Business Intelligence for Banking Performance Reporting Training Course

Course overview

Bank performance reporting is often slowed by fragmented source systems, inconsistent definitions of net interest income, loan growth, liquidity and credit quality, and manual spreadsheet consolidation. Analysts and managers need reports that reconcile to finance and risk data, expose exceptions quickly, and provide drill-through from board-level KPIs to branch, product, customer segment or portfolio detail. This course addresses the practical challenge of turning core banking, treasury, lending and finance data into governed performance reporting that supports timely management action.

Participants learn to define a banking KPI catalogue, map source data to reporting measures, prepare data with SQL and Power Query, and build interactive Power BI models and dashboards. The course covers profitability reporting, balance-sheet trends, deposit and loan analysis, net interest margin, cost-to-income, liquidity indicators, arrears and non-performing exposure, and variance analysis against budget and prior period. Participants also apply data-quality controls, reconciliation checks, role-based access principles and Basel III/IFRS 9 reporting considerations appropriate to management information.

Teaching combines instructor-led demonstrations with a realistic banking reporting case. Participants work with sample transaction, customer, loan, deposit, general ledger and target data to create a refreshable management dashboard. They leave with a documented Banking Performance Reporting Pack: a KPI dictionary, data model, SQL extraction logic, Power BI dashboard pages, reconciliation checklist and a 90-day application plan. The course is suited to professionals who need to produce, improve, review or govern management information rather than merely consume dashboards.

Course objectives

By the end of this course, participants will be able to:

• Define a banking KPI dictionary for profitability, balance-sheet, credit-quality and liquidity reporting
• Map core banking, general ledger and portfolio data fields to approved performance measures
• Write SQL queries that extract and aggregate loan, deposit, income and expense data
• Build a star-schema Power BI data model with banking dimensions and calendar logic
• Create DAX measures for net interest margin, cost-to-income, loan growth and arrears ratios
• Design drill-through dashboard pages for branch, product, segment and portfolio variance analysis
• Apply reconciliation, completeness and exception controls to a banking management information pack
• Produce a documented Banking Performance Reporting Pack for monthly management review

Benefits of attending

Target competencies

Who should attend

• Banking Business Intelligence Analysts — who build dashboards from core banking, finance and portfolio data
• Management Information Analysts — who prepare recurring executive, branch and product performance reports
• Finance Analysts and Controllers — who reconcile management reporting to the general ledger and budget
• Risk Reporting Analysts — who monitor credit quality, arrears, concentrations and portfolio trends
• Data Analysts in Retail or Corporate Banking — who translate operational data into usable performance insight
• Branch, Product and Portfolio Managers — who need to interpret KPI drivers and commission better reporting

Requirements and prerequisites

Participants should be comfortable working with spreadsheets, tables, filters and basic business calculations such as percentages, variances and ratios. Familiarity with banking terms including loans, deposits, interest income, operating expenses, arrears and the general ledger is helpful, as is experience using management reports. Basic SQL awareness is useful but not essential; SQL foundations are practised during the course. Participants should bring a laptop capable of running Microsoft Power BI Desktop and Microsoft Excel. Prior Power BI, DAX, data-modelling or programming experience is not required, and complete BI beginners should expect a structured, hands-on introduction.

Training methodology

The instructor uses a simulated bank dataset containing general ledger balances, loan accounts, deposits, customer segments, branch hierarchies and monthly targets. Short technical demonstrations are followed by guided SQL, Power Query, DAX and dashboard-building exercises. Participants work in groups to agree KPI definitions, identify reconciliation breaks and critique dashboard layouts for an executive performance meeting. Daily review points connect calculations to banking decisions. On the final day, each participant completes and presents a practical reporting pack and prioritised 90-day implementation plan.

Course outline

Day 1: Banking performance reporting foundations

• Bank management information architecture and reporting cycles
• Core banking, general ledger, treasury and lending data sources
• Banking KPI hierarchy for board, executive and operational reporting
• Profitability measures including net interest income and cost-to-income
• Balance-sheet measures for loans, deposits and funding mix
• Credit-quality measures including arrears, non-performing exposure and coverage
• KPI dictionary design with owners, formulas, frequency and source lineage

Workshop: Participants create a KPI dictionary for a retail bank monthly performance pack, including definitions, owners, source systems and drill-down dimensions.

Day 2: Data preparation and banking data modelling

• SQL SELECT, JOIN, GROUP BY and CASE statements for banking data
• Extracting monthly loan, deposit, income and expense balances
• Power Query data profiling, type conversion and error handling
• Banking calendar design for month-end, quarter-end and year-to-date reporting
• Star-schema modelling with fact balances and conformed dimensions
• Customer, product, branch and portfolio hierarchy management
• Data-quality tests for completeness, duplicates, missing codes and unexpected movements

Workshop: Participants prepare and model loan, deposit and general ledger extracts in Power BI, producing a validated star schema and data-quality issue log.

Day 3: Measures, calculations and reconciliation

• DAX measures versus calculated columns in performance reporting
• Net interest margin and yield calculation logic
• Period-on-period, year-to-date and budget variance measures
• Loan growth, deposit growth and product-mix analysis
• Cost-to-income and operating expense allocation measures
• Arrears ratio, non-performing exposure and impairment coverage calculations
• Reconciliation of dashboard totals to general ledger control figures

Workshop: Participants build a DAX measure library for a monthly bank scorecard and reconcile selected measures to a supplied finance control total.

Day 4: Dashboard design for banking decisions

• Executive scorecard layout for profitability, growth, risk and efficiency
• Power BI slicers, bookmarks and report-page navigation
• Drill-through analysis by branch, region, product and customer segment
• Waterfall charts for actual-to-budget and period variance explanation
• Exception highlighting with conditional formatting and threshold rules
• Tooltips and decomposition trees for KPI driver investigation
• Role-based access principles for sensitive customer and portfolio information

Workshop: Participants design a three-page executive dashboard with drill-through views and exception rules for branches with deteriorating performance.

Day 5: Governance, presentation and implementation

• Management information governance and controlled KPI change processes
• Basel III liquidity and capital reporting context for management dashboards
• IFRS 9 impairment reporting context and expected-credit-loss data dependencies
• Dashboard refresh schedules, data lineage and audit evidence
• Reporting commentary that separates facts, drivers, risks and actions
• Stakeholder review methods for finance, risk, operations and business teams
• Ninety-day roadmap for migrating a manual report to governed BI reporting

Workshop: Participants present their Banking Performance Reporting Pack, defend KPI choices to a mock management committee and complete a 90-day implementation roadmap.

Tools & standards covered

Microsoft Power BI Desktop, Microsoft Excel, Microsoft SQL Server, Basel III

A typical training day

Live online deliveries follow the same structure in the East Africa Time zone, with shorter screen blocks and longer breaks.

What the fee includes

How you can take this course

Certification

Participants who complete the full five days receive the Skillset Development Certificate of Completion, stating the course title, course code, dates and delivery format — suitable for professional-development records and employer reimbursement.

Frequently asked questions