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Understanding the Impact of Quantum Computing and AI on Cybersecurity

By Rob Foxx

The topics of quantum computing and AI are often new and confusing—and unfortunately, they haven’t been well explained to many people. However, these technologies are already changing the ways in which attackers gain access to systems and data.

According to a recent report by Mimecast, 95% of breaches are caused by human error. This staggering figure highlights the critical importance of training your staff as a core part of any cybersecurity strategy. These errors typically occur because someone or something appeared legitimate enough to prompt user action. This allows attackers to bypass most traditional security controls, since the malicious action is performed by an authorized user. As technology continues to evolve, we can expect human error to play an even greater role in future breaches.

How Quantum Computing Changes the Game
Before diving into its implications, it’s important to define what quantum computing actually is. Traditional computers use binary logic, representing data as either a 1 or a 0. In contrast, quantum computers leverage qubits, which can represent 1 and 0 simultaneously through a principle called superposition. This allows quantum computers to evaluate many possibilities at once, significantly accelerating complex computations.

While quantum computing demands more power and specialized hardware, its speed poses a serious threat to current cybersecurity defenses. For example, tasks like reversing a hash (e.g., an encrypted password) — which would take traditional computers days, weeks, or even years — can potentially be performed in a fraction of the time using quantum technology.

Quantum computing can also enable more sophisticated malware, especially under ransomware-as-a-service models, and may dramatically accelerate the discovery of zero-day vulnerabilities — making patching and proactive defense more critical than ever.

The Role of AI in Evolving Threats
Artificial Intelligence, at this point, should be a familiar concept. AI consumes vast amounts of data, analyzes it, and uses that as a foundation to learn, reason, and solve problems. While it’s far from perfect, AI has become a powerful tool — especially for bad actors.

Cybercriminals are now using AI to improve their research, enhance targeted phishing, and execute more convincing social engineering attacks. With access to better, more personalized data than ever before, AI-generated threats can appear highly authentic — even to seasoned users.

Additionally, AI can be used to create ransomware faster, with greater effectiveness, and with less technical skill required than in the past. These advantages make AI an indispensable tool for attackers — and a growing concern for defenders.

What You Can Do
The most important thing you can do today is educate your team and ensure you have access to cybersecurity experts who can help manage these risks. Strong security practices are more critical than ever, including:
•  Longer passwords, as recommended by National Institute of Standards and Technology (NIST)
•  Multi-factor authentication (MFA) for system access
•  Continuous logging and review of activity within your environment

In addition, legacy tools are no longer sufficient on their own. Many environments now require upgraded solutions, such as:
•  Next-generation antivirus (NGAV)
•  Managed Detection and Response (MDR) services from providers like Cynet 360, CrowdStrike, and SentinelOne

These solutions can analyze logs, detect threats, and issue alerts far more quickly than human analysts ever could. They typically cover:
•  User behavior analytics
•  System and process monitoring
•  Network traffic inspection
•  File and endpoint analysis

Most importantly, these tools are also AI-powered, allowing them to defend against AI-driven attacks using similar technology. In the rapidly evolving cybersecurity landscape, staying ahead means adopting the same tools and techniques your adversaries are using — and doing it before they do.

Foxx is director – infosec and IT audit services for FIPCO, a WBA Gold Associate Member.

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AI Process Automation Q&A With Tim Schneider, CEO and President of Bank Five Nine

Bank Five Nine CEO and President Tim Schneider generously shared insights from Bank Five Nine’s experiences with AI process automation.

At Bank Five Nine, we use a combination of Blue Prism, Python, and JSON as the foundation of our robotic process automation. Each of these tools has its strengths and weaknesses. Some automation uses a combination of all three.

What specific banking processes has your institution automated using AI-driven robotic process automation, and what impact has it had on efficiency?
When we first started our automation initiatives, forty-eight (48) use cases were identified as potential candidates for automation. The following automation processes are in production:

Monthly Auditing
•  Run monthly reports from Encompass and upload to StoneHill site/portal for auditing to meet GSE and government loan program requirements in Encompass. File and maintain selected loans in Encompass for access by StoneHill.

