Below is a practical, end-to-end approach to reporting an AS/400 (IBM i) payment table in a Web UI using data analytics, focused on banking/payments use cases.
1. Understand the AS/400 Payment Table (Foundation)
Before building any UI or analytics, clearly classify the data.
Typical fields in an AS/400 payment table:
-
Payment date & time
-
Amount
-
Currency
-
Payment type (credit, debit, transfer)
-
Channel (branch, ATM, online, batch)
-
Status (success, failed, pending)
Debtor/creditor details
👉 First step: Create a data dictionary so web and analytics teams understand what each field means.
2. Data Flow Architecture (AS/400 → Web UI)
Recommended Architecture
AS/400 (DB2)
⬇
Data Extraction Layer
-
Scheduled batch extracts (daily/hourly)
-
Cleaned & aggregated tables
-
Charts, tables, filters
-
Near real-time or T+1 reporting
💡 Do not directly hit AS/400 from the Web UI — always use a reporting layer.
3. Key Reports to Show in the Web UI
A. Executive Summary Dashboard
High-level KPIs at the top:
-
Total payment volume (count) - summary of payments
-
Today / MTD / YTD comparison
📊 Best visuals:
-
Trend line (daily volume)
-
Donut chart (status split)
B. Payment Volume Analysis
Show how payments behave over time.
Reports to include:
Payments per month
-
📊 Visuals:
-
Line chart (time series)
-
Heatmap (hour vs day)
C. Status & Failure Analysis
Critical for operations teams.
Metrics:
-
Failed payment %
📊 Visuals:
-
Pie chart (status)
-
Table with filters
-
Alert flags for high failure rates
D. Customer / Account Insights
Useful for business and risk teams.
Analytics ideas:
-
Dormant vs active accounts
📊 Visuals:
-
Ranked tables
-
Pareto chart (top 20% customers)
4. Filters & Drill-Down (Very Important)
Your Web UI should allow users to:
-
Filter by date range
-
Filter by payment status
-
Filter by channel
-
Search by transaction ID / account
🧠 Drill-down example:
Click on “Failed Payments” → see detailed transaction list → click transaction → view AS/400 reference details.
5. Data Analytics Techniques to Apply
A. Aggregations
-
Daily / hourly totals
-
Rolling averages
-
Month-over-month growth
B. Trend Analysis
-
Detect increasing failures
-
Identify volume spikes
C. Exception Reporting
-
Payments above threshold amount
-
Sudden drop in transaction volume
-
Unusual activity by account
6. Security & Compliance (Banking-Critical)
When exposing AS/400 payment data on Web UI:
✔ Mask sensitive fields (account numbers)
✔ Role-based access (Ops vs Finance vs Audit)
✔ Read-only reporting access
✔ Audit logs for report usage
7. UI Design Best Practices
For banking users:
-
Clean, minimal layout
-
Fast page loads
-
Export to Excel / PDF
-
Consistent date & currency formatting
-
Clear legends and labels
8. Sample Web UI Page Structure
Page 1: Payments Overview
-
KPI cards
-
Volume trend chart
-
Status breakdown
Page 2: Payment Details
-
Filterable transaction table
-
Drill-down links
Page 3: Operations Dashboard
-
Failures
-
Pending items
-
SLA breaches
9. Why This Approach Works for AS/400 Systems
-
Protects AS/400 from heavy UI load
-
Enables historical analytics
-
Scales for large payment volumes
-
Supports future fintech & API integrations
To report an AS/400 payment table in a Web UI, the best approach is:
Extract → Analyze → Aggregate → Visualize
By combining data analytics with clean dashboards, banks can turn legacy AS/400 payment data into real-time business and operational insights.
No comments:
Post a Comment