/wp-content/uploads/logo.png 0 0 Andrew Sexton /wp-content/uploads/logo.png Andrew Sexton2016-03-22 10:47:202017-01-03 09:06:27Solvency II - making demands on your data quality process
Solvency II is finally upon us and much has been said about how the pressures will ripple across insurers and their asset managers. But how can asset managers ensure that they are managing the data quality demands of Solvency II and meeting the high standards of their insurance clients?
/wp-content/uploads/logo.png 0 0 Andrew Sexton /wp-content/uploads/logo.png Andrew Sexton2015-11-30 17:42:132017-01-03 09:06:047 Steps to Getting Data Quality Right - Part 2
Once you have visibility into the quality of your data across the core architecture and/or wider enterprise, are monitoring it on an ongoing basis, using sophisticated workflow to help prioritise and solve your data quality issues and have considered your functional requirements, the next essential step is...
/wp-content/uploads/logo.png 0 0 Andrew Sexton /wp-content/uploads/logo.png Andrew Sexton2015-09-17 18:01:332017-01-03 09:02:427 Steps to Getting Data Quality Right - Part 1
Ensuring you have good data quality underpinning all of your investment processes is an obvious requirement for today’s data management professional. But it’s harder than you’d think to get the process of measuring and managing data quality right.
/wp-content/uploads/logo.png 0 0 Rouge /wp-content/uploads/logo.png Rouge2015-06-16 08:37:012017-01-03 09:01:24Data Management - Is it time for a best of breed approach?
Data management - it’s a catch all term for any aspect of a firm’s technology or operational process which involves the loading, movement, transformation, storage, management or use of data, whether it be structured or unstructured.
/wp-content/uploads/logo.png 0 0 Rouge /wp-content/uploads/logo.png Rouge2015-06-16 08:32:212017-01-03 09:01:01The changing Data Landscape – Identifying where to invest in data projects at Asset Managers
IT are asking for funding to improve the data processing capability. Operations are requesting additional resources to manage data quality. The Data Analysts want new tools to track data provenance. All the while the fund managers are complaining about ‘bad data’.
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