With massive amounts of data being compiled on a daily basis, financial institutions are turning to artificial intelligence (AI) to improve customer experience, detect risk, and simplify common tasks. While AI solutions can provide a variety of benefits to banks, how can we ensure that the technology is being fed the best data? As AI becomes more common, the scrutiny has turned to data that feeds and teachers the solution. If it isn’t of the highest quality, is the AI able to complete its task?
Morgan Stanley has established a Data Center of Excellence to address the difficulties that come with enterprise data. Over 30 experts specializing in data infrastructure, architecture, and governance have come together to monitor the data the bank holds and ensure AI applications are being built with the right data in mind. The data and AI teams are working closely so the AI algorithms will use appropriate, high-quality data.
“The reason we have the Center of Excellence is we want to continue to build on AI, and we understand this is one of the foundational areas that is needed,” said Katherine Wetmur, head of quality assurance and production management.
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AI and Machine Learning are becoming more common in financial institutions, helping to sort and analyze data, but what if that data is bad? “While most popular discourse centers on data privacy concerns, one of the more serious negative impacts is the bias that lives within the data that feeds these systems and uses it to become more intelligent,” said Navin Sharma, Vice President, Product Management at Pitney Bowes.
“If you look beyond these broad challenges and look more closely at how organizations could start to use AI in their everyday decision making, the picture becomes even darker. AI has brought us the era of “black-box” decision making that is casting aside traditional decision-making processes, the kinds that have been made by consensus in meetings between people or driven by human-programmed business rules,” said Sharma. For financial institutions, ensuring the quality of data that is being fed to AI programs is just as important as the program itself.
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While AI is being used for high-value tasks like AML efforts, it is also used by many financial institutions for simpler tasks like customer service. In today’s digital world, when that service is not available, it causes a big issue. Because of this, Danske Bank and IBM have partnered to create predictive insight technology that can predict an outage before it happens, in hopes of preventing them.
“Banking is complex and AI is something that helps a human being to deal with complexity in a more efficient manner,” said Craig Ian Alexander, senior vice-president and co-head of IT operations at Danske Bank. This partnership and AI technology is in its initial phases but hopes to improve customer experience and bank preparedness in the event of an outage.
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