Abstract: Geographical mapping and linking of security and risk indicator data. Cross-references are created between location indicators and geo-spatial areas based on a statistical algorithm, in accordance with geo-spatial data. The cross-references are stored in a first data table. A credit risk indicator (CRI) is generated for each geo-spatial area based on other data, forming CRI data that is stored in second data table. A security associated with one of the location indicators is identified among security data. A first link is created between the security and a geo-spatial area based on the cross-references in the first data table. Based on the first link, a second link is created between an indicator among the CRI data in the second data table and the security. The second link is used to form instrument-level data for the security that includes the indicator. The instrument-level data is stored in a third data table.

Abstract: Geographical mapping and linking of security and risk indicator data. Cross-references are created between location indicators and geo-spatial areas based on a statistical algorithm, in accordance with geo-spatial data. The cross-references are stored in a first data table. A credit risk indicator (CRI) is generated for each geo-spatial area based on other data, forming CRI data that is stored in second data table. A security associated with one of the location indicators is identified among security data. A first link is created between the security and a geo-spatial area based on the cross-references in the first data table. Based on the first link, a second link is created between an indicator among the CRI data in the second data table and the security. The second link is used to form instrument-level data for the security that includes the indicator. The instrument-level data is stored in a third data table.

Abstract: Geographical mapping and linking of security and risk indicator data. Cross-references are created between location indicators and geo-spatial areas based on a statistical algorithm, in accordance with geo-spatial data. The cross-references are stored in a first data table. A credit risk indicator (CRI) is generated for each geo-spatial area based on other data, forming CRI data that is stored in second data table. A security associated with one of the location indicators is identified among security data. A first link is created between the security and a geo-spatial area based on the cross-references in the first data table. Based on the first link, a second link is created between an indicator among the CRI data in the second data table and the security. The second link is used to form instrument-level data for the security that includes the indicator. The instrument-level data is stored in a third data table.

Abstract: Geographical mapping and linking of security and risk indicator data. Cross-references are created between location indicators and geo-spatial areas based on a statistical algorithm, in accordance with geo-spatial data. The cross-references are stored in a first data table. A credit risk indicator (CRI) is generated for each geo-spatial area based on other data, forming CRI data that is stored in second data table. A security associated with one of the location indicators is identified among security data. A first link is created between the security and a geo-spatial area based on the cross-references in the first data table. Based on the first link, a second link is created between an indicator among the CRI data in the second data table and the security. The second link is used to form instrument-level data for the security that includes the indicator. The instrument-level data is stored in a third data table.

Abstract: Geographical mapping and linking of security and risk indicator data. Cross-references are created between location indicators and geo-spatial areas based on a statistical algorithm, in accordance with geo-spatial data. The cross-references are stored in a first data table. A credit risk indicator (CRI) is generated for each geo-spatial area based on other data, forming CRI data that is stored in second data table. A security associated with one of the location indicators is identified among security data. A first link is created between the security and a geo-spatial area based on the cross-references in the first data table. Based on the first link, a second link is created between an indicator among the CRI data in the second data table and the security. The second link is used to form instrument-level data for the security that includes the indicator. The instrument-level data is stored in a third data table.

Abstract: Geographical mapping and linking of security and risk indicator data. Cross-references are created between location indicators and geo-spatial areas based on a statistical algorithm, in accordance with geo-spatial data. The cross-references are stored in a first data table. A credit risk indicator (CRI) is generated for each geo-spatial area based on other data, forming CRI data that is stored in second data table. A security associated with one of the location indicators is identified among security data. A first link is created between the security and a geo-spatial area based on the cross-references in the first data table. Based on the first link, a second link is created between an indicator among the CRI data in the second data table and the security. The second link is used to form instrument-level data for the security that includes the indicator. The instrument-level data is stored in a third data table.