Finic
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Frontier AI to stop fraud, abuse, and financial crimes.

Finic delivers human-level judgment in milliseconds, for 1/100th of a cent. No data wrangling needed.

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How it works

A new approach to real-time decisioning.

We developed a new technique for fraud detection called Question-Bottleneck Scoring (QBS) that brings human-level judgment to real-time decisioning.

Finic makes decisions the same way humans do:

  1. 01DecomposeBreaks risk down into plain-English questions.
  2. 02AnswerAnswers each question using the data available at that checkpoint.
  3. 03SynthesizeCombines the answers to make a final good-or-bad judgment.
POST /scoreRisk scoreA calibrated 0–1000 risk score for every record.
POST/v1/scoreLive
POST /askQ&AYour own questions about a case, with a probability for every answer.
POST/v1/askLive
/monitorContinuous monitoringComing soon.
Zero-shotMatches or exceeds models trained on your data, without training on your data.
ComposableUse Finic's risk score by itself, or incorporate it into your decisioning pipeline to cover gaps where existing models are weak.
ExplainableScores are built from plain-English questions easy for any auditor to understand.
Benchmarks

Faster, smarter, and cheaper.

Finic is built on Grayson, our own decision model that's up to 200x cheaper and 50x faster than LLMs.

99.4%*
As many correct decisions as human analysts
$0.11
Per 1,000 decisions
0.15 s
Response time
Zero
Training, fine-tuning, or feature engineering needed
vs. Human analystsHuman-level accuracyMatches your reviewers on accuracy, at 712× the volume and a fraction of the cost.
vs. AI agents107× cheaperMore decisions right than an AI agent, at under 1% of the cost.
vs. Traditional ML13% fewer mistakesThe same volume as XGBoost, with 13% fewer mistakes.

*Side-by-side test on production data at a Fortune 500 company, against its human reviewers and its best in-house model (an XGBoost model trained on the company's own data).

†Human cost assumes analysts at $30 an hour, each making 10 decisions an hour. XGBoost cost is an estimate of the all-in cost of training, serving, and maintaining a machine learning model. AI agent cost is an estimate at Claude Sonnet 5.5 API pricing, about $11.75 per 1,000 decisions; its volume assumes about 8 seconds per response.

Use cases

What use cases will you discover?

Customer onboardingCatch bad actors at the point of entry, not after the damage is done.
Customer lifecycle reviewMonitor every customer, continuously. Catch bad actors, unblock power users, and reach customers when they're most receptive.
Bot & AI agent detectionKnow the moment control passes from a customer to a bot or AI agent.
Transaction monitoringReview every payment with the customer's recent activity, in a fraction of a second, before it goes through.
Ops automationTriage alerts, classify tickets, and flag bots or agents that go off-script.
Insider threat detectionWatch employee and contractor activity for social engineering and unusual behavior.
User-generated contentFind users abusing other users, or your platform, in content and conversations.
Finic

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