Machine Learning in Reconciliations
Winning in financial services is increasingly about the speed and accuracy of data normalization and reconciliation. Banks, asset managers, custodians, broker-dealers, portfolio managers, market utilities, etc. are all fundamentally data-driven. Thousands of employees onboard, match, compute and report massive quantities of data every day across every part of the business.
Executives must be able to trust their data to make informed business decisions. Trusting data requires it to be verified against trusted sources. Verifying against trusted sources requires reconciliation… in real-time at velocity, at complexity, at voracity.