Financial Institutions, Take Note. AI Will Soon Transform Your Cybersecurity, Compliance, and Customer Service
Recent statistics leave little doubt that AI has significant upside potential for community banks. Recent numbers from Accenture Consulting show that 68 percent of community banks are exploring or implementing AI solutions to enhance customer experience and streamline operations. The same study showed that AI-driven customer experience can lead to 20 percent higher customer satisfaction and 30 percent potential cost reductions.
Banks are exploring AI for a whole host of use cases—from parsing incoming resumes, to monitoring investments, to helping customers perform more complex self-service tasks on their customer portals. Of course, AI additions to existing cloud tools like Microsoft’s 365 are also a big part of that equation, speeding up every kind of internal workflow.
AI presents a bright, shining promise to improve business efficiency and create exciting new ways to serve banking customers. What does that look like for the average bank? Let’s explore.
How Banks Are Making Use of AI
As of 2023, banks with under $100 billion in assets are still lagging behind their larger peer organizations regarding AI adoption. However, most banks have tried at least three use cases. According to The State of AI in Financial Services 2023, here are some of the top use cases reported by Nvidia.
- Natural language processing and large language models for chatbots
- Recommender systems/following best action
- Portfolio optimization
- Fraud detection in transactions/payments
- Algorithmic trading
- Conversational AI
- Marketing optimization for content creation
- Creating synthetic data for model creation/optimization
- Document management
- Compliance
And so much more.
The Upside Potential for AI Is Big for Banks
The power of AI is making its way into the core process software banks use, cloud productivity software like Microsoft 365’s Copilot, and innovative new AI-powered stand-alone tools. Soon, AI will be so ingrained in the tools we use that it will be impossible to separate it from the work we do every day.
As the possibilities unfold, it begs another question: are banks seeing the benefit? The early answer appears to be yes. Here’s the latest information from Nvidia on the business impacts banking customers are already seeing.
AI’s advanced, intelligent algorithms have the potential to do many things better at banks if adequately managed. We’re already seeing many of our client banks that are now enjoying:
- More accurate and thorough security and fraud alerts
- Fraud alerts incorporating several different kinds of security mechanisms at once
- Data-driven insights for nearly any business need
- Cost savings by cutting time and labor out of processes and making more informed decisions
- 24/7 availability of basic bank customer service functions through portals and chatbots
- Efficient issue resolution for basic tasks
- AI-generated assistance for essential onboarding and account questions
What does that look like for the average bank? Let’s review how AI plays out at some of the industry’s leading, larger banks.
Examples of How Banks Are Using AI in 2024
The larger, enterprise-level banks have the resources to promote AI in banking. As prices for AI tools come down and AI becomes mainstream, expect to see similar possibilities in community banks soon.
The future of AI in banking is here, and it’s easy to jump on board. Before you do, ensure you fully understand what could go wrong with your chosen tools.
Before You Start with AI, Consider the Risks to Your Bank
It’s important to remember that few laws govern AI in banking. Instead, AI is supposed to conform to all the existing banking and data handling laws. Specifically, these laws include the GDPR (General Data Protection Regulation) in the European Union and the CCPA (California Consumer Privacy Act) in the US, both of which govern how banks collect, store, and process customer data.
To use AI tools safely, you’ll need to ensure there are no loopholes in the algorithm that can get you into situations like this:
- Protected data that’s being collected by the tool and stored outside your controls
- Algorithm bias that unfairly excludes job or loan applicants
- Loss of customer trust from data breaches associated with AI
- Operational disruptions
- Improper resource allocation due to poor or misaligned business intelligence
- Mitigation strategies that are interrupted by automated responses
- Regulatory penalties associated with poor/improper usage of AI tools
So, with all this in mind, how can you prepare your infrastructure and business process for the AI revolution ahead? Proceed carefully. The key is thorough preparation and governance.
How Banks Should Prepare for AI Implementation
Because of the extra scrutiny around AI and the data privacy concern, banks should elevate the risk level to at least one before any implementation. For instance, evaluating a product like a chatbot without customer data would typically have a low-risk rating. However, because auditors and regulators scrutinize AI tools more closely, you will want to treat chatbot testing as a medium risk.
This should apply to all your AI implementations. Although testing, introducing, and managing those tools requires more work, the rewards can be tremendous for your organization. If you’re interested in pursuing AI tools at your financial institutions, let’s walk through what you should do step by step.
Start by Researching the Business Opportunities AI Can Bring to Your Bank
It’s easy to start with an intriguing new AI tool and begin vetting from there. We recommend starting one step back from there. Instead, ask, “Why do we need the power of AI to perform a specific task?” or “What will be the net benefit to our institution?” Here’s how that process would look in practice.
Step One: Task the Members of the Bank’s IT Committee to Identify Key AI Opportunities
This includes looking at any area that could benefit from automation. For instance, your HR department might need AI help sorting and responding to job applicants. Customer service may want a powerful AI assistant added to the customer portal. Marketing may want to use AI to monitor business intelligence/ad effectiveness or use generative AI to create marketing materials. Be proactive by asking for your organization’s AI wish lists now.
Step Two: Create or Update Your Policy for Acceptable Use of AI for Your Bank
If your bank hasn’t developed an acceptable use policy for AI yet, it’s time to do so. Once you’ve established AI use policies and procedures, you’ll need to update them every time new AI capabilities are added. As you write the policy, include language that outlines the AI board’s involvement in future approvals or policy creation around AI Tools.
Step Three: Request the IT Committee Propose a Business Case
Ask your group to put their recommendations into writing for senior management, creating a clear case including use cases, budget, and likely productivity gains for the proposed technology.
Step Four: Hand Over Your Findings to Senior Management to Evaluate and Verify the Case for AI
While this adds an extra layer of approval, it’s also an excellent opportunity to help educate senior bank leadership on how AI impacts the bank.
Step Five: Once You’ve Identified What You Want to Do with AI, Determine How You Want To Do It
With your business cases identified, it’s time to move to the next step, including:
- Evaluate the AI tools available to solve your specific business needs
- Once a vendor is selected, you must perform thorough vendor due diligence and include team members in compliance. Assess what data will be gathered, who has access to that data, what other ways the data will be used, and where the data will reside.
- Conduct a risk assessment of this tool before starting any work and have it validated and approved by senior management before deployment.
Step Six: If Your Tool Passes the Test, It’s Time to Put Together a Deployment Plan
Once you’re straightforward about implementing new AI capabilities, assemble key team members from Compliance (ISO), IT, and senior management to verify that your expectations are still aligned with the results of your due diligence. Together, build a thorough testing and validation period to ensure the tool works correctly. Then, deploy the new capability widely.
Step Seven: Create a Regular, Repeatable Validation Protocol
Because AI tools are rapidly changing, vendors will likely change their data usage and privacy policies. These need to be reviewed regularly based on your vendor risk rating. It’s also important to regularly assess the effectiveness of your tools and ensure they are still meeting regulatory compliance standards for data usage and privacy.
Put in the Work Now and Reap the Rewards of AI for Banks
While this may seem like a lot of work on the front end, AI can bring extraordinary new levels of efficiency, customization, and business intelligence to your financial institution. We’d love to help you transition smoothly to this new tech future.
We’ve helped hundreds of banks create IT infrastructure they can grow on. We can help you take this AI journey, too. Our cyber security experts are on hand to help you with audits, policy development, and procedures on a consulting basis. You can also hire Integris to handle all your IT MSP duties. Either way, we’d love to talk. Contact us at integrisit.com.
