Industries / Banking and fintech
AI for banking and fintech, with controls first.
AI in banking and fintech with controls first: document checks, transaction reviews and support that move faster, with people approving every decision that affects a customer or a regulator.
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What we can build for AI in banking and fintech. We have not yet delivered an AI project for a bank. These are capabilities, backed by related fintech and AI work.
KYC document checks
Identity and onboarding documents read and checked, with anything unclear routed to a person.
Transaction flags for review
Unusual transactions flagged with the reasons, for your team to review and decide.
Loan and onboarding files
Data extracted from applications and supporting documents, with exceptions routed to people.
Support assistants
Answers to routine account and product questions, with a handover to staff.
Compliance reporting
Evidence gathered and reports drafted for your compliance team to review.
Knowledge assistants
Answers from policies and procedures, with a link to the source.
Audit trail
Every recommendation and approval recorded, so decisions can be traced.
Access controls
Role-based permissions and approval checkpoints for high-stakes actions.
Built on your systems
Designed to work with the core, card and CRM systems you already run. Integrations are agreed during discovery.
Complaint triage
Complaints classified and routed with the key facts captured.
Collections support
Reminder conversations drafted and tracked, with hardship cases passed to people.
Regulatory change tracking
Rule changes mapped to your policies, with gaps flagged for compliance.
Match the autonomy to the task. AI in banking prepares and flags. People decide.
- L1WorkflowA fixed, auditable path.
- L2AssistantAI drafts. A person reviews.
- L3Supervised agentAI acts and flags exceptions.
- L4AutonomousRoutine, low-risk, monitored.
- Human-ledPeople decideAI supports the analysis.
Document intake and extraction
A fixed, auditable workflow, with AI reading the documents.
L1 WorkflowKYC checks
A governed workflow, with an agent flagging anything unclear.
L1 WorkflowL3 Supervised agentTransaction monitoring
Agents flag unusual activity with the reasons. Analysts review.
L3 Supervised agentCredit, fraud and account decisions
Stay with people. AI prepares the evidence.
Human-led
Related work. We have not delivered an AI project for a bank yet. These fintech and AI engagements built the same kinds of systems.
Centralized crypto exchange
Matching engine, custody and KYC/AML built from scratch in a 20-week build.
99.9% uptime since launch Web3 · PaymentsStablecoin payment rails
Multi-currency stablecoin settlement, built and shipped in five weeks.
<1 sec settlement AI · InsuranceFull-stack AI platform for insurance
Fragmented policy, claims and correspondence data connected into one structured workflow.
~2.5x faster processingWant AI in banking for a process that runs on manual checks?
The technology behind our AI systems. Chosen per task, not per trend.
01 / 08
Models
The language models behind each feature, picked per task on cost, speed and quality.
- OpenAI
- Anthropic Claude
- Google Gemini
- Meta Llama
- Mistral AI
- OpenRouter
- Hugging Face
02 / 08
Agents and orchestration
How agents plan, call tools and hand work to each other.
- LangChain
- LlamaIndex
- CrewAI
03 / 08
Machine learning
Custom models for prediction, vision and classification.
- PyTorch
- TensorFlow
- scikit-learn
- OpenCV
04 / 08
Vector search and databases
Where your data lives, and how answers stay grounded in it.
- Pinecone
- Qdrant
- PostgreSQL
- Redis
- MongoDB
05 / 08
Data pipelines
Moving and preparing data so models see the right, fresh inputs.
- Databricks
- Snowflake
- Apache Spark
- Apache Kafka
06 / 08
Cloud and infrastructure
Where it runs, in your cloud or ours.
- AWS
- Microsoft Azure
- Google Cloud
- Docker
- Kubernetes
07 / 08
Evals and operations
Tracing, testing and monitoring once it is live.
- Langfuse
- MLflow
- GitHub
08 / 08
Product and apps
The product your users actually touch.
- Python
- FastAPI
- React
- Next.js
From first use case to production. Four stages, with a working version reviewed at each one.
-
Discovery
Map the process, the systems and data involved, and what good looks like.
Discovery notes
- The decisions and data involved
- Where manual checks sit today
- Regulatory and approval rules
-
Scope & architecture
Agree the architecture, success measures and delivery milestones.
Solution design
- Architecture and data access
- Approval checkpoints
- Success measures
-
Build
Build against real data, with a working version reviewed at each milestone.
Working build
- Working version on real data
- Compliance review
- Accuracy tests
-
Ship & support
Roll out to production with monitoring and a defined support window.
Production rollout
- Production rollout
- Monitoring
- Support window
Why Avinya for banking and fintech. Fintech systems with compliance built in, already in production.
KYC/AML built in
Our crypto exchange shipped with KYC/AML checks at onboarding, ready at launch.
Payments at speed
Our stablecoin rails settle across multiple currencies in under one second.
Card and wallet apps
A crypto-to-Visa card app with Apple Pay and Google Pay. Client name withheld.
Audit trail by design
Our insurance platform logs every record change, with role-based access.
Engagement models. Pick the shape that fits where you are.
Dedicated team
A dedicated team that works as an extension of yours, from first release to scale.
Project-based
A defined scope, milestones and delivery date for a specific product or workflow.
Consulting & advisory
Architecture and readiness advice before you commit to a build.
What our clients say.
AI platform for an insurance broker
“Avinya Labs built our full-stack AI solution … Their expertise accelerated our launch and significantly reduced execution risk.”
Guides on this topic. Plain answers to the questions buyers ask first.
Stablecoin Payments: Why Businesses Are Moving to Rails Now
Why banks, fintechs and merchants adopt stablecoin payments, and what the GENIUS Act changes.
Read the guide → GuideHow Intelligent Document Processing Works (2026 Guide)
Classify, extract, validate and route exceptions to people, and where it pays off.
Read the guide → GuideEnterprise AI Deployment: Why Projects Stall in Pilot
The eight causes we see most, and a roadmap that gets AI live.
Read the guide →AI for banking and fintech FAQs.
Have you built AI for a bank before?
Not yet. We have built fintech systems, a compliant crypto exchange, stablecoin payment rails and a card app, and AI platforms with audit trails in insurance. Those engagements are linked on this page.
How is AI used in banking?
Mostly to speed up checks and service: reading KYC and onboarding documents, flagging unusual transactions for analysts, extracting data from loan files, drafting compliance reports and answering routine customer questions. Credit, fraud and account decisions stay with people.
Will AI make credit or fraud decisions?
No. AI prepares the evidence and flags what needs attention. Credit, fraud and account decisions stay with people.
Do you handle regulatory compliance?
We design compliance into the system: KYC/AML flows, audit trails and access controls. We work alongside your legal counsel. We do not give legal advice.
Where should we start?
With one task where the data exists and the risk is contained. We map it, agree what good looks like, and build a working version you can review before anything scales.
How do you handle our data?
Access is scoped to what the system needs, with role-based permissions and audit trails where records change. We agree data handling during discovery.
How long does a banking AI project take?
A prototype on sample documents takes about 6 to 9 weeks and a first version about 8 to 12 weeks. Production, with approval checkpoints and an audit trail, typically takes 3 to 5 months.
Can we sign an NDA first?
Customer and transaction data is sensitive. Yes. We can sign an NDA before you share anything, and we agree ownership of the work in the contract before the work starts.
How do you apply AI in banking without losing control?
AI prepares and flags; people approve anything with financial or regulatory impact. AI in banking and AI for fintech are scoped with the NIST AI Risk Management Framework to document risk.
Free tool
How ready is your business for AI?
Twenty questions, about four minutes. You get a score across five areas and what to fix first.