Embarking on a digital transformation journey to adopt new technologies such as artificial intelligence (AI) and machine learning is a goal for many financial organisations. With these technologies, come better business insights, knowledge mining and risk analysis.
As part of this, it is common for organisations to move their entire data estate from legacy systems to the cloud. However, this data contains risk and a large percentage is non-business critical and non-compliant with legislation. This makes it difficult to adopt transformative technologies and demonstrate regulatory compliance. Consequently, companies must take control of their data at the outset of any digital transformation journey.
“Businesses need to identify what information they have, where it is stored, who has access and whether there are compliance risks,” says Simon Cole, CEO of Automated Intelligence. “They can only achieve this by understanding, cleansing, managing and adding governance to the data before migrating it to the cloud. This will surface any hidden value while minimising risk.”
Automated Intelligence’s data management platform AI.DATALIFT can help. Built on the Microsoft Azure cloud, the solution brings together unstructured data from various sources across an enterprise to give a clear overview of the entire data estate. Understanding and managing data improves data quality and enables companies to service customers through enhanced insights.
“Cloud scale lets Automated Intelligence review large volumes of data at a speed that humans couldn’t otherwise achieve,” says Cole. “Machine learning and advanced AI techniques highlight trends, patterns, risks and opportunities, as well as tracking exposure to legislation.”
There are practical benefits too. “Big companies store multiple petabytes of data on legacy platforms that cost tens of millions of pounds to run annually, but around 60-70% of this data brings no value to the business,” says Cole. “Understanding and deleting this data will instantly cut costs and storage requirements.”
Automated Intelligence works with multiple financial services businesses that are required to regularly audit data and abide by strict data regulations. A UK retail bank and a large financial services business are just two organisations that have already used AI.DATALIFT to manage data.
“These organisations are getting real-time visibility into their data so they can manage it efficiently and cost effectively,” says Cole. “They can quickly access relevant and accurate information to deliver exceptional customer experiences. Most importantly, their data is always securely stored, accessed and used in compliance with internal governance policies while also meeting privacy (GDPR/California Consumer Privacy Act) and financial services regulations.”
By helping financial companies take control of their data, Automated Intelligence is empowering them to take control of their future. “Once they’ve unlocked the value and removed the risk from their data, they’re well-positioned for a successful digital transformation,” Cole concludes.
This article was originally published in the Winter 2019 issue of The Record. Subscribe for FREE here to get the next issues delivered directly to your inbox.
Share this story