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REGISTER NOWIVP’s AI/ML-powered Suggestion Engine can dramatically reduce the time spent resolving breaks. Providing insight on the most probable user actions so that operations teams can focus on true genuine breaks, IVP’s Suggestion Engine acts as an assistant in cleaning up breaks and addressing reconciliation processing inefficiencies.
What are the challenges faced by the operations team?
The operations team aims to verify that each transaction in the bank statement is consistent and comparable to the internal records as presented in the Internal Book of Records (IBOR) or Accounting Book of Records (ABOR). This process can become very complicated because of the difference in time when a particular transaction is recorded in the bank and in the company. Oftentimes, adjustments are needed since other complications can arise from differences in currencies and data formats as well as potentially huge transaction volumes.
The critical challenge for any operations team is reconciling varied transaction types like interest bookings, cash deposits, cash withdrawals, pay downs, expenses, etc. apart from standard buy and sell transactions. These varied types of transactions are often booked with no clean identifiers, making the transaction description the only way to meaningfully identify them. However, these transaction descriptions are often not structured and consistent as they contain non-standard, running hand trade information. Reconciling them is risky as none of the matching rules can truly “match” or “pair” two related transactions that intend to be similar. The problem aggravates matching transactions in scenarios like “one-to-many” or “many-to-many”.
How can an AI/ML-powered suggestion engine resolve it?
An AI/ML-powered suggestion engine has the potential to resolve all of the breaks in an efficient approach:
An AI/ML-powered suggestion engine not only improves the operations control function but also leverages the asset manager’s time on other critical points.
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