TestAIIdeas.ProveWhatWorks.ScaleTheWinners.
Arcana designs experiments that prove what works, kill what doesn’t, and move the winners into production—fast.
The gap between a promising demo and a production-ready system is vast. We bridge that gap for banks and regulated fintechs by rigorously testing AI use cases against real-world constraints.
From initial hypothesis to audited pilots, we structure the validation sprints that tell you exactly where to invest your capital and engineering resources.
The Opportunity Cost of Inaction
Industry benchmarks vs. what we deliver
Automating highly manual, multi-step workflows
We focus on high-friction, high-scrutiny workflows where validated AI can materially change loss rates, capacity, and customer experience.
Fraud Detection
Reduce false positives while surfacing novel attack patterns that legacy rules and static models never see.
The Problem
False positives bury real fraud.
AML Monitoring
Detect complex structuring and layering patterns that rules-based systems routinely miss, without overwhelming teams with noise.
The Problem
Rules-based systems miss complex structuring.
KYC & Onboarding
Automate document and identity checks with human-in-the-loop review for edge cases, so growth doesn’t stall at manual queues.
The Problem
Manual review slows growth.
Compliance Monitoring
Move from sampling a sliver of interactions to monitoring essentially all relevant communications for regulatory triggers—without adding headcount.
The Problem
Sampling <1% of calls risks fines.
Credit Underwriting
Use alternative and behavioral data to safely approve more of the right borrowers, not just more volume.
The Problem
Thin files get auto-rejected.
Customer Support
Deploy agents that resolve complex, regulated queries with full context and auditability—not ‘just another chatbot.’
The Problem
Generic chatbots frustrate users.
The execution gap
The gap between "demo" and "deployed" keeps widening. For most banks, three forces drive the stall-out.
Velocity Mismatch
Models advance weekly. Procurement moves quarterly. By the time a tool clears your process, the underlying capability has already moved on.
Capability Explosion
Frontier models now reason over massive contexts and complex workflows, unlocking use cases that did not exist in last year’s roadmap. Most banks have no mechanism to continuously retest where AI can create real lift.
Vendor Noise
Every week, another AI vendor promises 'transformational' impact. Separating repeatable signal from marketing noise has become its own full-time job.
Prototypes over presentations
Slideware doesn’t de-risk AI. Controlled experiments do. Arcana is built to design and run the experiments that give you confident green-lights—or clean kills.
Structured Experiments
We define crisp hypotheses, counterfactuals, and success thresholds so every test yields a clear yes/no on ROI in weeks, not quarters.
Domain Expertise
Experiments are designed against real-world constraints—model risk, compliance, security, and supervisory expectations—not lab conditions.
Vendor Intelligence
We continuously scan the open-source and vendor landscape, then plug in only the components that actually move the needle for your use case.
Production Velocity
We build just scrappy enough to learn quickly—and just robust enough to take proven prototypes into audited, production-grade stacks.
Ready to validate your AI roadmap?
Let's discuss your use case
Bring one real use case. In 30 minutes, we'll map a concrete validation plan—what to test, how to measure it, and what 'production-ready' actually means for your institution.