SwiftADF is a data management platform that generates ADF, XBRL, CIMS, MIS, and regulatory reports providing real-time reports and analytics. It enables better decision-making and offers insights into the financial health of banks. SwiftADF automates reporting for the management personnel at the bank and simplifies reporting to RBI. Swift ADF provides T+1 Data Integration with Source Systems and manual data entry/editing options. Excel data integration, data versioning, and data validation are some of the key features of SwiftADF. It also provides detailed audit trails, custom CDR based on the reporting requirements and schedules ADF return generation depending on the calendar.
Data Integration and Processing
Data Extraction:
SwiftADF has built-in ETL and supports data extraction from source Applications like LMS, LOS, CBS, CRM, ALM, etc. Data can be extracted from RDBMS, big data, reports, unstructured databases, etc. SwiftADF allows schedule extraction jobs and T+1 data extraction.
Excel Data:
SwiftADF enables data import from Excel/CSV files and allows users to import multiple Excel files for various data elements. SwiftADF supports validating the data imported from Excel files and provides a maker-checker workflow for approval.
Manual Data:
SwiftADF provides a built-in web form generator and web forms to capture manual data. It supports data profiling and business rule validations. Multiple web forms for a single return can be created, and SwiftADF provides a maker-checker workflow for approval.
Data Integration:
Data integration from various sources is supported. SwiftADF enables data integration from Excel/CSV files and manual data entry forms. It facilitates data integration and collation
Data Transformation:
SwiftADF calculates and updates derived values based on the mapping. It supports data standardisation and transformation depending on business rules and permits data movement from the processing layer to the reporting layer./p>
Data Repository
SwiftADF has a common data repository (data warehouse) based on RBI’s guidelines. It uses facts, cubes, aggregates & data marts depending on the reporting requirements. Multiple versions of the reporting data can be stored.
Reporting
