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Chartwell/Books/Accounting/Jira/IA-2827.txt
2026-04-13 14:20:04 -04:00

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JIRA Story - RAG Knowledge Base
Accounting IA-2827: Preload iSeries Data for Pending Cancel and Billing Statements
Chunk 1: Overview
Metadata:
storyId=IA-2827, type=overview, domain=dataPreload, workflow=nightlyProcessing
Content:
Purpose: Preloads iSeries-derived data into AWS data store for Pending Cancel and Billing Statement documents to support downstream nightly processing.
Business Goal:
Ensure required historical and current data is available in AWS so that nightly processes can accurately evaluate policy state and prior notifications.
Core Behavior:
Extract data from upstream systems (iSeries and/or EDW)
Store normalized data in AWS data store
Enable lookup of prior billing and cancellation events during nightly checks
Outcome:
Nightly workflows can reliably determine whether billing statements or pending cancellation notices have been previously issued.
Chunk 2: Preconditions and Dependencies
Metadata:
storyId=IA-2827, type=preconditions, dependencies=iSeries,EDW,Oracle
Content:
Required Preconditions:
Data must be extracted from iSeries and/or EDW
Payment schedule data may include Oracle identifiers (needs confirmation)
Dependencies:
iSeries as primary source of policy and installment data
EDW as potential supplemental data source
AWS data store for persistence
Nightly processing workflows consuming preloaded data
Implicit Rule (Made Explicit):
If Oracle identifiers are not present, downstream processes must still function using available keys (e.g., AccountIdentifier, PolicyNumber)
Chunk 3: Functional Requirement - Pending Cancel Document
Metadata:
storyId=IA-2827, type=functional, documentType=PendingCancel
Content:
Required Fields (Normalized):
AccountIdentifier
PrimaryCancellationReason
CancellationNoticeDate
CancellationEffectiveDate
PolicyNumber
Purpose:
Represents policies that are at risk of cancellation and have been issued a pending cancellation notice.
Implicit Rules (Made Explicit):
Presence of record implies a pending cancellation notice has been sent
CancellationEffectiveDate represents the future termination date if no action taken
PrimaryCancellationReason must be preserved for downstream decisioning
Chunk 4: Functional Requirement - Billing Statement Document
Metadata:
storyId=IA-2827, type=functional, documentType=BillingStatement
Content:
Required Fields (Normalized):
AccountIdentifier
PaymentDueDate
StatementType
PolicyNumber
Purpose:
Represents billing statements issued to customers for payment collection.
Implicit Rules (Made Explicit):
Presence of record implies a billing statement has been generated/sent
PaymentDueDate is used for delinquency and cancellation evaluation
StatementType differentiates billing scenarios (e.g., regular, special)
Chunk 5: Functional Requirement - Installment and Notice Tracking
Metadata:
storyId=IA-2827, type=functional, concept=installmentTracking
Content:
Required Output Fields:
HeaderNumber
PaymentNumber (InstallmentNumber)
BillingNoticeSent (Y/N)
PendingCancelNoticeSent (Y/N)
PolicyNumber (12 digits)
AccountKey
Core Logic:
Identify the highest active PaymentNumber (InstallmentNumber)
Determine whether:
Billing statement has been sent
Pending cancellation notice has been sent
Implicit Rules (Made Explicit):
“Highest active” implies latest installment that is still open/active
Flags (Y/N) are derived from presence of corresponding document records
PolicyNumber must be normalized to 12-digit format
Chunk 6: Workflow and Processing Flow
Metadata:
storyId=IA-2827, type=workflow, orchestration=dataPreload
Content:
Processing Flow:
Extract data from iSeries and/or EDW
Normalize and map fields to AWS data model
Identify latest active installment per PolicyNumber
Evaluate presence of:
Billing statements
Pending cancel notices
Derive indicator flags (BillingNoticeSent, PendingCancelNoticeSent)
Store enriched records in AWS data store
Nightly process queries this data for decisioning
Key Rule:
Preloaded data must be available before nightly process execution
Chunk 7: Non-Functional Requirements
Metadata:
storyId=IA-2827, type=nonFunctional, category=dataAvailability
Content:
System Requirements:
Data must be preloaded prior to nightly batch execution
Data retrieval and storage must be reliable and repeatable
System should support incremental updates as new installments are generated
Performance Consideration:
Preload process must complete within batch window
Efficient lookup required for nightly processing queries
Chunk 8: External System Responsibilities
Metadata:
storyId=IA-2827, type=externalSystems, systems=iSeries,EDW,AWS
Content:
iSeries Responsibilities:
Provide PolicyNumber, InstallmentNumber (PaymentNumber), document indicators
Provide core billing and cancellation data
EDW Responsibilities:
Supplement missing or derived data fields (if applicable)
AWS Responsibilities:
Store normalized data
Provide query access for nightly processing
Oracle (Conditional):
May provide identifiers within payment schedule data (if available)
Implicit Rule (Made Explicit):
AWS acts as the system of aggregation and lookup, not the source of truth
Chunk 9: Business Rules
Metadata:
storyId=IA-2827, type=businessRules, domain=policyProcessing
Content:
Core Rules:
Highest active installment must be identified per PolicyNumber
Billing and cancellation indicators derived from document presence
PolicyNumber must be standardized to 12 digits
AccountIdentifier and AccountKey must consistently map across systems
Edge Cases:
Missing Oracle identifier → processing continues using available keys
Multiple documents → only latest active installment considered
No documents present → both flags set to "N"
Chunk 10: Data Quality Assumptions and Risks
Metadata:
storyId=IA-2827, type=dataQuality, riskLevel=low
Content:
Assumptions:
iSeries data is accurate and up-to-date
Installment numbering correctly reflects payment sequence
Document generation events are reliably recorded
Risks:
Missing or inconsistent AccountIdentifier across systems
Incorrect identification of “highest active” installment
Incomplete document history leading to incorrect flags
Mitigation:
Validate data completeness during preload
Normalize identifiers consistently
Cross-check installment sequencing logic
Chunk 11: Search Queries Supported
Metadata:
storyId=IA-2827, type=queryPatterns, purpose=RAGRetrieval
Content:
This knowledge base supports queries such as:
"How is iSeries data preloaded for billing and cancellation processing?"
"What fields are required for Pending Cancel documents?"
"What data is stored for billing statements?"
"How is the highest active installment determined?"
"How are billing and cancellation notice flags calculated?"
"What data does nightly processing rely on?"
"What happens if Oracle identifiers are missing?"
"How are PolicyNumbers normalized?"
"What systems provide data for preload processing?"
"How do we determine if a billing statement was sent?"