Use dates and data from loans in Fiserv Premier to automate emails to borrowers
•  First payment details/reminder
•  Subsequent Payments, as due after a certain date
•  Escrow activity notification (pre and post)

Update Customer Information in Premier
•  Read Activity reports provided by 3rd party and perform maintenance in Navigator

Operation Support Maintenance Tasks
•  Closed Accounts
•  eStatement Setup
•  Missing Endorsements

Non-post
•  Review report and post to an existing account or return maintenance

Rendering Statements
•  Automation of the rendering process

COLD Commit Bot
•  Commit all COLD reports parsed into Digital Imaging. The bot emails stakeholders that the process has been completed and that reports are available for the day.

EBC Parser
•  Reviews text files from Fiserv that list login attempts for Business OLB users and counts any user with 12+ login attempts.

Check Image Data Extraction
•  Review OCR data collected from Director Imaging Automated Indexing and exports it to a file location. This data is compared against the Teller Check report to assign a check number (from the check image) to the payee/remitter/amount data. This is
then compiled and sent to MoneyGram. The purpose is to add the Payee name so MoneyGram can lower the risk associated with cashier’s checks.

Zelle Balancing/Transfer Reports
•  RPA Blue Prism, Director workflow, and Python scripting are used. Reports from our online banking system are exported by a bot. Director Imaging exports a text file from Fiserv. A Python script then compares the two reports to identify Zelle transfers that were made by customers after the Fiserv cutoff. These transfers were causing our GLs to be out of balancing due to the difference in cutoff times between Fiserv and NCR OLB.

HMDA Score Update
•  RPA BluePrism bots generate a report from our LOS monthly. The bot then goes into each loan on the report and updates the data based on the generated report.

Loan Maintenance Review
•  We use BluePrism to export an autogenerated text report from Fiserv and use an input file with several keywords to search for maintenance that needs to be reviewed. There are two separate bots for Commercial and Retail loan operations teams.

Online Banking Activity Reporting
•  RPA Blue Prism is used to export documents for archiving and retrieval in Director Imaging. This is a daily process. We maintain records for failed logins, eStatement sign up, enrollment, new transfers, etc.

Loan Document Export for Disaster Recovery
•  RPA Blue Prism is used to export documents for archival in Director. The bot processes closed loans daily.

Reg CC Review
•  Bots use Director Import PDF Processor and Workflow to route checks to Operations Support to place holds. Operations uses options within the workflow to approve, deny, or void the Reg CC requests. Branches receive auto-notifications from workflow based on the activity of Operations Support

Debit Card Review
•  Auto-review common maintenance types to eliminate the need for manual review on all items. From an efficiency perspective, the processes that we have automated have greatly reduced the number of hours associated with that process. People still must review the output to ensure that it is correct and troubleshoot the automation if it errors off. We reduced the tasks, not the responsibilities.

What lessons did your bank learn during the implementation of AI for process automation? Were there any unexpected challenges or benefits?
Automation is not a create it and forget it process. Automation is an iterative process. Continuously changing and evolving as technology and business processes change. Data quality and process mapping are key to success. Having people who know why things are done the way they are is so critical to success.

Which repetitive tasks at your bank have been the easiest to automate, and which have proven more complex?

The tasks that have been the easiest to automate are the ones with processes that are clearly defined and whose outputs/outcomes are known. Example: Did the customer specify that they wanted an e-statement? Yes or No. Any process that, while clearly defined, has multiple outputs/outcomes and triggers other processes based on those outputs/outcomes has been the most challenging.

Has AI-driven automation improved accuracy in your bank’s operations?
Yes and no. Data quality is critical to success. The automation is only as good as the information that we feed it.

What advice would you give to other community banks considering AI for process automation, particularly in balancing technology adoption with maintaining a personal touch in customer service?
Focus on customer needs: Internal / External. Ensure that the automation addresses the specific needs and expectations of the customer.

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Harnessing AI for Process Automation in Banking: Smarter, Faster, and Yes More Human

By Katie Reiser

Banks face mounting pressure to streamline operations, enhance customer service, and stay competitive in a fast-evolving digital world. Artificial intelligence (AI) is no longer a buzzword — it’s a key driver of modern banking operations. Among its most impactful uses: process automation.

