Nand Kishor Contributor

Nand Kishor is the Product Manager of House of Bots. After finishing his studies in computer science, he ideated & re-launched Real Estate Business Intelligence Tool, where he created one of the leading Business Intelligence Tool for property price analysis in 2012. He also writes, research and sharing knowledge about Artificial Intelligence (AI), Machine Learning (ML), Data Science, Big Data, Python Language etc... ...

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Nand Kishor is the Product Manager of House of Bots. After finishing his studies in computer science, he ideated & re-launched Real Estate Business Intelligence Tool, where he created one of the leading Business Intelligence Tool for property price analysis in 2012. He also writes, research and sharing knowledge about Artificial Intelligence (AI), Machine Learning (ML), Data Science, Big Data, Python Language etc...

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Financial institutions turning to artificial intelligence for data mining, cost savings

May 1, 2017 | 846 Views

BB&T Corp. has a well-earned reputation for being deliberate when it comes to adopting technological advances.

That's why BB&T executives' enthusiasm for plugging artificial intelligence and robotics into its back-office, customer service and compliance operations has raised eyebrows with analysts and economists.

BB&T joins Wells Fargo & Co. and other national and super-regional banks in spending hundreds of millions of dollars to pursue what they believe will be significant future cost savings from data mining of customer patterns.

"We are investing in improving processing cost- a big opportunity for us and frankly all banks - by the use of artificial intelligence and robotics," Kelly King, the bank's chairman and chief executive, told analysts during its first-quarter earnings report April 20.

"We will be pretty aggressive about that. We just think there are huge ways to reduce cost in the backroom by the use of that."

Forbes magazine called artificial intelligence's potential for financial institutions "immense" because of its broad operational reach, such as: "including natural language processing (improving interactions between computers and human languages); machine learning (computer programs that can "learn" when exposed to new data); and expert systems (software programmed to provide advice) that help machines sense, comprehend and act in ways similar to the human brain."

According to analysts, financial institutions have been slower adapters of AI and robotics.

Yet, research firm The Financial Brand said those companies are recognizing "the potential for cloud computing and machine learning algorithms, along with rising pressures brought by new competition, increased regulation and heightened consumer expectations."

"They all have created a 'perfect storm' for the expanded use of artificial intelligence in financial services," such as product delivery, risk management and marketing.

"New cognitive-based solutions also enable a more pro-active and personal customer experience at a lower cost than was ever possible before," The Financial Brand said.

The group said its 2017 retail bank trend report determined that increasing use of AI and robotics was the second most popular expectation of financial institutions. Read More

Source: Journalnow
Nand Kishor Contributor

Nand Kishor is the Product Manager of House of Bots. After finishing his studies in computer science, he ideated & re-launched Real Estate Business Intelligence Tool, where he created one of the leading Business Intelligence Tool for property price analysis in 2012. He also writes, research and sharing knowledge about Artificial Intelligence (AI), Machine Learning (ML), Data Science, Big Data, Python Language etc... ...

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Follow on

Nand Kishor is the Product Manager of House of Bots. After finishing his studies in computer science, he ideated & re-launched Real Estate Business Intelligence Tool, where he created one of the leading Business Intelligence Tool for property price analysis in 2012. He also writes, research and sharing knowledge about Artificial Intelligence (AI), Machine Learning (ML), Data Science, Big Data, Python Language etc...

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