Balance sheet and credit

ALM Engine

Connects positions, funding, contractual cash flows, assumptions, curves, scenarios, and reproducible balance-sheet runs.

Asset and liability management
Category: Balance sheet and credit
Sector fit: Core: Banking. Related: Asset Management and Corporates.

The operational problem

Position data lived in core ledgers, treasury files, loan schedules, securities records, and manual spreadsheets. Funding terms and behavioral assumptions were maintained separately from contractual cash flows. Curve inputs changed independently of portfolio snapshots, while product codes and repricing conventions varied by source. Reconciliation occurred after analysis, allowing unresolved differences into exposure reports. Scenario results depended on local workbook states and analyst sequencing. The institution required a governed balance-sheet representation that could reproduce cash flows, shocks, earnings sensitivity, and economic value from a defined data cut.

How it was engineered

Markets IQ separated positions, contractual terms, generated cash flows, behavioral assumptions, curves, scenarios, and runs into linked ledgers. The ingestion gateway snapshots each source and maps local product codes into reference instrument types while retaining original values. Contractual schedules are generated first. Behavioral overlays are applied as explicit, versioned assumptions. Curve construction is isolated from shock design so market-data changes can be distinguished from scenario changes. Validation gates reconcile balances, maturity totals, repricing fields, and cash-flow sums before a run is released. Every run stores source versions, mappings, assumptions, curve set, scenario definition, and calculation outputs. The design requires more mapping effort at intake. That effort makes period comparisons and reruns technically meaningful and independent of local workbook state.

What it enables

The institution can reconcile assets and funding to controlled source snapshots, generate contractual and behavioral cash flows, and rerun rate scenarios from fixed assumptions. It can separate data movements from model changes, explain shifts in earnings and economic value, and compare reporting periods on the same instrument definitions. Reviewers can trace each exposure measure through its curve, scenario, cash flow, position, and source record.

Capabilities
Maps local product codes into governed instrument and funding definitions
Generates contractual cash flows before applying versioned behavioral assumptions
Builds curves separately from scenario shocks and portfolio calculations
Reconciles positions, repricing terms, maturities, and generated cash-flow totals
Reproduces earnings and economic-value measures from stored run inputs
Sector applications

How each sector applies it.

Banking. Balance-sheet, funding, repricing, liquidity, earnings sensitivity, and economic-value workflows. View sector →
Asset Management. Liquidity and rate-exposure data where portfolio mandates require them. View sector →
Corporates. Treasury and funding scenarios using the relevant position and cash-flow architecture. View sector →
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