AI-assisted process automation falls into two main categories: Robotic Process Automation (RPA) and Business Process Automation (BPA). While similar, they serve distinct functions.

RPA vs. BPA: What’s the Difference?

(In the spirit of embracing AI, I asked ChatGPT to explain the difference.)

Robotic Process Automation (RPA) involves using software “bots” to mimic repetitive human tasks. Common examples in banking include extracting data from forms, moving data between systems, and sending routine notifications. When paired with AI, RPA becomes smarter — bots can understand natural language, process unstructured data, and even make basic decisions. For instance, AI can enable bots to read loan applications and extract relevant data, reducing manual input errors.

Business Process Automation (BPA), on the other hand, focuses on end-to-end workflows. AI-assisted BPA doesn’t just mimic tasks — it analyzes and optimizes entire processes. Think of onboarding a customer: BPA can automate ID verification, credit checks, and document collection, all while AI determines the fastest and most efficient path based on real-time data. BPA is typically broader in scope than RPA and integrates more deeply with business systems.

Streamlining Banking Operations with AI
•  Customer Service: AI chatbots and virtual assistants can manage routine inquiries 24/7, freeing staff to handle more complex needs. Bank of America’s Erica handles millions of monthly interactions, helping with tasks like transaction searches and bill reminders.
•  Fraud Detection: AI rapidly scans transactions for anomalies, flagging potential fraud in real time — faster and more accurately than manual reviews.
•  Loan Processing: AI tools analyze credit reports, verify income, and assess risk more efficiently. JPMorgan Chase has slashed contract review times from thousands of hours to seconds using AI.
•  Compliance and Risk: AI helps monitor regulations and analyze internal policies. Automation reduces errors and allows teams to focus on higher-value compliance work.
•  Back Office Operations: AI driven RPA automates data entry, reconciliations, and report generation, cutting turnaround time and cost.

Making Work More Human
Rather than replacing employees, AI often enhances their roles. By offloading repetitive or low-value tasks to automation, bank employees can focus on work that requires judgment, creativity, and human interaction.

For example, instead of spending hours manually checking documents, a loan officer can spend more time consulting with customers on the best financial products for their needs. This not only improves employee satisfaction but also enhances the overall customer experience.

Kathy Strasser, EVP, chief operating officer/ chief information officer with IncredibleBank in Wausau, was a panelist for the popular AI in Action session during WBA’s Bank Executives Conference. When asked by panel moderator Eric Cook, chief digital strategist with WSI Digital (who also runs GSB’s Digital Banking School and teaches for the WBA’s School of Bank Management), about reassuring staff who may be uneasy with AI and concerned that it will ultimately replace employees, Strasser shared, “It’s about helping our employees get rid of the mundane part [of their jobs] so they can do the higher value things they want for their career path.”

Pitfalls and Considerations
While the benefits are compelling, banks should be aware of the challenges and risks associated with AI-assisted automation:
•  Data Quality: AI models are only as good as the data they are trained on. Poor data quality can lead to incorrect decisions or biased outcomes.
•  Over-Reliance on Automation: Not all processes should be automated. Some tasks require human oversight, especially when ethical or legal considerations are involved.
•  Cybersecurity and Privacy: Automated systems that handle sensitive customer data must be secure and compliant with data protection laws like GDPR or GLBA.
•  Change Management: Integrating AI into banking operations requires a shift in mindset and process. Employee training, clear communication, and stakeholder buy-in are crucial to successful implementation.
•  Regulatory Scrutiny: Regulators are increasingly focusing on how AI is used in financial services. Banks must ensure transparency and explainability in their AI systems.

Getting Started
For banks considering AI-assisted automation, the following steps can help:
1.  Start Small and Have a Goal: Be clear on what you want to accomplish. Often the need to gain speed, cut costs or improve the customer experience are different. Identify low-risk, high-volume tasks suitable for automation.
Gain quick wins and build confidence.
2.  Assess Readiness: Evaluate your current tech infrastructure and data maturity.
3.  Choose the Right Tools: Consider whether RPA, BPA, or a hybrid approach best suits your needs.
4.  Ensure Governance: Establish frameworks to monitor AI performance, ensure compliance, and manage risks.
5.  Invest in People: Train staff on new tools and encourage a culture of innovation and continuous improvement.

