advantage into day‑to‑day results; see the AI Essentials for Work bootcamp syllabus for a hands‑on route to those skills (AI Essentials for Work bootcamp syllabus (Nucamp)).

Program	Details
AI Essentials for Work	15 Weeks - Early bird $3,582 - Register for AI Essentials for Work - Nucamp

Selection favoured prompts and use cases with clear Singaporean proof points: demonstrable business value, regulatory alignment, and operational readiness. Priority went to examples already live or tested in local institutions - evidenced by DBS' hundreds of in‑production efforts (350+ use cases and ~800 models) and vendor solutions that solve real pain‑points such as thousands of noisy AML alerts or thin‑file credit decisions - so recommendations aren't theory but deployable workstreams; see SotaTek's roundup of top providers for regional context and the DBS case study for concrete impact and governance patterns.

Criteria included MAS alignment (FEAT and newer consortia guidance such as Project MindForge), measurable ROI or efficiency gains, data quality and privacy safeguards, explainability to satisfy compliance teams, and ease of integration with legacy stacks.

Risk controls - guarding against hallucinations, prompt injection, and data leakage - were non‑negotiable, and preference was given to partners with regional experience and end‑to‑end monitoring plans that enable safe scaling across Singapore's tightly regulated market.

“[The framework ensures] that use case owners evaluate whether we should use the data in the intended way and not just whether it is legally permissible or technically possible.” - Nimish Panchmatia, Chief Data and Transformation Officer, DBS

Active.Ai has been a standout in Singapore's move to automated customer service and conversational banking, offering a “no browsing, no downloads, no forms” experience where customers simply chit‑chat with a tireless bot to check balances, view transactions, make payments or get advice - exactly the kind of 24/7, mobile‑first support Singapore banks need as customer expectations rise; read the original Active.Ai conversational banking platform case study on Prove for details.

Built on an Omni Connector architecture with products like Morfeus (middleware) and Triniti (bank‑tuned NLU), Active.Ai emphasises context‑sensitive spelling correction, intent classification, sentiment detection, entity extraction and even small‑talk - able to normalise slang and acronyms such as “xfer” or “acc” so dialogs flow naturally (Profile of Triniti and Omni Connector at The Silicon Review).

Headquartered in Singapore and serving BFSI clients across 43 countries, the company's 2022 acquisition by Gupshup strengthened its conversational CX stack for banks and fintechs, making it a practical option for institutions scaling AI‑driven customer engagement in Singapore and the region (Active.Ai acquisition by Gupshup announcement - Vertex Ventures Singapore).

“Conversation is the new UX, and with banks opening up APIs, a new era of digital business is emerging. We are moving from 'mobile-first to AI-first,' and Active.ai is the platform facilitating Banks to achieve that.” - Ravishankar, CEO and Co‑founder

Silent Eight's Iris 6 is built for Singapore's high‑standards of AML/KYC: a modular, explainable Agentic AI that cuts alert noise and speeds investigations while keeping every decision traceable for MAS‑style audits.

By combining entity resolution, dynamic risk models and real‑time triage, Iris can rank and route alerts within seconds, reduce false positives by as much as 60% and expedite potential true positives - clients report up to a 70% drop in time from alert to confirmed match - so compliance teams focus only on genuine threats rather than endless noise.

Designed to integrate with legacy stacks and tuned to regulatory change via configurable policy simulators, the platform's global footprint and auditability make it a pragmatic option for Singapore banks seeking scalable, low‑TCO compliance; learn more in Silent Eight's piece on aligning with MAS and the Iris product overview.

