TeracDomain experts
Transaction Finance Professionals: AI Output Annotation and Ranking
$100/task
About this role, in Terac's words
We are running a paid study to evaluate and improve AI models specialized in the transaction finance domain. We need experienced finance professionals to review, rank, and annotate AI-generated financial outputs for accuracy and relevance.
What you'll do
What you would do
- Review AI-generated financial outputs for accuracy and logical consistency
- Rank multiple model responses based on their relevance to transaction finance workflows
- Annotate specific data points to correct errors or highlight hallucinations
- Provide brief written feedback explaining your ranking decisions
Candidate background
What this role asks for
- Transaction Finance
- Investment Banking
- Financial Analysis
- AI Annotation
Read from the posting's own words: show the exact sentences
- Transaction Finance: “listed by the platform under required skills: Transaction Finance”
- Investment Banking: “listed by the platform under required skills: Investment Banking”
- Financial Analysis: “listed by the platform under required skills: Financial Analysis”
- AI Annotation: “listed by the platform under required skills: AI Annotation”
Quoted from selected sections of Terac's posting. The full posting may state other conditions. Read the full posting
A closer look
More context, when you need it.
Full job descriptionThe original posting, in Terac's words
Posted by Terac, reproduced here so you can judge the role before clicking. Original posting ↗
We are running a paid study to evaluate and improve AI models specialized in the transaction finance domain. We need experienced finance professionals to review, rank, and annotate AI-generated financial outputs for accuracy and relevance.
What We're Researching
We're hiring finance experts to evaluate AI-generated outputs related to transaction finance. Our goal is to improve how artificial intelligence processes complex financial data and structures transaction-related information. This work directly feeds into training more accurate and reliable financial models for the industry. How It Works
During this paid study, you will review various AI-generated documents and data points specific to transaction finance. You will be asked to rank these outputs based on their factual accuracy, industry relevance, and overall quality. Additionally, you will provide detailed annotations to highlight errors or areas where the model's logic breaks down. The work is conducted asynchronously through our remote platform, allowing you to complete tasks at your own pace. Who This Is For
This opportunity is tailored for professionals with direct experience in transaction finance, investment banking, or corporate development. We welcome financial analysts, transaction advisory specialists, M&A professionals, and corporate finance managers. Ideal candidates have a sharp eye for detail and a strong understanding of financial modeling and transaction workflows.
What you would do
• Review AI-generated financial outputs for accuracy and logical consistency
• Rank multiple model responses based on their relevance to transaction finance workflows
• Annotate specific data points to correct errors or highlight hallucinations
• Provide brief written feedback explaining your ranking decisions
Who this is for
• Active professional experience in transaction finance, M&A, or investment banking
• Strong understanding of financial modeling and deal structuring
• Comfortable reviewing technical financial documents and data
• Excellent written communication skills for leaving clear annotations
Working with TeracPay, getting started and work, from Terac's own pages
What the platform publishes in general. These are not extra terms confirmed for this particular role.
- Getting paid
- Paid through Virtual Incentives: PayPal, Venmo, a prepaid Visa card or direct cashout in the US, PayPal elsewhere. A payout starts once a submission is approved, and cashing out needs a $12.50 balance and a verified ID. terac.com/docs/experts/policies/payout-policy, terac.com/docs/experts/how-to/payments, terac.com/whats-new/2026-05-31-may-2026-updates
- Before your first paid task
- A verified government ID through Persona before you can apply, then a screening step for each study: a short form, an AI voice interview or a file upload. A study you are screened out of is not paid. terac.com/docs/experts/how-to/apply, terac.com/docs/experts/policies/rewards
- How much work
- Terac guarantees no number of opportunities and no earnings. Manually reviewed applications hear back in 1 to 5 business days. terac.com/docs/experts/policies/terms, terac.com/docs/experts/support/faq
- Contract
- Independent contractor, with Terac Inc. of California. terac.com/legal/terms-of-service
Read on the pages linked above on 23 Sep 2026. Platforms change these terms, so check the linked page before you rely on one.
How does the pay compare?Across Domain experts roles, not this role alone
From our own daily reads of every open listing on the platforms we follow, not from Terac's posting. How we count.
Pay across the field: Domain experts
Across 699 roles in this field with a stated hourly rate in US dollars, on 18 platforms, the middle half pays $65 to $130 an hour at the top of the range, and the median is $100.
| Platform | Roles | Top of range, per hour |
|---|---|---|
| Alignerr | 149 | $24 to $200 · median $80 |
| micro1 | 136 | $28 to $400 · median $110 |
| AfterQuery | 88 | $45 to $175 · median $100 |
| Handshake AI | 79 | $30 to $300 · median $85 |
| Mercor | 78 | $55 to $450 · median $120 |
Sources and listing historyWhere this information comes from
This listing's history
- First seen here on 18 Sep 2026, and still on Terac's list when we last read it on 13 Oct 2026.
- The listed pay has not changed since then.
- Posted by Terac
- First seen by AIPayList
- Last seen live
- Listing ID
- qg91SGqSN9ORZ_X1
Pay as the source states it: “Terac listing record, advertisedRate 100.00 USD PER_TASK”.
Platforms sometimes change a rate after posting. Every listing here is re-read at least once a day and corrected when its source moves, so a difference you see on the platform is usually a change made since the last read. How freshness works.
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