Also serving on the AI in Action panel were Forward Bank’s COO Sheri Dick and Chris Nichols, Director of Capital Markets at SouthState Bank, who shared their approaches to governance. Nichols said, “We started with a steering committee and that evolved into an AI working group. This led to a charter and policy which evolved into having a full governance framework that outlines procedures and requirements and then added an AI strategy.” Nichols added, “I’m a big fan of aligning your business goals with your AI goals.”

Dick explained, “We have a governance policy and a practical use policy, but what we did from a foundational standpoint is we had an AI education session for all employees. A lunch and learn to help them understand… What is AI? What are the definitions of AI? What are the practical uses of AI?” She added, “These training sessions got everyone level set and gave us a foundation for each employee and we started from there.”

Regarding to investing in people, Nichols highlighted an unexpected benefit, “It makes for more confident employees. That’s not something that we really thought about when we originally made the AI use case. But what we found when we do our employee satisfaction survey every quarter, the more they use AI, the more confidence they have.”

Putting AI into Action
Cyrene Wilke, Chief Operations & Information Officer, Executive Vice President with Horicon Bank and another AI in Action panelist, offered this advice to banks considering using AI for process automation, “Start with focusing on opportunities to gain efficiencies in the back of the house in operations. Most banks will find processes being performed manually that can be fully or at least partially automated. Finding ways to be more efficient can free up time to provide better, more personalized customer service.”

Cook shared this insight, “I don’t want to make it sound like AI is going to be the panacea that’s going to solve all of your problems, but if it sparks that dialogue in your organization to make you question why you’re doing what you’re doing and [suggests] maybe there’s a better idea, I think that can be a really healthy dialogue for everybody to have.” AI-assisted automation offers banks a path to operate more efficiently, improve customer service, and empower employees.

By understanding the differences between RPA and BPA, choosing the right tools, and planning ahead, banks can move toward innovative and adaptable ways of working.

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AI Governance

By Rob Foxx

In the past few years, our world has turned a corner with new trends in technology. Unless you have been living a simpler and happier life than the rest of us you have either had an encounter with or conversation about Artificial Intelligence (AI). There has been a lot of talk and speculation about what that means for the work force. Will it replace traditional workers? Will it bring about the end of all things? Or something in the middle? Knowing the extent of its capabilities is important to its implementation. More importantly, how will we manage, limit, and protect ourselves from AI and its implementation? One of the best ways to answer these questions is with AI Governance.

AI is a wonderful tool. It is capable of completing work in just seconds that would normally take humans hours or days. AI can draft legal documents, policies, emails, and so much more ranging from the extraordinary to the mundane. This is not to say you can remove your work force. You could ask AI to explain how to perform a heart transplant in detail as if it were explaining it to someone with a 3rd grade education, and it will. Does that mean you should perform said heart surgery? Consider if it is something you could not do without AI, it’s something you should not do with AI.

Advanced AI already exists in the workplace and if it is not there it will be shortly. Windows 11 comes with copilot by default, and unless you disable it, copilot will be both accessible and collecting data in the background. Nextgen antivirus suites run on AI. Chat GPT and other AI engines are accessible from a web browser. Keep in mind these technologies are higher risk and lower maturity than your typical application.

How do you know who or what to trust? A good perspective to consider is if you are not buying goods or services then you likely are the goods being purchased. Your vendor provided services will usually specify items in the contract that should be things considered when risk assessing. These contracts should be reviewed with AI and privacy as a consideration. What data is collected? How will it be used? Will it use personally identifiable information? Will it gather critical or sensitive business data? It is even possible it will do this unintentionally? Another consideration is how AI is trained. AI is given data to train and learn from, but raw data may have a bias. AI, like anything else, can be inaccurate or even wildly wrong if it has too much or not enough information. AI can make a guess; this has been referred to as AI hallucinations.

For good management of AI consider restricting use of company approved tools. Always classify and protect your internal data. Know your risk and what you will accept. Define as an organization the proper use of AI tools. Allow for reporting of suspicious activity. Communicate your stances as an organization to your employees.

