As financial institutions wrestle with an exploding amount of data from a growing number of sources in a variety of formats, it has become increasingly difficult to ensure that decisions are made based on high-quality information.This has led to a hard look at the role artificial intelligence (AI) and machine learning (ML) can play in monitoring key elements of the data as it moves through an enterprise data lifecycle management pipeline.
The financial services sector is among the most mature users of enterprise systems in the economy. Established institutions often preside over generations of computing platforms that have evolved over the years to accommodate on-premises data centers, private-cloud and public-cloud infrastructures, according to executives at KPMG.
Timely access to the best information has put the issue of data quality at the center of business transformation initiatives that are critical to the continued and sustained success of established institutions over the months and years to come.
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