When the defense won: The bank that reduced incidents by 35% in 18 months (and how you did it)
It was 2024. The bank was where they are many: with alerts on all sides, incidents being discovered too late, and a team of security overwhelmed.
Then they decided to do something different.
The initial problem (2024)
The situation
A bank major European noticed a problem that each time it was more acute:
- Hundreds of daily alerts without context
- 15-minute average between detection and response (too slow)
- Multiple systems with no correlation between them
- Computer security exhausted triando noise constantly
- Incidents were discovered by third parties, not by their own systems
FACT (according to UC Today):
A financial institution major implemented a framework of common security based on:
- NIST Cybersecurity Framework
- ISO 27001
- Secure Controls Framework (SCF)
But the framework was only the beginning.
The transformation (2024-2026)
Step 1: Standardization without chaos
The first thing they did was to consolidate standards.
Before: Each department had their own interpretation of ‘security’.
- Risk management used their own criteria
- Infrastructure had their own policies
- Applications continued their own practices
After: A unique framework that everyone understands.
ANALYSIS: This seems simple, but it was transformational. When all speak the same language of security, things move faster.
Step 2: real-time Monitoring
Implemented monitoring real-time of:
- Access to critical systems
- Changes in settings
- Patterns of behavior of users
- Network connections anomalous
- Activity on sensitive database
The key: Not collecting more data. Correlated best to the one they already had.
Step 3: automated Response
Here was where they picked up the speed.
Before: An analyst, a human had to:
- See the alert
- To investigate manually
- Escalizar if it was critical
- To make that decision
- Execute response
15 minutes. Sometimes hours.
After: automated Rules that:
- Detected anomaly
- Correlate with context
- Assess severity automatically
- Run basic response (blocking, isolation)
- Alert for human validation
3-5 minutes. Sometimes seconds.
FACTS: The majority of incidents small are resolved automatically. Critics require human validation, but the triage is done.
Step 4: safety Culture
The most important thing: they Changed the mentality.
Before: ‘Security is the responsibility of the security team’
After: ‘Safety is everyone’s responsibility, but with tools that help us’
Trained employees in:
- What is abnormal behavior
- How to report suspicions
- How to not sabotage the security accidentally
The results (2024-2026)
Metric 1: confirmed Incidents
Before: 45 confirmed incidents per year (to be detected)
After: 29 confirmed incidents by year
Reduction: 35%
But what is interesting is not that there are fewer attacks. Is that:
- Those that occur are detected faster
- The damage is more limited
- The answer is most effective
Metric 2: response Time
Before: 15-30 minutes on average
After: 3-5 minutes on average
Improvement: 5-10x faster
Metric 3: False positive
Before: 80% of alerts were noise
After: 15% of alerts are noise
Improvement: Signal-to-noise ratio was 1:5 to 6:1
That means the security team now sees the real signal, not just chaos.
Metric 4: Cost of incidents
Before: an Average of $500k per incident (late detection, damage extended)
After: an Average of $50k per incident (early detection, damage limited)
Reduction: 90% in cost per incident
How they did it: The keys
Key 1: it was Not just technology
The framework and the tools were critical, but the real was:
- Leadership that gave priority to security
- Investing in the right solutions
- Training of staff
- Patience during the transition period (18 months is not fast, but it was necessary)
Key 2: Measurement from the start
Measured everything before you deploy.
Then measured continuously during.
So they knew what was working and what’s not.
Key 3: Automation with human validation
Don’t have critical decisions.
Yes computerized triage and basic response.
Left to humans, where humans are better: in critical judgment.
Key 4: internal Collaboration
Linked computers normally did not speak:
- Security + DevOps
- Security + Infrastructure
- Security + Applications
- Security + Compliance
When teams collaborate, security issues are discovered earlier.
How to 24Cevent power this even more
If this bank had 24Cevent implemented:
That already would be 10x better
The framework + monitoring + automation that they implemented are exactly what 24Cevent ago.
But 24Cevent would add:
1. Correlation multi-layer preset
- You don’t have to create all the rules yourself
- The best practices are already built-in
- Known patterns of attacks are already modeled
2. Predictive analysis
- ‘Based on current activity, this is likely to climb to X in y minutes’
- Taking actions preemptivas before they become critical
3. Integration with intelligence global threat
- ‘This pattern of attack is the same that we saw in Bank X 3 months ago’
- Reuse defense of others in your favor
4. Response to level of industry
- If 100 banks use 24Cevent, when one detects a threat, they all benefit
- Defense collaborative without sharing sensitive data
The lesson of this bank
A bank that:
- It is not ‘sexy’ with AI and automation extreme
- You do not have laboratory research
- It is simply a financial institution by measuring and improving
…managed to reduce incidents by 35% in 18 months.
Because they did the right thing:
- Standardized
- Monitored
- Computerized where it made sense
- Remained human in the loop
- Measured continuously
That is what wins against attacks. It is not magic. Is discipline.
And with 24Cevent, that discipline is multiplied.
SOURCES CHECKED: