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A Pulse on Digitization in Banking Part 4: How Remote Work & the Great Resignation Encourage Digitization

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In the wake of the pandemic and the move to everything remote, banks have had to shift priorities and processes. As a result, the banking industry quickly pivoted customers to online and mobile-based banking experiences.

The “Great Resignation” has also left its mark on the industry. 4.3 million people quit their jobs in May 2022 and another 4.2 million quit in June 2022. Financial institutions of all kinds found themselves strapped for workers, pushed into adopting digital means to fill the labor void.

These two pandemic-induced phenomena have lent to greater adoption of cloud technology, automation, and artificial intelligence. In this blog, the fourth in our series on digitization in banking, we’ll explore the impact of these three technologies on the banking industry.

Cloud adoption

Cloud adoption is often step one of the digital transformation processes. This is because the scale and flexibility of cloud enables organizations to adopt other new digital technologies. The shift to remote work – and remote everything else – during the pandemic forced banks to adopt cloud technologies more hastily.

There are a few reasons for banks to adopt cloud strategies now.

Keep up with the competition

Migrating from legacy systems can be daunting. However, it’s necessary for banks to make the transition to keep up with cloud-first, digital-native competitors like neobanks and fintechs. Luckily, banks don’t need to go all-in on cloud to take advantage of the opportunities it presents. Many take a hybrid approach, opting to maintain existing legacy hardware while adopting cloud for some use cases.

Harness near-limitless scalability

According to one study from GFT, 86% of bankers have adopted cloud to take advantage of its nearly limitless scalability.

The way consumers bank has changed how banks operate. As consumers require greater personalization and better digital experiences, banks must answer their needs. Cloud architecture can be scaled or down as the digital needs of banks – and their customers – expand. Any bank considering investing in digital tools to enhance their business must consider the scale their network enables them to achieve.

Optimize costs

Cloud technology requires virtually no hardware, making it cheaper to install and easier to maintain. There’s no need for dedicated staff to upkeep the physical infrastructure required for legacy systems. What’s more, cloud service providers often offer flexible pricing options, allowing you to pay for what you use – not any more. With hardware-based systems, you won’t get that level of flexibility and you often end up overpaying for bandwidth you don’t use.

It’s not surprising, then, that 81% of bankers responding to the GFT survey note that they adopted cloud technologies to save costs. How much your company saves with cloud computing depends on what infrastructure you’re using now and related costs.

Move digital initiatives forward

Regardless of what form your digital transformation journey takes, cloud technology will play an essential, foundational role. Moving data to a centralized, virtualized location is the first step in taking full advantage of it. All banks have rich troves of customer data these days. Whether they’re able to use that data depends largely on how it’s stored and managed. Once data is in one location, teams can then use it to extrapolate meaningful consumer insights to provide better customer experiences.

Remain secure

One of the most common and harmful misconceptions about the cloud is that it’s less secure than on-prem. Cloud service providers actually build security into their tools. Still, it’s important for banks to consider where in their technology stack vulnerabilities may lie as they formulate cloud strategies.

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Building upon a cloud foundation

All in all, a robust cloud strategy can help a bank achieve optimal network efficiency. One Zayo customer, a global investment bank, was able to boost security, streamline data, increase agility and network flexibility, and save on costs by leveraging Zayo CloudLink to connect from their private cloud to multiple cloud providers.

Cloud adoption is the first step to being able to take advantage of the following two technologies, so it’s critical to start with a robust cloud strategy.

Automation

In the midst of widespread resignation, banks are finding themselves strapped for employees across the board. One way to help alleviate some of the burden employees face and avoid burnout and further staff losses is through automation. By automating mundane, everyday tasks, banks can free up their employees to work on more thought-intensive, pressing matters. There are a few areas where automation can help mitigate some of this burden.

Banking operations

Automation can help support middle and back-office workflows like check deposits and wire transfers. Deposit automation, for example, validates check images when they’re deposited, eliminating the need for employees to clear them manually. This can help both free up time and lessen the chance of human error.

Customer service

Automated systems like chatbots and phone voice assistants can support simple customer queries. By answering simple questions, this technology reduces some of the load on call center staff. Plus, these technologies can streamline conversations representatives have with customers by giving them a good picture of the customer’s question before they speak with them. This leads to better conversations and customer satisfaction.

Application and loan processes

Checking over applications and documents to approve loans, open credit cards, and more can prove to be a tedious task. Luckily, automation can lighten some of the load here. By processing documents through automation, banks receive more accurate documentation that are less prone to human error. It can also make it easier for customers to fill out forms and applications by automatically filling out information that exists in the system already. Plus, automation tools can detect fraud by instantaneously cross-checking content across documents and other sources.

Employee recruitment

Human resources traditionally spend a lot of their time looking over resumes in search of relevant skills and information. Thankfully, automation tools take some of this work off of their plates by screening resumes and cover letters for skills and other keywords to weed candidates out or move them ahead.

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Artificial intelligence and machine learning

Artificial intelligence and machine learning can further cut down on time human employees spend doing manual tasks while providing greater insights, strengthening security, and enabling more informed decision-making. It’s no wonder 75% of respondents at banks with over $100 billion in assets are implementing AI strategies today. AI and machine learning can support banks in the following ways.

Customer identity and authentication

By enabling individual voice, face, and fingerprint identification through AI, customers can more easily access accounts and banks can reduce fraud and identity theft.

NATWEST, a UK-based bank, takes AI-based biometrics to the next level by allowing customers to open a bank account with a selfie to verify ID documents. This removes friction for customers and bank employees, cutting down time to open an account while increasing account security.

Personalization

By examining customer data, artificial intelligence and machine learning algorithms can provide meaningful insights and recommendations based on predictions. By automatically offering tailored product recommendations, investment options, and advice, AI can foster a better overall customer experience.

Credit scoring and lending

These tools can also give lenders a better understanding of a customer’s creditworthiness. By analyzing the wealth of customer data banks have on-hand, machine learning algorithms can offer more robust and more accurate credit scoring models. This can help the bank make better lending decisions.

Fraud prevention and risk management

Finally, AI and machine learning can help with one of the most costly issues facing the banking industry – fraud. American consumers alone lost $5.8 billion to fraud in 2021. To combat this issue, some banks are leveraging artificial intelligence to monitor threats and breaches, both on the consumer side and internally.

This technology can learn patterns and indicators for fraud and aid in predicting them and preventing them. As digital tools change and improve, so will cybercrime. Leveraging intelligent, insightful tools is an integral part of fighting this next generation of fraud.