Using AI to Drive Business Growth in Banks

Falk Rieker, ‎Global Vice President, Global Head of IBU Banking at SAP 

While the banking sector recognizes artificial intelligence (AI) as an innovative tool that can drive business growth and streamline operations, adoption is still in the early stages.  Banks have been slower to implement AI because all they know is that they need this technology – but they haven’t figured out ‘why’ just yet. According to an Oxford Economics study, while executives believe that AI is important to the finance function’s successful performance today, only 18 percent believe it is critically important.

This is a dilemma that a multitude of industries face when it comes to new technology – balancing the reward and risk of being an early or late adopter of new technology.IDC predicts that over the next three years, seven of the top 10 cognitive/AI use cases will be industry-focused, totaling 85 percent of priority investments. AI is a must-have solution in bankers’ tool boxes. AI improves the customer’s digital experience and drives greater efficiency. This technology can also enhance the competitive advantage of banks and increase profitability. Below are three key factors bankers should consider when implementing AI.

Sharpen your competitive edge

In the tug-of-war between fintech and finserv, banking leaders have been quick to create innovation labs to research new technologies such as AI. Few institutions, however, have moved forward with applying the technology to the business to achieve key objectives. At the speed with which consumer expectations are evolving in the digital era, banks must ensure they are leveraging the latest solutions. Quantiply delivers AI-powered financial crime, risk and compliance software solutions for banks helping to increase efficiency. Using Quantiply’s Sensemaker solution, banks can address know your customer (KYC), anti-money laundering (AML), sanctions monitoring and market abuse to easily detect fraudusing real-time updates. With a strong digital core, banks can remain nimble and easily adapt to factors such as changing customer expectations and global market volatility.

Enable customer-centricity

There are a myriad of applications for AI technology. For most industries, becoming more customer-centric is a critical first step toward identifying how a technology will increase the value of business. However, determining which business objective should be a priority for a bank needs to be the first step. When you strip any business down to its most basic form, it always boils down to the customer. By thinking of the outcome first and the technology second, banks can capitalize on key windows of opportunities. When banks listen and truly understand the needs of their customers, they can optimize the technology to ensure they are delivering personalized and value-added services.

With AI, banks can analyze mass amounts of data to create more robust customer profiles allowing them to provide more individualized offerings to customers, instead of a host of generic offerings. Banks can provide personalized services and products to customers based on their purchase history, income or age. The Bank of One has evolved to match customer needs with their digital banking experiences. For example, banks provide personalized ATM messages based on customer preferences and ‘favorites’ that appear highlighted on the screen depending on the customer’s history of ATM usage. By building an AI system centered around predictive analytics, customers will benefit from real-time updates based on their preferences. Over time, this individualized attention will allow banks to build greater customer loyalty.

Bring efficiencies to the back-office

While much of AI has been focused on the front office, the technology can also help expedite back-end processes.Many functions in the back office offer a tremendous opportunity for banks to radically transform the landscape.A notable example of AI in the backoffice can be found in EZOPS, a fintech company that supports middle and back-office digital transformation by providing AI-fueled services for banks seeking growth in capital markets.

Often, trading staff at banks spend too much time conducting repetitive, mundane tasks to reconcile data. EZOPS designed a product called ARO to help companies predict and resolve breaks by streamlining operations, reducing risk and redirecting employees to higher-value responsibilities. The company helps top-level asset managers and fund administrators involved with heavy trading volume including equities, cash and commodities at banks and insurance firms.

How to navigate the road to digital transformation

When it comes to new technology such as AI, it is important to have the big picture in mind and to identify how that technology can help the company progress. AI is one of the most valuable pieces of emerging technology that can help banks delight customers through a more personalized customer experience, through streamlining back-office efficiencies and through strengthening competitive differentiators. Banks that deploy this technology effectively will have happier customers, more cost-effective operations and will be a competitive force to be reckoned with.

Falk Rieker, ‎Global Vice President, Global Head of IBU Banking at SAP 

While the banking sector recognizes artificial intelligence (AI) as an innovative tool that can drive business growth and streamline operations, adoption is still in the early stages.  Banks have been slower to implement AI because all they know is that they need this technology – but they haven’t figured out ‘why’ just yet. According to an Oxford Economics study, while executives believe that AI is important to the finance function’s successful performance today, only 18 percent believe it is critically important.

This is a dilemma that a multitude of industries face when it comes to new technology – balancing the reward and risk of being an early or late adopter of new technology.IDC predicts that over the next three years, seven of the top 10 cognitive/AI use cases will be industry-focused, totaling 85 percent of priority investments. AI is a must-have solution in bankers’ tool boxes. AI improves the customer’s digital experience and drives greater efficiency. This technology can also enhance the competitive advantage of banks and increase profitability. Below are three key factors bankers should consider when implementing AI.

Sharpen your competitive edge

In the tug-of-war between fintech and finserv, banking leaders have been quick to create innovation labs to research new technologies such as AI. Few institutions, however, have moved forward with applying the technology to the business to achieve key objectives. At the speed with which consumer expectations are evolving in the digital era, banks must ensure they are leveraging the latest solutions. Quantiply delivers AI-powered financial crime, risk and compliance software solutions for banks helping to increase efficiency. Using Quantiply’s Sensemaker solution, banks can address know your customer (KYC), anti-money laundering (AML), sanctions monitoring and market abuse to easily detect fraudusing real-time updates. With a strong digital core, banks can remain nimble and easily adapt to factors such as changing customer expectations and global market volatility.

Enable customer-centricity

There are a myriad of applications for AI technology. For most industries, becoming more customer-centric is a critical first step toward identifying how a technology will increase the value of business. However, determining which business objective should be a priority for a bank needs to be the first step. When you strip any business down to its most basic form, it always boils down to the customer. By thinking of the outcome first and the technology second, banks can capitalize on key windows of opportunities. When banks listen and truly understand the needs of their customers, they can optimize the technology to ensure they are delivering personalized and value-added services.

With AI, banks can analyze mass amounts of data to create more robust customer profiles allowing them to provide more individualized offerings to customers, instead of a host of generic offerings. Banks can provide personalized services and products to customers based on their purchase history, income or age. The Bank of One has evolved to match customer needs with their digital banking experiences. For example, banks provide personalized ATM messages based on customer preferences and ‘favorites’ that appear highlighted on the screen depending on the customer’s history of ATM usage. By building an AI system centered around predictive analytics, customers will benefit from real-time updates based on their preferences. Over time, this individualized attention will allow banks to build greater customer loyalty.

Bring efficiencies to the back-office

While much of AI has been focused on the front office, the technology can also help expedite back-end processes.Many functions in the back office offer a tremendous opportunity for banks to radically transform the landscape.A notable example of AI in the backoffice can be found in EZOPS, a fintech company that supports middle and back-office digital transformation by providing AI-fueled services for banks seeking growth in capital markets.

Often, trading staff at banks spend too much time conducting repetitive, mundane tasks to reconcile data. EZOPS designed a product called ARO to help companies predict and resolve breaks by streamlining operations, reducing risk and redirecting employees to higher-value responsibilities. The company helps top-level asset managers and fund administrators involved with heavy trading volume including equities, cash and commodities at banks and insurance firms.

How to navigate the road to digital transformation

When it comes to new technology such as AI, it is important to have the big picture in mind and to identify how that technology can help the company progress. AI is one of the most valuable pieces of emerging technology that can help banks delight customers through a more personalized customer experience, through streamlining back-office efficiencies and through strengthening competitive differentiators. Banks that deploy this technology effectively will have happier customers, more cost-effective operations and will be a competitive force to be reckoned with.