AI-powered cybersecurity is now a core member experience issue for credit unions. Here’s how to align security, AI, and cloud to truly protect your members.
Why AI-Driven Cybersecurity Is Now A Member Issue
Ransomware attacks on financial institutions jumped more than 60% over the last two years. For credit unions, every one of those incidents isn’t just an IT problem; it’s a member trust problem.
Here’s the thing about member-centric banking: you can’t claim to put members first if their data, money, and digital identity aren’t protected around the clock. As credit unions roll out AI for fraud detection, smarter lending, and member service automation, the attack surface grows just as fast as the innovation.
That’s where leaders like Robert Johnston, CEO of Adlumin and former military cyber operator, are pushing the conversation forward. His core message to credit unions is blunt: you won’t stay relevant if your security posture doesn’t keep pace with your digital strategy.
This article takes the themes from his CUInsight Network conversation and connects them directly to the broader AI for Credit Unions: Member-Centric Banking story: how to use AI, data science, and cloud-based platforms to protect members while still innovating rapidly.
From Compliance Checkbox To Member Experience Strategy
The fastest way to fall behind as a credit union is to treat cybersecurity as a regulatory checkbox instead of a core member experience capability.
Robert’s team at Adlumin sits in a unique spot: they’re plugged into credit union CORE systems, regulatory expectations, and real-world incident data. What they see is consistent:
- Attack volume and sophistication keep climbing
- Many credit unions still rely on legacy tools and manual log reviews
- Board conversations focus on compliance more than risk outcomes
Why compliance alone isn’t enough
Compliance frameworks are necessary, but they’re lagging indicators. By the time an exam finding or report surfaces an issue, the attackers have already moved on.
A member-centric cybersecurity approach shifts the questions from:
- “Are we compliant with X regulation?”
to:
- “Can a member safely sign in, move money, and share data at 2:00 a.m. while our systems auto-detect and contain suspicious behavior?”
That’s the mindset change AI makes possible.
The data science layer credit unions are missing
Modern security operations rely on data science, not just log collection. Platforms like Adlumin’s don’t simply store logs from firewalls, endpoints, and CORE systems; they analyze relationships and behavior over time.
For a credit union, that means:
- Learning what “normal” looks like for staff, vendors, and members
- Scoring the risk of logins, transactions, or admin actions in real time
- Correlating subtle anomalies that would never be obvious to a human analyst
Most credit unions already have the raw data sitting in their systems. The gap is the analytical brain on top of it.
How AI-Based Security Supports Member-Centric Banking
AI in credit unions is often framed around fraud detection, loan decisioning, or chatbots. Cybersecurity AI belongs in the same strategic conversation, because it’s doing something very similar: reading signals in real time and making smart decisions fast.
1. Threat detection that actually keeps up
AI- and ML-driven security platforms can ingest millions of events per day from:
- Online and mobile banking
- Core processing systems
- Payment rails
- VPN, identity, and access platforms
- Endpoint devices and servers
Instead of human analysts sifting through dashboards, the system:
- Flags unusual access patterns (e.g., a loan officer logging in from two countries within an hour)
- Spots lateral movement inside your network
- Builds risk scores that prioritize which alerts matter now
A good rule of thumb: if your team can’t explain how you’d detect a compromised staff account within minutes, your security is still too manual.
2. Stronger fraud defenses without member friction
Members hate friction. But they hate seeing money disappear even more.
AI-based cybersecurity and fraud tools can work together to:
- Step up authentication only for high-risk actions or behaviors
- Block or delay suspicious transfers while triggering targeted outreach
- Combine device risk, behavioral biometrics, and transaction patterns
Done right, you get less blanket friction (like forcing every member through MFA every time) and more targeted friction (only when risk spikes). That’s how you stay member-centric and secure at the same time.
3. Protecting AI projects with the same intelligence
As you roll out AI for:
- Automated member service
- Personalized financial wellness insights
- AI-assisted underwriting
…those models and data pipelines become high-value targets.
An attacker who tampers with training data or model output can quietly degrade decision quality or abuse access to sensitive information. AI-powered cybersecurity can:
- Monitor access to AI models and data stores
- Detect unusual usage of APIs and service accounts
- Flag exfiltration attempts from data lakes and analytics platforms
AI doesn’t just power your member-facing tools; it should also guard the infrastructure behind them.
Cloud-Based Security: Why The Next Wave Favors Credit Unions
Robert Johnston argues the next wave of innovation for credit unions is cloud-based data and security. He’s right, and not just for performance or cost reasons.
