One of Europe’s largest cooperative banks—serving over a million customers through an extensive network of branches manages a complex infrastructure of 7,000+ systems and 300 critical applications. In a fast-paced financial ecosystem, even a brief downtime can disrupt millions of transactions, making IT resilience essential.
Read the full case study here.
The Challenge: Breaking through siloed IT operations
In retail and commercial banking—especially when offering insurance services—uptime is mission-critical. But this bank’s fragmented IT landscape left teams stuck in reactive mode:
- Multiple siloed “IT tribes” operating without cross-functional visibility
- Frequent Stripe billing system disruptions causing revenue impact
- SEPA payment platform running 4,000+ monthly batch jobs, with 250+ failures/month
- Manual SEPA recovery taking 30+ minutes per incident
- No predictive capability—monitoring tools flagged issues but couldn’t resolve them
- IT fatigue from repetitive manual interventions and constant firefighting
This model was unsustainable for an institution responsible for millions of daily financial transactions. The bank needed automation-led resilience and predictive intelligence.
The Solution: Automation-driven IT operations with ignio
The bank deployed Digitate’s ignioTM AIOps and AI Workload Management (WLM) to bring intelligence, context, and automation into IT operations. The platform delivered:
Key capabilities:
- Proactive root-cause identification and self-healing actions for Stripe failures
- Predictive detection of SEPA batch job failures end-to-end
- Integration with Control-M for holistic batch job visibility
- AI/ML-driven prioritization and autonomous resolution of incidents
- Significant reduction in manual triaging and recovery times
The Outcome: Resilient, predictive, and automated banking operations
Metric | Outcome |
Service Requests | 5,700+ resolved end-to-end; 90% faster delivery |
Incident Management | 10,000+ hours saved annually |
Automation Index | Increased to 90% |
Manual Effort Savings | 60,000+ hours saved/year |
SEPA Batch Jobs | 250+ failures predicted; MTTR cut from 30 minutes to seconds |
Revenue Protection | $1.6M+ in potential loss prevented |
Business value delivered
- Faster recovery: MTTR reduced from 30 minutes to seconds for SEPA failures
- Proactive operations: Predictive alerts prevented SLA breaches and downtime
- Employee productivity: 50+ automated service request use cases freed up IT staff
- Customer trust: Timely financial transactions restored brand confidence
- Cross-functional collaboration: Synergy achieved across 11+ work areas
Key Takeaways
This transformation wasn’t just about automation—it was about building financial resilience through predictive, intelligent IT operations. With ignio, the bank now:
- Turns noisy alerts into actionable insights
- Prevents major disruptions before they occur
- Delivers uninterrupted, high-quality customer service
Ready to explore automation-led IT resilience? Schedule a demo with us today.
Read the full case study here.
FAQs: AIOps and AI Workload Management in Banking
What is AIOps in banking?
AIOps applies AI and automation to banking IT operations, enabling proactive incident prevention, faster resolution, and improved service availability.
Why is predictive batch job monitoring important for banks?
It prevents delays in financial transactions, avoids SLA breaches, and maintains customer trust by addressing failures before they escalate.
How does ignio™ AI Workload Management improve efficiency?
It uses AI to predict failures, automate resolutions, and optimize job scheduling, drastically reducing manual intervention.
Can AIOps prevent revenue loss?
Yes. By reducing downtime and transaction failures, AIOps safeguards critical revenue streams.
What’s the difference between reactive and proactive IT operations?
Reactive operations address issues after they occur, while proactive operations predict and resolve them before they impact the business.
