What does the customer risk scoring engine produce?
Calculate traceable customer risk scores from approved factors, weights and scales.
Use the exact local files and task-specific inputs listed below. Preparation and review stay in this browser. Inspect all findings before preparing the finalized pack.
What do you need before you start?
- Define the authorized source population and your review rules.
- Keep the unchanged original files and record the snapshot and exclusions.
- Review missing and invalid inputs before preparing the finalized pack.
What information do you enter?
Select the actual local sources and freeze the task-specific inputs below. Keep source files and complete findings private.
- Customer factor observations. Exact headings subject_id, factor_id, value, observed_on, source_ref.
- Approved customer risk factors. Exact headings factor_id, weight, scale_min, scale_max, direction, model_version, approval_ref.
- Analysis reference. Customer-controlled review reference.
- Analysis owner. Responsible reviewer of method and evidence.
- Observation date. Real YYYY-MM-DD date. Future source observations are unresolved.
- Population and method scope. Name source population, selected period, approved model and known omissions.
- Population declaration. Select the explicit approved working method.
| Field | What to enter | Fictional example |
|---|---|---|
| Analysis referenceRequired | Customer-controlled review reference. | |
| Analysis ownerRequired | Responsible reviewer of method and evidence. | |
| Observation dateRequired | Real YYYY-MM-DD date. Future source observations are unresolved. | 2026-10-09 |
| Population and method scopeRequired | Name source population, selected period, approved model and known omissions. | |
| Population declarationRequired | Select the explicit approved working method.Choose from Selected records only, Your declared complete sources. | Selected records only |
What you can download
Every result must identify its supplied facts, assumptions and unresolved items.
| Free result | Included downloads |
|---|---|
Enter your information, inspect the on-screen result and keep a browser backup. Editing and direct copies of your entered information stay free. |
These supported outputs are free. No checkout is required. |
Fictional review report (PDF). Editable review (DOCX). Complete fictional pack (ZIP). Requires tailoring and responsible review. Samples use the finalized renderer.
How does the customer risk scoring engine work?
- 1Select the actual sources
Customer factor observations. Exact headings subject_id, factor_id, value, observed_on, source_ref.
- 2Freeze the review rules
Match every subject to every approved factor. Normalize value within each supplied scale to 0 through 100, reverse only a stated Smaller is higher direction, and calculate sum(normalized value times weight) divided by sum(weights). Preserve factor contributions, missing or unexpected factors, duplicate identities and original values. Zero weights are allowed, but total weight must be positive. Missing or invalid factors prevent a subject score.
- 3Inspect complete findings
Review all source-linked results and unresolved items. Free JSON and CSV preserve complete results.
- 4Keep recoverable work
Exact source files and input strings save in this browser. Backups verify tool identity, input schema, hashes and parsed bytes before replacing current work. Prior checkpoints and historical purchases stay separate.
- 5Prepare the finalized pack
Prepare nine complete files, including both exact originals, then download them free. Review the fictional sample below.
Method and sources
Apply the steps above to the supported inputs. Use the listed source sections to review the rule basis, assumptions and limits.
Common questions
What information does the customer risk scoring engine need?
Enter customer factor observations. Exact headings subject_id, factor_id, value, observed_on, source_ref; approved customer risk factors. Exact headings factor_id, weight, scale_min, scale_max, direction, model_version, approval_ref; analysis reference. Customer-controlled review reference; analysis owner. Responsible reviewer of method and evidence; observation date. Real YYYY-MM-DD date. Future source observations are unresolved. Define the authorized source population and your review rules.
What does the customer risk scoring engine produce?
Traceable formula results, complete task output tables and source-linked unknowns. Free full result JSON, findings CSV and working datasets. Nine files. Formal PDF and DOCX, complete Excel source populations and calculations, findings CSV, frozen inputs/results JSON, delivered-file hashes, instructions and two exact originals. Validated browser backup ZIP, local reload, exact-byte restore and separate preserved earlier forms, calculator drafts, source files and historical purchases. Review unresolved findings and limitations before use.
Who makes the final decision?
A responsible person reviews the result. Calculations use supplied observations and explicitly approved methods. Original files and prior work remain in this browser. Results do not establish source authenticity, population completeness, causation, regulatory compliance or approval to make a customer, supplier, lending or model decision.
Is this tool free?
Yes. The on-screen result and listed downloads are free. No checkout is required. Keep local backups and review the stated method and limits.
Can I use the customer risk scoring engine for this task?
Apply the customer’s factors and weights. Calculations use supplied observations and explicitly approved methods. Original files and prior work remain in this browser. Results do not establish source authenticity, population completeness, causation, regulatory compliance or approval to make a customer, supplier, lending or model decision.
What still needs review?
Calculations use supplied observations and explicitly approved methods. Original files and prior work remain in this browser. Results do not establish source authenticity, population completeness, causation, regulatory compliance or approval to make a customer, supplier, lending or model decision.
subject_id identifies the customer. Direction is Larger is higher or Smaller is higher. Scores are administrative calculations, not customer risk decisions.
Source limits are 10 MB, 5000 rows, 50 fields, 100000 cells and 5000000 parsed characters per file. Plain decimal inputs support 12 whole digits and 6 fractional digits.
Calculations use exact rational arithmetic and round displayed values half away from zero to six fractional places unless an explicit payment rounding rule applies. Decisions compare unrounded values.
Complete results support at most 20000 findings and 15000000 characters. Formal reports show the first 25 rows per calculation output, 1000 characters per calculation preview, and the first 100 named checks with 400 characters per check field. Excel and JSON retain all values.