Metric	Value
AML investigations solved (2024)	100+ million
Peak solve rate	83%
Markets supported	150 regulated markets
False positive reduction	Up to 60%
Model precision	98.7%

“When AI works hand in hand with your team – assisting in AML and KYC processes end-to-end – you are able to truly scale. This isn't theoretical. Our AI is already deployed across some of the world's largest financial institutions, operating in over 150 regulated markets. We're doing the work today.” - Ben Rayner, Global Head of Sales at Silent Eight

Finbots.AI, founded in Singapore, offers CreditX/ZScore - a no‑code, alternative‑data credit scoring engine designed to help lenders approve thin‑file customers profitably while meeting MAS‑level governance; the platform claims rapid scorecard creation (hours/days), real‑time decisioning (<0.03 sec) and measurable uplifts such as >20% higher approvals and >15% lower loss rates, making it a practical fit for digital lenders and SME desks that need speed without sacrificing explainability (see the Finbots.AI CreditX no-code credit scoring platform and a market write‑up on Finbots' early growth and tech approach at Fintech Global article on Finbots' credit risk solution).

Built to ingest internal, external and alternative datasets, CreditX automates feature engineering, bias reduction and one‑click deployment while supporting MAS Veritas and AI Verify workflows - a useful “fast‑to‑value” route for Singapore teams aiming to expand financial inclusion without overloading risk operations; imagine underwriting decisions that arrive in the time it takes to blink, freeing relationship managers to focus on exceptions and growth.

Metric	Finbots.AI Claim
Increase in Approvals	>20%
Decrease in Loss Rates	>15%
Decision Latency	<0.03 sec
Operating Cost Reduction	>50%
Origin	Founded in Singapore

“A game-changer in credit modelling” - Ti Eng Hui, CEO, Baiduri Bank

Taiger - Document Understanding & Underwriting Automation: in Singapore's tightly regulated banks and insurers, the payoff from automated document understanding is practical and immediate - think a 50‑page credit dossier reduced to a one‑line risk snapshot that steers an underwriter straight to the exceptions.

The core techniques are plain: OCR to read PDFs, document classification, named‑entity extraction and relationship‑level information extraction, plus summarisation and deep‑learning fine‑tuning so models handle messy, jargon‑filled files reliably (see POTENZA's guide to mastering NLP for document understanding for a useful checklist and pilot‑first advice).

By starting small on high‑volume document types (invoices, contracts, credit reports) teams can prove ROI fast and feed subject‑matter expert corrections back into the model, exactly the pragmatic route Nucamp highlights for transforming compliance and contract processing via NLP document automation.

That practical, iterative approach also maps to Singapore's governance expectations as NAIS 2.0 and MAS guidance push firms to pair capability with controls - delivering faster underwriting decisions without losing explainability or auditability (POTENZA - Mastering NLP for Document Understanding, Nucamp AI Essentials for Work syllabus - NLP document automation for compliance, Nucamp AI Essentials for Work syllabus - AI governance and MAS NAIS 2.0 guidance).

ADVANCE.AI's liveness detection is a practical tool for Singapore banks and fintechs that need fast, tamper‑resistant identity verification for remote onboarding and fraud prevention: the system explicitly distinguishes a live person from a 2D print or replayed video, detects flat-image spoofs and uses facial movement recognition - head movement, eye‑blinking and mouth opening - to prove presence in real time (ADVANCE.AI liveness detection product overview).

That multi‑layered approach maps neatly to common Singapore use‑cases (banking, payments and fintech) flagged in the vendor's regional write‑ups, helping teams balance low friction with stronger anti‑spoofing controls during KYC and high‑value transactions (ADVANCE.AI blog: liveness detection in Singapore and APAC).

For teams planning pilots, this means starting with risk‑based flows - passive checks for routine logins and active challenges for sensitive steps - so onboarding stays smooth for customers while making synthetic‑identity and replay attacks vastly harder to pull off.

Feature	Notes
Anti‑spoofing	Distinguishes live faces from 2D prints and videos; detects flat images
Movement analysis	Head movement, eye blinking, mouth opening used to confirm liveness
Primary Singapore use cases	Remote onboarding, KYC, high‑value transaction verification for banks/fintech
Regional presence	Listed for Singapore among other APAC markets

Crayon Data's maya.ai brings a modular, Singapore‑based approach to personalised product recommendations and marketing - think plug‑and‑play Apps, pre‑built Models and governance‑ready Capabilities that let banks and merchants speed from pilot to production without rebuilding data plumbing.