Cloud-native security platforms are better suited to modern threats because they’re built to:
- Scale analytics as your log volume explodes
- Update detection models frequently across all customers
- Feed anonymized data into shared threat intelligence
Why cloud makes sense for credit unions right now
For most small and mid-sized credit unions, trying to build an internal 24/7 security operations center (SOC) is unrealistic. You’d need:
- Security engineers
- Threat hunters
- Incident responders
- Compliance analysts
…all competing with large banks and tech companies for the same scarce talent.
Cloud-based managed detection and response (MDR) or SIEM-as-a-service flips that model. You get:
- A shared platform maintained by security specialists
- Continuous tuning of AI/ML detection models
- Automated reporting that feeds directly into your compliance needs
It’s one of the most practical ways for credit unions to get enterprise-grade cybersecurity without enterprise budgets.
Addressing the “cloud is less secure” myth
Some boards still worry that cloud equals less security. In reality, the risk comes from how cloud is configured, not from the cloud itself.
The upside when done right:
- Stronger identity and access controls
- Better encryption and key management
- Faster rollout of patches and security updates
- Built-in redundancy and disaster recovery options
Member-centric banking means choosing the infrastructure that best protects their data, not just the one you’ve always used.
Practical Cybersecurity Best Practices For CU Leaders
Concepts are great, but leadership needs a practical playbook. Here’s what I’ve seen work when credit union executives take cybersecurity seriously as part of their AI and digital strategy.
1. Treat cybersecurity as a member promise, not an IT project
Frame security and AI investments around member outcomes:
- “Members can trust that every interaction is monitored and protected.”
- “We can detect and contain a breach before members feel the impact.”
Update board and leadership dashboards so they track:
- Mean time to detect (MTTD) and mean time to respond (MTTR)
- Number of critical incidents contained automatically
- Coverage of log sources feeding your AI-driven security tools
2. Integrate CORE and security data
Robert talked about improving compliance for CORE systems with integrated security data. That’s non-negotiable.
Concrete steps:
- Ensure your SIEM/MDR platform ingests logs from your CORE, digital banking, card systems, and major third-party vendors
- Correlate authentication events, transaction data, and admin activity
- Use that integrated view to power both security analytics and compliance reporting
When regulators ask, you’ll have evidence, not just policies.
3. Build an incident response muscle
AI will flag more issues. Your organization needs to know what to do next.
Create and rehearse:
- A clear escalation path (who owns what in a breach)
- Communication templates for members, partners, and regulators
- Playbooks for common scenarios: credential stuffing, ransomware, insider misuse, vendor compromise
Include member experience in these plans. How will you:
- Keep online and mobile services available or offer alternatives?
- Support affected members with proactive outreach, monitoring, and education?
4. Align cybersecurity and AI projects from day one
When your team pitches a new AI-powered tool—fraud detection, loan automation, or chatbots—pair it with a security workstream:
- Threat modeling for the new system
- Access and identity design
- Logging and observability requirements
- Data retention and privacy policies
This keeps you out of the trap where a fantastic AI member experience goes live on top of a weak security foundation.
Preparing For Regulatory Change Without Slowing Innovation
Robert also highlighted a reality credit unions know too well: regulators are watching cybersecurity and AI very closely. New rules are coming faster, and guidance around cloud, data, and third-party risk keeps evolving.
The good news: if you build AI-powered cybersecurity and strong data governance in from the start, regulation becomes less of a scramble and more of a translation exercise.
Practical moves:
- Centralize logs and evidence into platforms that can generate exam-ready reports
- Map your AI and cybersecurity controls back to relevant guidance
- Keep vendor due diligence updated for critical cloud and AI partners
Regulatory pressure isn’t going away. But credit unions that treat it as a forcing function to modernize security will end up more competitive, not just more compliant.
Where Member-Centric Security Goes Next
The direction is clear: AI for credit unions can’t just be about smarter marketing and faster lending. It has to extend all the way down into how you defend your members and your institution.
The path forward is straightforward:
- Stop treating cybersecurity as a separate, back-office concern
- Connect your CORE, digital channels, and security telemetry into one analytical brain
- Use cloud-based, AI-driven platforms to get 24/7 protection without 24/7 internal staffing
- Tie every security decision back to a member promise: safety, continuity, and trust
Credit unions that do this won’t just avoid breaches; they’ll turn trust into a strategic advantage in an increasingly digital market.
The question for your leadership team is simple: as you invest in AI for member experience, are you investing just as seriously in the AI that protects it?