2.4 The department, working with other government and non-governmental bodies, collects an extensive amount of data resources for fraud risk assessment and identification analysis. The Bank receives significant volumes of data on lender performance and each borrower, which informs the fraud analytics work done on behalf of the department by the Government Counter Fraud Function. Outputs include, for example: analysis to identify high-fraud risk facilities for lenders to investigate further; data enrichment such as data matching with Companies House; inter and intra scheme analysis to identify suspected fraudulent actors across BBLS and other schemes; and network analysis which has resulted in details of high-risk networks of associated individuals or companies being passed onto law enforcement agencies. Data sharing with lenders also helps them with their internal fraud risk profiling and identification. Data also aids the Bank to enhance their lender management programme. The department is also collaboratively working with HMRC to improve its risking analysis and identify cross schemes fraud. 2.6 The department has worked with the Bank to develop analytical and forward-looking expected credit loss models that are compliant with International Financial Reporting Standards (IFRS 9). These models provide a sophisticated approach to forecasting expected credit losses across the COVID-19 loan guarantee schemes, utilising granular data from lenders and other sources.