AI for Banking & Financial Services
Document AI, real-time fraud scoring, and Thai-language service agents, built with explainability, human review, and in-country hosting from day one.
About the industry
Thai banks, insurers, and fintechs run on trust, speed, and regulation. Customers expect instant service on LINE and mobile, scammers move money faster than manual checks, and every automated decision must be explainable to a regulator. AI helps on all three fronts when it is built with controls from day one.
In practice, AI in financial services is a set of well-scoped systems: Thai document AI for onboarding, real-time models for fraud and credit, and language agents for service. They connect to your core banking, CRM, and case tools, and humans approve the decisions that matter.
Thai OCR and KYC document checks
Fraud, mule-account, and credit-risk models
Thai-language agents on LINE, app, and phone
Explainability, model documentation, audit trails
AI in action
Your data goes in, a model reads it, and a decision comes out with a record your team can audit.
Why AI, why now
Static rules miss new patterns. Graph analytics and ML scoring catch networks, not just single transactions.
ID cards, house registrations, and statements slow onboarding. Thai OCR and LLMs automate extraction with checks.
Explainability, model risk controls, and data residency are requirements, not extras.
How we help
We are consultants first. We help you decide where AI pays off in your bank, insurer, or fintech before any model is built, and how to deploy it so risk, compliance, and IT can sign off.
Map fraud loss, onboarding cost, and contact-centre volume to AI candidates with your business and risk teams.
Review transaction data, document flows, CRM, and core-banking access, and what must be fixed before modelling.
Rank use cases by loss avoided, cost to serve, and time to value, with a board-ready investment case.
Explainability, model documentation, PDPA controls, and hosting design aligned with Bank of Thailand AI guidance.
Run the pilot with your investigators and agents, define human-in-the-loop rules, and set the KPIs that decide scale-up.
How we work
Eight steps. You can stop after any of them and keep what we produced.
One sentence in the builder, or a call.
Architecture, stack, timeline, budget range.
30 minutes online with a senior consultant.
Data, systems, and constraints, on site or online.
A design your IT and security teams can sign off.
Fixed scope, milestones, and price in THB or USD.
Pilot in weeks, then production rollout.
Support, model monitoring, and new use cases.
What we build
ME0-1234567-89Thai OCR and a Thai LLM extract and cross-check data, with human review for exceptions.
Thai ID cards, house registrations, and bank statements are retyped and checked by hand, which slows onboarding and invites errors.
Real-time ML scoring and graph analytics, with an explainability dashboard investigators can act on.
Scam transfers and mule accounts move faster than rules can be updated, and investigators drown in false alarms.
An AI agent on LINE, app, and phone that resolves routine questions and hands complex cases to staff with context.
Branches and call centres are swamped by routine questions while complex cases wait.
SME credit scoring and early-warning models with documented features and monitoring for drift.
SME lending relies on thin files and manual judgement, and warning signs on existing loans show up late.
AI use cases
Outcome Faster onboarding, fewer errors, and an audit trail aligned with Bank of Thailand AI guidance.
Outcome Earlier fraud interception with fewer false positives.
Outcome Routine enquiries resolved instantly, staff freed for complex cases.
Outcomes describe what each solution is designed to improve. Figures appear only where they come from a delivered project. Results depend on your data, systems, and scope.
Responsible AI
FAQ
Yes, as a decision-support layer. AI extracts and validates document data and flags inconsistencies, while approval stays with your compliance team and an audit trail is kept.
By combining transaction features with network signals, tuning thresholds against your investigator capacity, and feeding investigator outcomes back into the model.
Yes. It answers in Thai and English on LINE OA, in your app, and by phone, grounded in approved product and policy content.
Other industries
AI for Banking & Financial Services
Eight to twelve weeks.A measurable target on your own data.