Originally published by Out-Law.com
Banks have been urged to measure the cost of "data quality lapses" after a survey found that most of the institutions are unprepared for dealing with inaccurate, corrupted or falsified data.
According to Accenture, there are "impending waves of corrupted insights, bad decisions, and potential compliance failures" that could stem from "falsified data" infiltrating bank information systems.
The consultancy surveyed nearly 800 bank business and IT executives from around the world and found that 77% of the respondents believe most organisations are unprepared to confront those scenarios.
According to Accenture's technology vision 2018 survey (30-page / 1.74MB PDF), 28% of bankers said they do not validate or examine the third-party data they receive most of the time, while a further 5% said they do not validate the information at all.
In addition, more than a third of the respondents (34%) said their organisation had been targeted by "adversarial AI" at least once, and 78% said they think automated systems "create new risks, such as fake data, external data manipulation, and inherent bias".
"Banks have always held a hefty amount of highly confidential internal data on customers, partners, services, suppliers, and products," the report said. "Now, they are increasingly adding data from external "unstructured" sources, such as newly accessible government and third-party databases, and many more interaction channels, including social media."
"If banks don't ensure that data is accurate, valid, consistent, and has referential integrity, then they will be vulnerable to drawing business insights and making decisions that are of questionable value at best and corrupted or illegal at worst."
Accenture said that there can be non-malicious reasons why there is "bad data in a system", but said the presence of such information "may be a sign that a process isn't working the way it was intended". It said it is important to uncover processes that "inadvertently invite deceit", and advised banks to "start collecting information on the cost of data quality lapses".
"Consider completeness, accuracy, validity, and consistency amongst other potential issues that can lead to re-work, customer dissatisfaction, or even regulatory fines," Accenture said in its report.
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