This site and domain are for sale. Inquire: [email protected]
Home › Benchmarks › Banking › Transaction Fraud Monitoring
Banking

How much does an AI agent cost to run Transaction Fraud Monitoring?

Token cost benchmark for an autonomous Transaction Fraud Monitoring agent, across 24 models. Prices as of 25 Oct 2026.

An agent for Transaction Fraud Monitoring on the clean path costs about $0.0062 to $0.625 per outcome depending on the model, around 8.0x the cost of a single chat message. At 10,000 outcomes a month that is roughly $62 to $6,250.
Estimate your own numbers →

Cost per outcome by model

Model$/1M in$/1M outCost / outcomeCost / month*
Claude Haiku 5.5$0.10$0.50$0.0062$62
GPT-6 Luna$0.10$0.50$0.0062$62
Llama 4 Maverick$0.25$0.87$0.0145$145
DeepSeek V4.1 Flash$0.30$1.20$0.0179$178
Gemini 2.5 Flash$0.30$2.50$0.0218$218
Mistral Large 3$0.50$1.50$0.0282$282
Gemini 3.8 Flash$0.75$3.75$0.0469$469
Claude Haiku 4.5$1.00$5.00$0.0625$625
DeepSeek V4 Pro$1.32$3.96$0.0746$746
Mistral Large 4$1.36$4.18$0.0771$771
Gemini 2.5 Pro$1.25$10.00$0.0894$894
Grok 4.7$2.00$6.00$0.113$1,130
Claude Sonnet 5.5$2.00$10.00$0.125$1,250
Claude Sonnet 5$2.00$10.00$0.125$1,250
GPT-6.1 Sol$2.00$10.00$0.125$1,250
Gemini 4 Argon$2.00$10.00$0.125$1,250
Gemini 3.1 Pro$2.00$12.00$0.131$1,310
Claude Sonnet 4.6$3.00$15.00$0.188$1,875
Claude Opus 5.5$4.00$20.00$0.250$2,500
Claude Opus 5$5.00$25.00$0.312$3,125
Claude Opus 4.8$5.00$25.00$0.312$3,125
Claude Fable 5.1$10.00$50.00$0.625$6,250
Claude Fable 5$10.00$50.00$0.625$6,250
GPT-6 Astra$10.00$50.00$0.625$6,250

*At 10,000 outcomes per month. Cheapest model highlighted.

What this agent does

The clean-path steps this benchmark prices:

  1. Enrich (account, device, geo)
  2. Score Fraud Risk
  3. Low risk?

What drives the cost

This path runs 3 steps: 2 tool calls and 1 decision point. Tool steps make two model calls each, and the agent re-reads its growing context on every call. That compounding is why one Transaction Fraud Monitoring outcome costs about 8.0x a single chat message ($0.188 on Claude Sonnet 4.6), not the price of one message.

Why these numbers matter.

How this benchmark is calculated

These figures are modeled estimates, not metered bills. We price a generic, representative Transaction Fraud Monitoring workflow across 24 models using the same cost engine as the live estimator, at each model’s published list price (checked 25 Oct 2026), under documented default assumptions for planning loops, tool calls, memory retrieval, sub-agents and context size. Your own process will differ, so use these as starting points, tune the assumptions in the estimator, and validate against your real usage. Illustrative estimates, not financial advice.

Frequently asked questions

How much does an AI agent cost to run Transaction Fraud Monitoring?

On the clean path with default assumptions, an agent for Transaction Fraud Monitoring costs about $0.0062 to $0.625 per outcome depending on the model, or roughly $62 to $6,250 per month at 10,000 outcomes. The cheapest model here is Claude Haiku 5.5 at $0.0062; the most expensive is GPT-6 Astra at $0.625.

Why does an AI agent cost more than a single chatbot message?

An agent does not make one model call. It plans, calls tools, retrieves context and re-reads its growing working context on every step. For Transaction Fraud Monitoring that adds up to about 8.0x the cost of a single chat message.

Which model is cheapest for Transaction Fraud Monitoring?

Across the 24 models benchmarked, Claude Haiku 5.5 is cheapest at $0.0062 per outcome and GPT-6 Astra is the most expensive at $0.625. A cheaper model is not always the right choice, but it sets the floor for this workflow.

How can I reduce the cost of an agent for Transaction Fraud Monitoring?

The biggest levers are prompt caching on the base context, fewer planning loops, smaller tool results, less retrieval, and choosing a cheaper model where quality allows. You can test each lever in the live estimator.

What is this Transaction Fraud Monitoring benchmark based on?

These are modeled estimates, not metered bills. Each figure prices a generic, representative Transaction Fraud Monitoring workflow across 24 models with the same cost engine as the live estimator, at each model's published list price (checked 25 Oct 2026), under documented default assumptions for planning loops, tool calls, memory retrieval, sub-agents and context size. Your own process will differ, so treat these as starting points, tune them in the estimator, and validate against your own usage.

More Banking benchmarks

Open Transaction Fraud Monitoring in the live estimator →