How are compliance costs estimated?

From a published 2024 industry survey of 47 firms, supplemented by FINRA's annual report on algorithmic trading examinations. The methodology page documents both sources. Costs are reported as ranges because actual costs vary 5-10× across firms of similar size.

Why is the cost ratio not stable across firm sizes?

Fixed-cost components (legal review, surveillance system) dominate at small firms; variable costs (per-trade documentation, model audit) dominate at large firms. Below $100M AUM, NLT compliance is roughly 3× more expensive than FTC; above $1B AUM the gap narrows because fixed costs amortize.

What's a common mistake when using FTC vs FCA vs MiCA+DORA Regulatory Cost?

Reading the snapshot as authoritative for the current date. Regulation changes — check the as-of date and cross-reference with the regulator's site before relying on the number.

How do jurisdiction overlaps inflate the total?

Sizing only year-1. The recurring compliance cost in years 2+ matters more for long-term margin; year-1 is mostly one-off setup.

AI in Markets Calculator Guide

How to use FTC vs FCA vs MiCA+DORA Regulatory Cost

Compare US (FTC), UK (FCA), and EU (MiCA + DORA) compliance cost for an AI-finance product. Snapshot data with as-of date so you can size the regulatory burden before committing eng-weeks to a deployment that won't ship.

5 STEPSPublished May 12, 2026Live Content

By Orbyd Editorial · AI Fin Hub Team

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FTC vs FCA vs MiCA+DORA Regulatory Cost

Compare US (FTC), UK (FCA), and EU (MiCA + DORA) compliance cost for an AI-finance product. Snapshot data with as-of date — not legal advice.

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On This Page

Overview 5 steps Scenarios FAQ

What It Does

Use the calculator with intent

Founders and engineering leads scoping a multi-jurisdiction AI-finance product who need a realistic compliance cost number before committing.

Interpreting Results

Headline cost is the year-1 estimate (initial filing + first-year ops). Year-N steady-state is materially lower for most categories. Use the as-of date — regulatory frameworks shift quickly; cross-check against a current source before committing.

Input Steps

Field by field

1

Enter inputs

Enter your firm's AUM, strategy count, and primary trading region.
2

Set parameters

Set the assumed regulatory regime: current FTC, proposed NLT, or both for comparison.
3

Read outputs

Read setup cost (year 1), ongoing annual cost (year 2+), and incident reserve (averaged across the industry).
4

Compare results

Compare FTC vs. NLT side-by-side. The cost ratio shifts with firm size — small firms pay disproportionately more under NLT.
5

Re-run

Re-run if the AUM grows by 50% or more — the cost curves are non-linear.

Common Scenarios

Use realistic starting points

Robo-advisor in US only

Product

robo-advisor

Jurisdictions

FTC + state-level RIA registration; cost moderate, well-trodden path. Most cost is initial setup; recurring cost is low.

AI-trading agent in EU

Product

AI trading agent

Jurisdictions

DORA (operational resilience) + MiCA framework; cost meaningfully higher than US. EU compliance is the gating constraint for many AI-finance products.

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FAQ

Questions people ask next

The short answers readers usually want after the first pass.

Two competing regulatory disclosure regimes for algorithmic trading: FTC's traditional reasonable-care framework versus the NLT (Non-Linear Tools) proposal that would impose stricter explainability requirements. The calculator compares compliance cost and operational burden under each.

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Regulatory Cost of AI in Finance

Regulatory cost as a function of jurisdiction, model class, and end-use: the FTC vs NLT distinction and the documentation burden by regime.

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The agent-cost envelope: the loop of (calls × tokens × retries × model_price) that determines the dollar cost of an LLM-driven trading agent per decision.