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The Top Priorities for Artificial Intelligence in Banking in 2022 | Technology

The Top Priorities for Artificial Intelligence in Banking in 2022 | Technology
The Top Priorities for Artificial Intelligence in Banking in 2022 

Artificial Intelligence in Banking: Top Priorities for 2022 

Bank and credit union executives know they need to integrate AI into the daily operations of their institutions.  The potential use cases are almost limitless.  Some, such as chatbots, are well-known but have not yet been widely implemented.  Here are five of the most promising applications of artificial intelligence in banking.

Artificial intelligence in financial services is still filled with largely untapped potential.  While many bankers may think of things like chatbots and fraud monitoring when it comes to AI, in reality the technology can be used in any conceivable part of a bank or credit union.

For the most part the industry hasn't even scratched the surface of how AI could transform banking.  Here are some of the top ways financial institutions can implement Artificial Intelligence in 2022 and beyond.

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Smart Chatbot and Digital Assistant

Let's start with the most obvious application first.  Some banks and credit unions already deploy chatbots, but so far most perform only basic functions, with few exceptions.  Those who use more advanced artificial intelligence to provide predictive insights are commonly called digital or virtual assistants.  But as AI and natural language processing become more advanced, expect these intelligent digital assistants to play a bigger role in a consumer's financial life.

Numerous surveys and market research studies have found that people actually prefer to interact with bots rather than humans.  Although some of these surveys are conducted by conversational AI vendors, skeptics should consider the fact that Bank of America digital assistant Erica has 24 million users and completed 123 million interactions in the fourth quarter of 2021, the year that  247% higher year on year.

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Conversational AI is enabling chatbots to provide customers with predictive and personalized financial insights, a trend that will only continue. 

"The quality of chatbots will definitely improve in the next few years," says software solutions firm Light IT.  "They will more accurately predict human behavior and use this information to learn on their own."

For example, USAA upgraded its EVA virtual assistant in 2022 to understand more customer "intentions," including when they use slang.

Chatbots also save time and money by reducing human interaction with customers.  Juniper Research estimates that chatbot interaction will save 862 million hours for banks globally, which equates to $7.3 billion in cost savings.  This is just one area that AI can help build proficiency in, as explained next.

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Building Internal Competencies

If you've been in banking even for a while, you're already sick of hearing the word "silos."  Even so, it's actually true that many financial institutions have a silent structure, and often the systems and techniques used by different lines of business don't "talk" to each other—at least not in those ways.  which can be used easily.  This leads to internal inefficiencies and unnecessary manual work.

As McKinsey noted in the AI ​​report, most banks' data is split across separate business and technology teams, and analytics efforts are focused on use cases alone.  This makes it difficult to obtain complete information about each customer and provide personalized, customized digital services.

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AI can help add to that data and enable banks to perform "analysis from internal and external sources for millions of customers, in (near) real time, at the point of decision across the organization," notes McKinsey.  .

This will ultimately not only create internal efficiencies, but also facilitate greater customer experience.

Banking customers transact through ATMs, physical branches, contact centers and mobile and online banking -- creating friction in the journey, observes James Freeze, chief marketing officer for AI company Interactions at Forbes.  "Consumers should not go looking for insights into their mortgages, savings or investments. These information should be proactively offered across all channels, and AI can facilitate that."

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A more personalized customer journey

It is well known that customers want more personalization and customization from their banks.  But many institutions fail to provide such experience.  AI can help in this regard.

AI-powered data analytics can enable banks and credit unions to better understand customer needs, says Jim Maras, co-publisher of The Financial Brand and CEO of Digital Banking Report.  This will ultimately enable them to act as a "concierge" for clients, proactively providing insights to them based on real-time financial opportunities or threats.

"The power of data, advanced analytics and artificial intelligence will be at the foundation of consumer engagement, making autonomous, real-time decisions without human intervention," Maras said in a white paper.

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Golden Data: One of the biggest possibilities of AI is to help banks convert their 'treasury' of data into useful insights for customers and wallet share for the institution.

Major retail companies such as Amazon, Netflix, Kroger and PayPal already use data analytics and artificial intelligence to tailor product discounts and recommendations to their customer base, notes financial education technology company Everfee in a blog.  AI can help financial institutions dig into their data to find similar opportunities.

Everfee writes, “With no paucity of customer data, financial institutions are sitting on a treasury of answers as to where customers are going next and what their financial needs will be soon.”  “With that data, institutions can increase their wallet share and generate revenue by perfecting their products and services to customers in anticipation of their time of need.”

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Lending and Loan Decisions

Artificial Intelligence can play a vital role in not only taking credit decisions faster, but also ensuring that banks are able to easily identify applicants who have high chances of returning the loan.

An individual's creditworthiness, so far, has largely been based on past credit history and current earnings.  AI, on the other hand, can power predictive models of an individual's ability to repay a loan, as opposed to relying on historical data. 

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Expansion of loan pool

The combination of alternative data and AI enables banks and credit unions to make better lending decisions and lend to a wider range of borrowers.

By using AI to analyze data, banks can qualify new customers for credit services, lowering the risk of loan limits and pricing, and even fraudulent loan applications, McKinsey says.

The firm notes, "Distinguishing themselves from traditional banks... AI-first banks have created streamlined lending journeys using extensive automation and near-real-time analysis of customer data."

AI can also be used for more inclusive lending, enabling access to a wider range of financial products, streamlining the application process to make it more accessible, and demonstrating credit scoring free of human bias. 

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“For lenders, it combines a socially-oriented strategy with a great marketing tool,” said Dmitry Dolgorukov, co-founder of HES Fintech, in a BAI post.  “Borrowers, even those with thin files, stand a better chance of obtaining financing at a fair price. For the financial industry as a whole, expanded access to finance without compromising the financial stability of lenders and borrowers  Looks like a great match."

One caveat: So-called "black box" lending has also drawn scrutiny from members of Congress and the Consumer Financial Protection Bureau.  Financial institutions must be able to demonstrate that the AI ​​technology they use does not involve inherent bias.

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Rapid response to fraud and Cyber Security issues

With the sheer number of transactions that banks must process today, it is incredibly easy for fraud to slip through the cracks.  In just one area, P2P payments, scams are on the rise.  Fraudsters are using increasingly sophisticated tools and tactics to circumvent traditional defenses designed to detect and prevent fraud.

Rating agency Fitch surprisingly states that only 1% of money laundering activity is currently detected.  It's no surprise that fraud and security are one of the top use cases for artificial intelligence that bank executives are looking at, according to the Economist Intelligence Unit's survey.

The survey said that banks are looking at AI to not only reduce losses and use resources more efficiently, but also improve customer experience.  “Mastercard, for example, uses data on transactions and authorizations to predict and detect fraud more accurately and quickly: reducing false positives means fewer legitimate transactions are closed, increasing the customer experience.  Improvements happen."

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These are not just frauds like money laundering, but attacks that directly target customers that banks should be wary of.  According to Kevin Goschalk, CEO of fraud and security company Arkose Labs, banks experienced a 70% increase in account takeover attacks targeting bank customers in 2021.

AI can be used to help detect and prevent these attacks.

“The threat of a quickly evolving attack makes it difficult for fraud teams at banks to get ahead of bad actors,” Goschalk told Financial Brand.  "That's why AI is an extremely important component in effectively detecting and preventing fraud."

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For example, banks can use AI to better understand online traffic patterns, Goschalk says.  The technology can help determine specific valid device fingerprints for customers over a given time period, which helps banks determine the right action and response to take in real time.

Source: Bryan Yurcan, The Financial Brand, Direct News 99