Use Case · Banking
P&L-Reporting
& Bond Analysis
P&L-Data, aggregated automatically from various source systems, sorted by business area and product, bond portfolio analysed. Reports in minutes instead of days, without transfer errors.
Why Reporting Is a Lever
Every month the same marathon: collect data, consolidate, check, correct
P&L reporting in a bank is not a single process but a chain of manual steps.
Data from the core banking system, treasury, lending, securities trading and controlling must be brought together. Five to eight source systems, each with its own data format, its own logic, its own timing.
The result: a controller spends 3-5 days per month manually aggregating P&L data, preparing it in spreadsheets, explaining variances and compiling the reporting pack for the board and supervisory board. Bond analysis is the same picture: maturities, coupons, ratings and maturity profiles are manually compiled from multiple systems.
The problem is not the analysis. The problem is the data work beforehand. 80% of reporting time goes into data collection and consolidation. The actual analysis that the board cares about gets the rest. And with every manual step, errors creep in that must be painstakingly corrected later.
How the Process Changes
Before / After
per monthly reporting cycle (P&L + bond analysis)
The Solution in Detail
How We Automate P&L Reporting & Bond Analysis
01
Multi-Source Data Aggregation
The AI agent connects to all source systems: core banking, treasury, securities processing, controlling, Bloomberg. Data is automatically extracted, mapped to a unified format and consolidated. No manual exports, no CSV files, no copy-paste errors.
API integration where available, RPA for legacy systems. Automatic mapping between charts of accounts and reporting structures. Reconciliation checks against source systems. Complete audit trail.
02
Automatic P&L Preparation
Consolidated P&L data is automatically broken down by business line, product group, client segment and period. Prior month, budget and prior year comparisons calculated automatically. Material variances identified and annotated with suggested explanations.
03
Bond Portfolio Analysis
Bond portfolio automatically analysed: maturity structure, coupon distribution, rating distribution, maturity profiles, duration, interest rate risk. Data consolidated from Bloomberg and internal systems. Drill-down to individual position. Comparison with benchmark portfolios.
Bloomberg connection for market data. Internal holdings data from securities processing. Automatic calculation of duration, modified duration, key rate duration. Stress test scenarios configurable.
04
Reporting Pack & Dashboard
Automatic generation of the complete reporting pack: board report, supervisory board papers, business line reports. Every format from the same data, consistent, error-free. Additionally: interactive dashboard for ad-hoc analyses and drill-downs.
Power BI dashboard with role-based access. Automatic PDF generation for supervisory board. Spreadsheet export for controllers. Historical comparison across any time period.
Results
What Reporting Automation Typically Delivers
80%
effort
0
errors
Day 2
(previously day 5-8)
100%
all reports
The greatest lever is not speed but quality. Controllers who spend their time on analysis rather than data collection deliver better insights for the board.
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Ready?
On which day of the month does your P&L report land on the board's desk?
Let us calculate in 30 minutes how many hours of data collection and consolidation you can automate, and how your report can be ready on day 2 instead of day 8.
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