Which upstream and downstream systems must an evaluation harness model around booking?
A harness needs the approval source, the loan system, security and payment records, and a servicing view, linked by stable identifiers so state changes can be traced and checked.
A booking task is only realistic if the agent can see what a real analyst sees and the harness can see what happens next. A minimal model has five parts.
- **Approval source.** Records such as `approval_id`, `applicant_id`, approved limit, product code, pricing tier, authority level and a `conditions[]` array with `condition_id`, text and status. - **Loan system of record.** `facility` records keyed by `facility_id`, with `approval_id`, limit, term, repayment frequency, first payment date and `status`. - **Security and documents.** `security_item` and `document` records linked by `facility_id`, with lodged and registered flags. - **Payments.** `settlement_instruction` and `disbursement` records, linked by `facility_id`, with release status. - **Servicing view.** Read-only schedule and statement previews that appear only after booking.
Stable identifiers matter most. If `approval_id` and `facility_id` are carried through every table, a grader can follow a booking from decision to first statement.
Tool actions can mirror the work: `get_approval`, `list_conditions`, `create_facility`, `link_security`, `set_status`, `hold_file` and `return_to_credit`. Each call should write to an event log so graders can inspect order as well as outcome. Generated data should be checked for grounding before it is trusted as realistic.
Modelling the neighbouring systems, not only the loan system, lets you detect failures that show up after the booking write succeeds.
- Audience:
- Evaluation teams
- Content type:
- Integration
- Buyer question:
- What it is and why it matters
Content release: r-a220eb6e099b243b
Related questions
- What is loan booking and why does it matter for testing AI agents?
- How does the booking workflow map onto record links and agent tool actions?
- What does a booking error look like when an agent misses an approval condition?
- What makes recording an approved facility hard for an AI agent?
- Why is this workflow a better test for agents than question answering?
- What does booking an approved facility involve in a real lender?