The need for an organisation to have a Data Strategy is primarily driven by recent and ongoing changes in regulation with increasing global quality and ownership standards being set for data. The approach that regulators are taking are onerous on businesses today and especially within the Financial Services sector, with acts such as GDPR (General Data Protection Regulation – EU law 2016/679), the Banking Executive Accountability Regime (BEAR in Australia), the Senior Manager Regime in the UK and similar requirements from the Monetary Authority of Singapore meaning that senior executives are now personally accountable for customer/client data and the security and quality of such data.

We are seeing that the key business objectives for most financial organisations are :

Getting out of the “red” regulatory obligations and gaining an adequate level of compliance

Being compliant with local and global Regulatory bodies which now includes sign off on quality of data

Customer data aggregation to manage risk holistically across all product offerings

Real Time Data Capabilities and lowering technology costs (using SAAS, microservices and Cloud)

There has been an explosion in the number of data platforms with examples such as Hadoop, NoSQL databases and Analytics pipelines that support massive amounts of data for storage and processing.

There is an evolution and progression to data storage which utilises the concept of a data lake. This is an extension to the concept of a Data Warehouse that stores data from both structured and unstructured data sources (such as social media feeds, weblogs, sensor data from IOT devices etc) which can allow the necessary governance and quality aspects of data management to be addressed as well as providing a rich data source for Analytics.

Contact us on how we can help you with identifying the five common themes that will avoid data becoming unusable or unmanageable, without the appropriate management tools and techniques in place