Using patented taste‑led enrichment, Genome Builder profiles and campaign tooling, maya.ai can stitch customer behaviour, merchant offers and third‑party feeds into targeted campaigns and offer‑packs that improve CLV while preserving lineage and data governance; the platform's headless APIs and pre‑built connectors make integration with core banking stacks and merchant ecosystems straightforward (Crayon Data maya.ai modular AI platform for banks and merchants).

For smaller teams or SME pilots, the Maya product family also surfaces low‑code tools and no‑friction apps that scale marketing and sales automation fast - useful for Singapore institutions that need measurable uplift with tight compliance and speed to market (SmartMaya Maya AI platform for SMEs marketing automation).

Layer	Examples
Apps	Customer App, Merchant App, Enterprise App
Models	Enrichment Engine, Genome Builder, Model Library & Builder
Capabilities	Offer Sourcing, AI‑curated Campaigns, Data Governance & Connectors

DataRobot brings a practical, governance‑first AutoML stack that Singapore banks and fintechs can use to go from experiments to production while staying audit‑ready: its AI Catalog, Model Leaderboard and Composable ML speed model building, while built‑in MLOps tracks data drift, accuracy and challenger models so teams know when to retrain - think of drift alerts as a smoke alarm for a live credit model.

The platform embeds into complex origination and fraud flows, automates documentation for model risk teams, and supports SR 11‑7 style validation and monitoring practices so compliance and product owners can move faster with confidence; see DataRobot's writeups on DataRobot model monitoring blog and its DataRobot AI for financial services solutions capabilities.

Partners have used DataRobot to modernise scorecards and speed decisioning in weeks (example: Evolve AI + DataRobot consumer credit underwriting case study), and the vendor cites faster deployments and measurable ROI that make a pilot‑to‑scale path tangible for SG teams.

Metric / Capability	Value / Note
Faster deployment	~83% faster (DataRobot benchmark)
ROI / Cost	4.6x ROI, ~80% lower cost (vendor claims)
Key governance tools	Automated documentation, drift monitoring, challenger models, humility rules

“We succeeded in increasing our loan acceptance rate, so we sell more while keeping risk at the same level. In addition to other demographics, we're serving unbanked individuals, giving them access to legal capital and a chance to build their credit history.” - Tamara Harutyunyan, Chief Risk Officer and Chief Data Officer

SymphonyAI (Ayasdi) brings graph analytics to complex fraud and network detection - powerful for Singapore banks that need to connect the dots across fragmented data and speed investigations; their research stresses that choosing the right technique mix (for example, GraphSAGE and other graph methods) is key to spotting sophisticated money‑mule rings and layered scams (SymphonyAI graph analytics for financial crime detection).

By pairing NetReveal entity resolution and the Sensa Investigation Hub, investigators get a single‑subject view that visualises hidden relationships and routes alerts into a consolidated case workspace, while Sensa's Copilot cuts manual reviews and improves consistency.

The approach is outcome‑driven: SymphonyAI cites a ~50% lift in payment fraud detection, a 55% reduction in false positives and sub‑50ms scoring latency - metrics that matter when Singapore teams must scale monitoring without swamping analysts (SymphonyAI payment fraud detection and prevention).

In practice this means fewer noisy alerts, faster investigators and clearer audit trails to support compliance and incident response - a spiderweb of transactions becomes a clean, single‑subject story investigators can act on.

Metric / Capability	Value / Note
Payment fraud detection increase	50%
False positive reduction	55%
Detection & scoring latency	<50 ms
Out‑of‑the‑box scenarios	45+ fraud scenarios
Manual review reduction (Sensa Copilot)	~30%

Trusting Social brings a Singapore‑based hub (9 Temasek Boulevard) and a battle‑tested, telco‑data approach that can help local lenders extend credit to thin‑file customers: its Credit Insights / Trust Score uses masked, anonymised telco signals to infer creditworthiness across large populations - a method proven on “over 100 credit portfolios” and deployed at scale in markets where the company processes billions of telco records to enable millions of borrowers monthly; see Trusting Social Trust Score product page Trusting Social Trust Score product page and the CB Insights company profile for details on reach and funding.