Foxx is director – infosec and IT audit services for FIPCO, a WBA Gold Associate Member.

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Executive Letter: Be Aware of AI Used by Your Third-Party Vendors

By Rose Oswald Poels

Banks have long had the ability to utilize the services of third-party vendors to assist in daily operations. Such use provides many efficiencies for the bank and often additional services for customers. However, banks must remain diligent in the overall management of a third party, as the use of a third party does not reduce the bank’s responsibility to follow state and federal laws and regulations, or to operate in a safe and sound manner. To assist with the management of third parties, the agencies have issued interagency guidance (recently updated in 2023) and have provided a guide for community banks of third-party risk management.

Oversight of third-party vendors is particularly crucial for any area in which there may be bias for discrimination, including in real estate evaluations or appraisals, for credit underwriting or other loan qualification or approval programs, and for marketing and advertising. An additional layer of risk can arise for the bank when artificial intelligence (AI) is used by a third party in these settings given the concerns by regulators of discrimination within AI logic. The FDIC, OCC, FRB, and CFPB have each been clear that banks are the parties responsible to ensure AI used complies with law.

This week, I have learned that in recent FDIC examinations banks have been scrutinized for not being aware of the use of AI by their third parties. Awareness is critically important to the bank for proper risk management of the third party, especially if AI is used in any area in which there may be bias for discrimination. As the use of AI continues to rise, banks must remain aware of any use of AI by their third parties. Identifying and monitoring how third-parties utilize AI will better assist banks in managing risk of their third-party relationships. Should an examiner determine a bank’s third-party AI tool violated a compliance or other consumer-protection law, the bank will most likely be cited for the violation given that banks are responsible for the actions or inactions of their third parties.

While on the topic of automation, I also wanted to remind banks to review their use of any chatbot on their website to ensure questions submitted via the tool are being answered correctly and timely. Regulator expectation is that any answer provided by the chatbot be accurate and timely. More complex or nuanced customer questions likely need to be answered by bank staff rather than by the chatbot AI.

This article is not intended to deter the use of AI since it can be used in many helpful ways. After recently learning, though, that bankers were unable to answer during examinations whether AI is even being used by their third-party vendors, or unable to explain how it is used by third-party vendors, I thought this reminder would be timely. If you have questions on vendor management issues, you may contact WBA’s Legal Team at wbalegal@wisbank.com.

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AI Reshapes the Workforce

Organizations use AI to recruit, retain talent

By Hannah Flanders

When asked if artificial intelligence (AI) would replace the workforce, experts agreed that most jobs require a human connection. However, some economists assert that automation by platforms like ChatGPT — an AI program with capabilities to understand and generate human-like text — may lead to displacement in some areas.

Although human resources and talent acquisition-related positions continue to be among the fastest growing user role on LinkedIn, according to World Economic Forum’s 2023 ‘Future of Jobs’ report, many agree that AI will only augment the abilities of human professionals, rather than replace them entirely.

“If the staff are not robots, the process shouldn’t be either,” says Renée Peterson, vice president – talent acquisition and development manager at Horicon Bank. “Being a community bank, it is important that we don’t lose the community feel.”

While the World Economic Forum predicts that AI will help create nearly 70 million jobs in the next five years, another 83 million are expected to be eliminated. Human resources professionals and bankers in Wisconsin, however, should not let this staggering number deter them from embracing AI’s potential.

Oliver Buechse, owner of Advancing Digital, explains that incorporating AI into an organization allows employers to empower their team. “AI allows individuals to do. By providing the opportunity for those that are interested to explore AI and its capabilities in their job function, employers will not only be fostering a culture of innovation but also assisting their organization in remaining ahead of a world increasingly reliant on technology.”

Recruiting, Retaining Talent

According to the Society of Human Resource Management (SHRM), it takes, on average, 36 days to fill an open position. During this time, HR professionals are occupied preparing a recruitment plan; sourcing, screening, and selecting candidates; making offers; and onboarding.

While AI cannot completely automate the recruiting process, some experts say that it may help streamline processes.

