SPONSORED CONTENT PRESENTED BY JACK HENRY & ASSOCIATES, INC.
Your bank has built trust by focusing on relationships, efficiency, and empowering customers. Today, you may be wondering, “Can AI support our mission and values?”
Indeed, AI can be a tool that takes this mission to the next level.
Let’s explore four key areas to help you harness the power of AI, so it becomes the driving force that not only supports your goals but helps you deliver on your mission and values with even greater impact.
66% of banks have discussed allocating budget or resources to AI.[i] To stand out, you’ll need a clear, well-defined vision for AI.
Define Your Business Goals and Vision
Before diving into AI adoption, you need to understand the fundamentals (Generative AI vs. Large Language Models vs. Machine Learning and so on). And – perhaps most importantly – you need to understand why you’re pursuing it.
After all, AI isn’t the end goal. It’s a means to achieve your mission. For example, if your organization’s mission focuses on financial empowerment, AI can analyze spending patterns and offer personalized advice to help accountholders avoid fees, save more effectively, and find the right solutions for their financial needs. Start identifying how AI can support your business objectives by asking yourself:
- Are you looking to improve efficiency, freeing up time for your staff to engage more deeply with customers?
- Do you want to grow deposits or better manage risk?
- Are you aiming to offer more personalized financial solutions, helping customers achieve financial health? AI isn’t just about technology. It impacts people, processes, and change management across organizations.
57% of financial institutions struggle with AI skill gaps.[ii]
Consider the business impacts of AI adoption:
- People and skills: AI can automate certain tasks, but it also requires your team to adapt to new roles and responsibilities. Identify how AI will impact job functions and develop strategies for reskilling employees.
- Technology: Ensure that your technology infrastructure is capable of supporting AI, in terms of both data storage and processing power. A robust IT framework is key to scaling AI successfully.
- Change management: As with any major transformation, AI adoption will require thoughtful change management. Ensure that your bank’s leadership is aligned on how AI will support the organization’s broader vision. Bottom line: AI should align with your purpose, not just be a shiny new tool.
Develop an Ethical Framework
AI introduces new opportunities, but it also comes with ethical considerations. Ensuring your AI systems are used responsibly is essential for maintaining your customers’ trust. By embedding ethics into your AI strategy from the start, you strengthen your reputation and ensure long-term success. Start by adopting a framework that emphasizes fairness, inclusivity, and accountability.
Google emphasizes responsible AI development, stating that AI must align with human values and be designed to address risks.[iii]
Your ethical framework should cover:
- Bias management: AI models can unintentionally perpetuate biases. Build or select systems that are inclusive and regularly monitored for fairness.
- Transparency and accountability: Ensure that decisions made by AI are understandable, and that there’s clear human oversight (“human in the loop,” or HITL).
- Privacy and data security: Protecting customer data is paramount. AI should enhance security, not introduce vulnerabilities.
Understand and Mitigate Risks
While AI offers tremendous opportunities, it also introduces risks that need to be carefully managed to protect your organization’s reputation, financial stability, and customer trust. A robust AI risk management framework is essential to address these challenges. Start by implementing a formal AI risk management framework that identifies, assesses, and mitigates risks early on.
This framework should incorporate continuous monitoring of AI systems to detect and address emerging risks such as:
- Algorithmic bias: AI systems can unintentionally reinforce societal biases if not carefully monitored.
- Data privacy and security concerns: Your customers entrust you with sensitive information, and AI must be used in ways that uphold the highest standards of privacy.
- Regulatory compliance: Your AI use must align with local and international laws such as The General Data Protection Regulation (GDPR) or The California Consumer Privacy Act (CCPA).
IBM emphasizes that AI risk management is about minimizing potential negative impacts while maximizing the benefits of AI technologies.[iv]
By incorporating formal tools, practices, and principles, you can systematically monitor and manage the risks associated with AI, ensuring your systems remain secure, transparent, and effective over time.
48% of financial institutions struggle with a lack of clarity about AI’s business impacts.[v]
Ensure Compliance and Accountability
Establishing strong governance and accountability structures is crucial to ensure your AI systems remain transparent, legally compliant, and ethically sound.
Here’s how you can ensure compliance and accountability:
- Governance structures: Develop clear governance structures that outline the roles and responsibilities for AI development, deployment, and oversight. This includes identifying key decision makers who are accountable for the ethical use and performance of AI systems.
- Transparency: Build trust by documenting all AI-driven decisions and making data sources, algorithms, and model biases transparent to your stakeholders. Transparency ensures that your organization can explain how AI systems arrive at conclusions and highlights the ethical safeguards in place.
- Legal compliance: Ensure adherence to GDPR, The Revised Payment Services Directive (PSD2), and other applicable regulations. Your AI policies should be designed to meet both local and international legal standards governing data protection, consumer rights, and financial services.
- Internal usage standards: Create internal policies that limit the use of personally identifiable information (PII), intellectual property (IP), and sensitive code in AI systems. These standards ensure that data handling is compliant with both internal policies and external regulations.
Establishing these clear governance frameworks will not only help your bank meet compliance standards but also strengthen accountability and trust within your organization and with customers.
55% of organizations have not yet implemented an AI governance framework, but the majority are in the process of developing one.[vi]
What’s Next?
To ensure AI truly enhances both your operational efficiency and your mission to support customer financial health, the first step after your policies are created is to lay a strong foundation:
- Find use cases: Identify one area where AI can have a tangible impact – like automating routine tasks or improving fraud detection. Piloting a project will give you the insights you need to scale AI across your organization.
- Assess and develop talent: AI is not about replacing the human element in banking. It’s a tool your staff can use to enhance the customer experience, so start by developing procedures for training staff on effectively using AI.
- Prepare your data and technology: Identify any gaps in your technology that could limit performance. Regularly evaluate your data for consistency, reliability, and accuracy by conducting data hygiene exercises to correct inconsistencies.
- Identify alliances and key providers: Work with providers who specialize in AI solutions for banks. Make sure they align with your values and ethical standards to ensure their solutions support your mission of community-focused, responsible banking.
You can further expand your knowledge and plan your AI approach with these expert insights.
[i] 2024 Technology Survey, Bank Director, accessed October 17, 2024
[ii] AI Governance Frameworks for Responsible AI, Gartner: Peer Community, accessed October 18, 2024.
[iii] Why We Focus on AI (and to What End), Google AI, accessed October 18, 2024
[iv] What Is AI Risk Management? IBM, accessed October 18, 2024