For Singapore teams, the clear advantage is faster, more inclusive decisioning for underbanked segments, but pilots must bake in consent, anonymisation and robust eKYC controls to meet MAS‑style privacy expectations - the company's regional work (notably in the Philippines) shows the payoff and the governance tradeoffs in practice (Fintech News Philippines article on Trusting Social's use of AI and telco data).

Attribute	Detail
Founded	2013
Headquarters	9 Temasek Boulevard, Singapore
Primary product	Credit Insights / Trust Score (telco‑based)
Funding	~$214M total raised (Series D)
Operational reach	Vietnam, Indonesia, India, Philippines; 170+ FIs

“The traditional banking system was inherently blind to hundreds of millions of deserving individuals lacking financial history - that's the fundamental flaw Trusting Social was built to fix.” - Nguyen Nguyen, Founder & CEO

OCBC's internal GenAI rollout, OCBC GPT, is a practical blueprint for Singapore banks experimenting with large language models: launched for all 30,000 staff in November 2023 after a 1,000‑person pilot, the ChatGPT‑based assistant (built with Microsoft Azure OpenAI) helped trial users complete tasks about 50% faster and has already answered over one million prompts as teams use it for writing, research, code‑help and summarisation - a productivity lever that complements role‑specific copilots like Wingman and domain tools such as Buddy for internal policy lookups (OCBC 2024 Annual Report - Creating Value Through AI, Fintech News Singapore profile of OCBC GPT generative AI rollout).

OCBC pairs fast wins with governance: secure hosting, FEAT‑aligned controls, and upskilling so staff become prompt‑savvy - a model Singapore institutions can mirror when moving GenAI from pilot to production without sacrificing auditability.

Metric	OCBC Figure / Note
Employees supported	30,000 (global rollout)
Pilot size	~1,000 staff
Productivity uplift	Tasks ~50% faster (trial)
Prompts answered	>1 million (as of May 2024)
AI decisions (daily)	~4 million now; projected 10 million by 2025
Customer insights	~250 million personalised recommendations per year

“We are excited to be one of the first banks in the world to deploy generative AI tools at scale. We believe that these tools have the potential to transform the way our employees work by automating a wide range of time‑consuming tasks, freeing up their time to focus on more strategic and value‑added work.” - Donald MacDonald, Head of Group Data Office

Begin with a single, measurable pilot - pick a clear pain point (AML triage, document automation or thin‑file credit decisions), scope it tightly, and bake MAS' FEAT expectations into the project from day one: Fairness, Ethics, Accountability and Transparency were adopted by MAS in 2018 and now sit at the centre of Singapore's playbook, so use the MAS Veritas Toolkit to run FEAT assessments and make audit‑ready decisions rather than hoping compliance will follow later (MAS Veritas Toolkit for responsible AI in Singapore's financial sector).

Keep the tech stack simple, instrument monitoring for drift and bias, and treat third‑party models as hot potatoes - contract clauses, compensatory testing and contingency plans are non‑negotiable.

Upskilling beyond slideware matters: short, practical programmes that teach prompt craft, prompt‑driven workflows and hands‑on validation enable product owners and compliance teams to collaborate quickly; consider the AI Essentials for Work syllabus as a pragmatic route to build those workplace skills (AI Essentials for Work bootcamp syllabus - Nucamp).

Start small, prove measurable ROI, document every decision for FEAT, and scale only when monitoring, governance and people are ready - this is how Singapore teams turn pilots into production without tripping regulatory or reputational alarms.

Program	Length	Early bird	Register
AI Essentials for Work	15 Weeks	$3,582	AI Essentials for Work bootcamp registration - Nucamp