A comprehensive guide to interpreting Trutina risk scores, flag categories, severity levels, and recommended actions. Written for credit analysts and compliance officers.
Risk Score Overview
•Scores range from 0 to 100, where 0 is lowest risk and 100 is highest risk.
•The composite score is derived from 5 detection categories, each with its own maximum point cap.
•Each flag has a severity and weight that contribute to the category total.
•Scores are deterministic — the same inputs always produce the same score.
Score Thresholds
0 – 19
20 – 44
45 – 69
70 – 100
Low Risk
Medium Risk
High Risk
Critical Risk
0 – 19Low Risk
Action: Approve
Documents appear genuine. May have minor informational flags that do not indicate fraud.
Common reasons
–Minor metadata quirks (e.g., unusual PDF producer but consistent content)
–Salary marginally above median but within 75th percentile
20 – 44Medium Risk
Action: Manual Review
Some anomalies detected that warrant human verification. Most turn out benign but should be documented.
Common reasons
–Salary above ABS benchmarks for stated occupation
Significant issues detected. Multiple flags across categories suggest the document may not be genuine.
Common reasons
–Employer ABN registered to a different entity name
–Mathematical inconsistencies (gross − tax ≠ net)
–Suspicious PDF metadata (browser-created, excessive fonts)
–UK/US terminology in an Australian payslip
70 – 100Critical Risk
Action: Reject
Strong indicators of fraud or fabrication. Multiple critical flags across categories. Recommend escalation to fraud investigation.
Common reasons
–AI-generated content detected with high confidence
–Gross − tax ≠ net (mathematical impossibility)
–ABN does not exist or is cancelled
–PDF created in browser, not payroll software
–Network clustering with known fraudulent broker submissions
Flag Categories
Each flag category has a maximum point cap. Flags within a category are summed (weighted by severity) up to the cap. The total risk score is the sum of all category scores, capped at 100.
1
PDF Forensics
max 25 pts
What it checks
•PDF producer/creator metadata (e.g., "Chrome" vs "Xero Payroll")
•Creation and modification timestamps (future dates, identical timestamps)
AI_GENERATED_HIGHClaude confidence >90% that document text was AI-generated
UK_TERMINOLOGY"Basic Salary" instead of "Ordinary Earnings", "National Insurance" instead of super
GENERIC_SUPER_FUNDSuper fund name is generic or does not match known APRA-registered funds
PLACEHOLDER_VALUESRound numbers, sequential identifiers, or template-like field values
How it works: Claude Sonnet reads the full extracted document text and evaluates authenticity against Australian payroll conventions, industry terminology, and AI-generation patterns.
3
Math & Date Consistency
max 30 pts
What it checks
•Payslip: Gross − Tax = Net (within ±$1 rounding tolerance)
PDF Forensics: 25AI Content Detection: 35Math & Date Consistency: 30Cross-Reference Verification: 20Broker Risk Profiling: 15
Total possible: 25 + 35 + 30 + 20 + 15 = 125, capped at 100
Reading the Report Narrative
•Every analysis includes a plain-English summary written for bank credit officers and compliance teams.
•The narrative references specific evidence from the documents (e.g., “ABN 12345678901 is registered to ‘Smith Holdings Pty Ltd’, not ‘Acme Corp’ as stated on the payslip”).
•Reports are suitable for inclusion in APRA/ASIC documentation and audit trails.
•Each flag in the report is expandable, showing the raw field values, expected values, and the confidence level of the detection.
Example: Low Risk (Score 12)
12
Low Risk
Recommended: Approve
Summary narrative
The application from Sarah Mitchell (Loan: $620,000) includes 2 payslips from “Melbourne Consulting Group Pty Ltd” and 3 months of bank statements from ANZ. All documents appear genuine.
ABN 51 824 753 186 is active and registered to “Melbourne Consulting Group Pty Ltd” (exact match). BSB 013-442 (ANZ Melbourne) is valid. Gross ($8,200) minus tax ($2,050) equals net ($6,150) — correct. Super at $943 represents 11.5% of gross — matches current SGC rate. YTD figures align with 4 fortnightly pay periods since 1 July.
One informational flag: salary is above the 75th percentile for “Management Consultants” (ABS Cat. 6302.0) but within normal range for senior roles.
The application from James Parker (Loan: $1,200,000) contains 2 payslips from “Acme Corp” and 3 months of bank statements. Multiple critical issues detected across 4 of 5 categories.
PDF Forensics: Both payslips were created in “Google Chrome” (not payroll software). 5 different font families detected. Creation timestamp is identical to modification timestamp (no editing history).
AI Content Detection: Claude confidence 94% that payslip text is AI-generated. Uses “Basic Salary” (UK terminology) instead of “Ordinary Earnings”. Super fund listed as “Australian Super Fund” (generic, not an APRA-registered entity name).
Math Errors: Payslip shows Gross $12,500, Tax $3,125, Net $9,575 — actual net should be $9,375 (discrepancy of $200). Super at $1,000 represents 8.0% of gross (below SGC minimum of 11.5%).
Cross-Reference: ABN 98 765 432 100 is registered to “Acme Trading Holdings Pty Ltd”, not “Acme Corp” as stated. Salary of $325,000 p.a. exceeds the 99th percentile for the stated occupation “Administrative Assistant”.