“AI is great at processing and analyzing massive amounts of data,” highlights Beth Ziesenis, a popular speaker known professionally as ‘Beth Z, Your Nerdy Best Friend.’ “By using generative AI (such as ChatGPT), hiring managers have the ability to analyze what people are looking for and consider feedback from current and former employees to develop a job description that may better communicate the benefits and responsibilities.”

Experts noted that HR professionals may also utilize AI to quickly screen public social media profiles, brainstorm relevant interview questions, and even personalize regret letters.

“In addition to saving time that would otherwise be spent researching or writing, HR teams will greatly benefit from the perspective AI can provide during the recruiting process,” Peterson emphasized.

Despite the large amount of data AI has the ability to process, Horicon Bank’s Senior Vice President – Chief Information Officer Cyrene Wilke states that staff needs to ensure that they are correctly leveraging the tools available to them.

“AI has existed in some capacity for many years, but its abilities only continue to expand,” says Wilke. “While AI at this current moment may allow us to identify top candidates for the position, it is important to recognize that not every qualified candidate makes their information public on LinkedIn or other social media and that sometimes, trained AI bias may still disqualify candidates with differing experience. For this reason, it is important that AI doesn’t entirely replace your staff — just helps enhance their abilities.”

In addition to helping HR professionals recruit for open positions, AI may also be beneficial in assisting and analyzing current employee retention efforts.

During the onboarding process, employers may utilize AI to automate training programs efficiently and inexpensively. As well as tracking employee progress, automating certain aspects of the onboarding process may help provide a more comprehensive training environment for individuals with varying skills or learning styles. Day to day, AI may also prove a powerful tool in assisting employees to understand how their role impacts the organization as a whole or to uncover new career paths within the organization.

“Companies that embrace the transparency AI provides will find a greater sense of belonging among their team members,” notes Buechse.

“With the ability to make predictions based on trends and patterns, AI can provide new perspectives,” says Wilke. “Of course, trained professionals would notice an unengaged employee through details such as excessive and unplanned paid time off. AI, however, would augment and complement the work HR professionals already do to help assist in recognizing trends or insights that are not always apparent at a surface level.”

As such, companies have begun deploying AI to assist in the process of gathering feedback from current and departing employees. Programs such as CultureAmp utilize AI to track employee engagement, measure employee satisfaction and company culture, as well as gather insight into the employee lifecycle. While many organizations already routinely connect with their employees for feedback and provide exit surveys to those leaving the organization, AI provides managers with a systematic and detailed analysis of employee sentiment.

“By taking the time to collect comments from team members, and understand what this feedback signifies, employers will stand apart in a huge way,” emphasizes Wilke. “AI has the potential to not just enhance the efficiency of multiple processes, but also aid in comprehending the employee experience and implementing necessary adaptations.”

Embracing Change

According to research by the Pew Research Center, 45% of Americans are equally concerned and excited about the growing use of AI.

“In order to curb the discomfort some may feel towards AI, it is critical that organizations have a written policy related to its use in human resources, and generally,” says Ziesenis. “Whether your team is waiting for more information or using it all the time — now’s the time to define your bank’s approach and protocol.”

Buechse agreed, “The U.K. has already released information related to its approach to harness the powers of artificial intelligence. In order to remain a step ahead, bankers should familiarize themselves with regulatory frameworks that are beginning to be published around the world. While regulation in the U.S. hasn’t quite caught up yet, that doesn’t mean it isn’t coming.”

As of this writing, bipartisan legislators have introduced a bill aimed at establishing an artificial intelligence commission to review, recommend, and develop frameworks for AI in the U.S. However, for those in the banking industry, it is important to consider the utilization of disclaimers, programs that have been tested for safety and effectiveness, as well as what protections are necessary to ensure privacy prior to launching new systems.

Given the ongoing expansion of AI throughout our lives, experts underscore the need to reframe how technology will amplify the abilities of humans.

“While AI may automate certain aspects of the profession, human resource teams may find that they have a greater ability to focus their energy and efforts on the most impactful aspects of the hiring and retention processes,” says Peterson. “AI will ultimately allow us to spend more time on fine-tuning the outcome.”

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