The impact of Digitisation: Are you managing the growing risk of unstructured data?

Many financial services organisations (FSOs) choose to embark on a digital transformation journey in order to support their goal of better serving customers with efficient communication and innovative product offerings. This digital transformation typically involves the digitisation of data and digitalisation of operational processes. 

 While this process brings many organisational advantages, when left unmanaged, digitisation can inadvertently result in the growth of unstructured data. In this blog article we will outline why this issue of unstructured data poses a regulatory and financial risk to FSOs. 

Before we can understand how the digitisation process contributes to unstructured data growth, we must first explain what digitisation means. Digitisation is the process of converting physical information into a digital format such as an employee scanning a paper document. The document has now become digitised.  

Digitalisation, which is a unique term of its own, denotes the use of digitised information to improve business processes. This would involve the employee from the above example sending the now digitised document to a colleague via email.  

Through the process of digitisation and digitalisation, organisations create, store and share new digitised copies of information every day. What organisations fail to realise however, is that large volumes of this new data can be unstructured, putting them at risk. 

Unstructured data relates to information which is created without a pre-defined data model. Some examples of unstructured data include emails, voice calls and scanned images to name a few. This means the data is not easily searchable in comparison to databases, which neatly organise data into columns and rows.  

The reason that this becomes an issue for FSOs is that they are then unable to determine the value held within unstructured data. This obscurity leads to the following risks: 

Regulatory risks: FSOs may unwittingly store uncompliant and over-retained information within their unstructured data, which breach regulatory guidelines. Breaches ultimately lead to financial fines and reputational damage. 

• Data privacy risks: Particularly for banks, unstructured data which is left unmanaged may contain personally identifiable information (PII) pertaining to customers. Such instances will undoubtedly incur a regulatory breach. 
• Cost implications: Unmanaged unstructured data can pose significant budgetary strains for FSOs to store. Unstructured data which is classified as Redundant, Obsolete or Trivial (ROT) should be cleansed or archived from an organisation’s data to alleviate the financial pressures of storing.  

At Automated Intelligence (AI), we have produced a white paper in partnership with Information, Governance and Risk Management Specialist, Roger Poole, which explores the issue of unstructured data within FSOs in great detail. The publication expands on the risks and challenges of unstructured data and how our innovative cloud-based platform, AI.DATALIFT, provides a solution to the issue of unstructured data. 

As a Governance, Risk and Compliance platform, AI.DATALIFT classifies data against an FSO’s Information Governance strategy. This means that when new information is created as part of the digitisation process, the data is appropriately categorised and organised, effectively reducing compliance risks.  

If you would like to read the white paper in full, please complete the form below.