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AI for Fintech & Finance

AI that's accurate enough to touch real money.

Fraud detection, underwriting support, and reconciliation automation, built by engineers who treat a wrong answer as a real financial event, not an edge case, and who instrument every model to prove it before it touches production data.

Same vetting bar either way, whether we staff the project or fill the seat. See the rubric

Documents flowing into a processor and out as answers in a chat interface
Fraud detection

Anomaly and pattern models tuned to your actual transaction data.

Underwriting support

Risk-scoring models with explainability built in, not bolted on.

Reconciliation

Automated matching with human review on every exception.

Auditability

Every automated decision traceable for compliance review.

What we build

What we build most for fintech teams.

Pattern-detection models trained and validated on your actual transaction history, with a false-positive rate tuned to what your ops team can actually review.

Anomaly detectionReal-time scoringModel validation
See fraud work

Risk-scoring systems with explainability built in from the start, a score without a reason isn't defensible in a regulated lending decision.

Risk scoringExplainabilityModel governance
See underwriting work

AI-assisted matching for transactions and ledger entries, with every exception routed to a human rather than silently auto-resolved.

Auto-matchingException handlingAudit trail
See reconciliation work

Internal tools that give support and ops teams instant, grounded answers from account and transaction data, the same discipline behind our own client work.

RAGInternal copilotsAccount data
See copilot work
What we build with

Current tools, not last year's.

Models
XGBoostClaudeGPTCustom ML
Data
PostgresKafkaFeature stores
Compliance
Audit loggingModel governanceExplainability
Infra
AWSEncryptionSOC 2-ready infra
Proof

Shipped, not slideware.

Agentic support layer
AI Agents

Agentic support layer

An agentic support layer for a B2B fintech that resolves routine tickets with zero human touch, with every low-confidence case routed to a human.

LangChainRAGPython
Read the case study
What clients say

On camera, in their own words.

Client video

Why he brought his development work to Code Elevator.

MikePlays here
How we run it

Scoped fast. Shipped on a real timeline.

011–2 weeksRisk-aware discoveryWe map the financial workflow and the cost of a wrong answer before proposing any model.
022–4 weeksPrototype and back-testingA model validated against historical data with a defined accuracy bar agreed before build starts.
034–10 weeksProduction hardeningExplainability, audit logging, and human-review gates built in before anything touches live transactions.
04OngoingMonitoring and retrainingOngoing drift monitoring, financial patterns shift, and a static model degrades quietly if nobody's watching.
Related services

Building something adjacent?

Questions

Answered before you ask.

Back-testing against your historical data with a defined accuracy and false-positive bar agreed with your team before build starts, the model doesn't go live until it clears that bar on data it hasn't seen.

Only within pre-agreed, bounded thresholds, anything above a risk or value threshold you set routes to a human. We design the threshold with you, not unilaterally.

Risk and underwriting models are built with explainability as a requirement, not an add-on. Every score comes with the factors that drove it, in a form your compliance team can actually review.

We build on SOC 2-ready infrastructure with encryption and audit logging as defaults, and work within whatever additional controls your compliance and security teams require.

What you're not risking

Every way out of this build is already written down.

You own it, from day one

Code, prompts, models and pipelines: all work-product IP assigns to you by contract from day one, not on final payment.

No vendor lock-in

Nothing is locked to us or to a proprietary platform you can't leave. You get the repository, the documentation, and full access.

Get started

Bring us the financial workflow. We'll tell you what's realistic.

Fraud, underwriting, or reconciliation. We'll validate against your real data and tell you the honest accuracy bar before it touches production.

We reply within an hour during our working day in India and the UAE.

Chat with our team