What are typical data integrity checks performed in FOSSE after a trade feed?

What are typical data integrity checks performed in FOSSE after a trade feed?

• A. Compare counts and sums only.
• B. Compare counts, sums, price fields, currency consistency, settlement status, and trade IDs mapping.
• C. Check only settlement status.
• D. Verify trade IDs mapping only.

Answer: (B)

Verifying data integrity after a trade feed into FOSSE requires a comprehensive set of checks that verify both the quantity of records and the quality of crucial fields. The best approach combines multiple validations: counts and sums to detect missing or extra records and arithmetic drift; price fields to ensure prices are present and sensible for the instrument; currency consistency to confirm all currency codes line up across the trade data and with the system’s base currency; settlement status to validate that the trade lifecycle is correctly reflected; and trade IDs mapping to ensure each incoming trade aligns with the correct internal record. Why this combination is the strongest: relying on only one type of check (for example, just settlement status or just IDs mapping) can miss other inconsistencies such as mismatched prices, incorrect currencies, or unmatched counts, which can propagate errors through risk and settlement processes. The multi-faceted approach catches a wider range of issues and supports reliable reconciliation between the feed and the system, which is essential for accurate trading operations and audit trails.

Verifying data integrity after a trade feed into FOSSE requires a comprehensive set of checks that verify both the quantity of records and the quality of crucial fields. The best approach combines multiple validations: counts and sums to detect missing or extra records and arithmetic drift; price fields to ensure prices are present and sensible for the instrument; currency consistency to confirm all currency codes line up across the trade data and with the system’s base currency; settlement status to validate that the trade lifecycle is correctly reflected; and trade IDs mapping to ensure each incoming trade aligns with the correct internal record.

Why this combination is the strongest: relying on only one type of check (for example, just settlement status or just IDs mapping) can miss other inconsistencies such as mismatched prices, incorrect currencies, or unmatched counts, which can propagate errors through risk and settlement processes. The multi-faceted approach catches a wider range of issues and supports reliable reconciliation between the feed and the system, which is essential for accurate trading operations and audit trails.