Complex ERM software are essential tools in the banking industry to quantify the net interest income and the market value of equity risks, and to prepare reports particularly on the asset and liability portfolio, the re-pricing gaps, and the liquidity positions. We set up a simplified simulation and reporting environment using R, which reproduces the key features of the commercially used ALM software solutions.

Typical ALM data processes follow the so-called extract, transform, and load (ETL) logic.

Extraction, which is the first phase, means that the bank has already collected the deal-level and account-based source data from the local data warehouse (DWH), the mid-office, the controlling or the accounting systems. The source data of the total balance sheet (here called a portfolio) is also extracted in order to save calculation time, memory and storage space. Moreover, single deal-level data is aggregated by the given dimensions (for example, by currency denomination, interest...