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bash scripting
Here’s a comprehensive list of real-time Bash scripting use cases in the banking domain, based on how banks and financial institutions operate:
1. Infrastructure & Server Management
Log rotation & archival for compliance (e.g., RBI, PCI-DSS requirements)
Automated backup scripts for databases (Oracle, PostgreSQL, MySQL)
Server health checks (CPU, memory, disk, process monitoring)
Patch deployment automation for Linux servers
Scheduled cleanup of temporary or old files to prevent storage issues
2. Security & Compliance Automation
User access review scripts (list and remove inactive accounts)
Automated SFTP/SSH file transfer for secure interbank data exchange
Checksum/hash verification to detect data tampering in transaction files
Automated encryption/decryption of files (GPG/OpenSSL) before transfer
Log parsing to detect unauthorized login attempts or suspicious activities
TLS/SSL certificate expiry checks with email/SMS alerts
3. Data Processing & ETL Tasks
Automated extraction of transaction data from source systems
Batch processing of large CSV/XML/JSON files received from payment gateways
File format conversion (e.g., SWIFT MT → CSV for internal systems)
Splitting/merging large files for downstream processing
Automated data validation to detect missing or corrupt records
Archiving processed transaction files for audit purposes
4. Monitoring & Alerting
ATM/branch server uptime checks with instant alerts
Batch job monitoring for failed payments or settlements
API health checks for core banking & payment services
Automated threshold alerts (e.g., low disk space before transaction peak hours)
Log scanning for fraud detection patterns (e.g., abnormal transaction volume)
5. Application Deployment & Maintenance
Zero-downtime deployment scripts for banking apps
Configuration file updates across multiple servers
Restart automation for crashed services (core banking, payment processors)
Version rollbacks if new deployments cause issues
6. Reporting & Reconciliation
Daily transaction summary generation and emailing to stakeholders
Reconciliation scripts to match internal transaction logs with external systems (e.g., NPCI, SWIFT, VISA/Mastercard)
Automated report formatting for regulators (RBI, SEBI)
Scheduled report uploads to secure portals
7. Disaster Recovery & Failover
Automated DB failover initiation between primary & DR sites
Data sync scripts between production & DR environments
System status verification post-DR switch
✅ Why Bash is heavily used in banking:
Works directly on Unix/Linux systems where most core banking apps run
Simple, lightweight, and fast for repetitive automation
Can integrate with Python, SQL, and monitoring tools
If you want, I can map each of these banking Bash use cases to actual command/script examples so you have a ready-to-use reference. That would make it easier for interviews and real work.
python automation
Got it — here’s the Python equivalent list for real-time use cases in the banking domain, covering the same operational areas as I did for Bash, but now focusing on where Python shines in finance & banking automation.
1. Infrastructure & Server Management
Automated server health checks (CPU, RAM, disk space, process uptime) via
psutilCloud infrastructure automation using
boto3(AWS) orazure-mgmt/google-cloudPatch scheduling & orchestration with
fabricorparamikoAutomated log rotation & archiving with compression
Centralized server inventory management using API calls to CMDB systems
2. Security & Compliance Automation
Automated user access audits from LDAP/AD via
ldap3Automated file transfers over SFTP using
paramikoData encryption/decryption using
cryptographyorpyOpenSSLAutomated checksum/hash validation with
hashlibfor transaction filesSecurity event log parsing to detect anomalies (via regex & log parsing libs)
TLS/SSL certificate monitoring using
ssl+ alert emails
3. Data Processing & ETL Tasks
Automated ingestion of transaction data from APIs, CSV, Excel, or JSON
Data transformation & cleaning using
pandasFile format conversion (e.g., SWIFT MT → CSV) using parsing libraries
Splitting & merging bulk transaction files based on size or rules
Automated data quality validation with Pandas profiling
Archival to cloud storage (AWS S3, Azure Blob, GCP Storage) via SDKs
4. Monitoring & Alerting
Real-time API health checks with
requestsand alerting via Slack/Teams APIATM/branch device uptime monitoring via SNMP (
pysnmp)Batch job monitoring with automatic retries
Predictive anomaly detection on transaction data using
scikit-learnLog monitoring for fraud patterns in near real-time with regex & Kafka streaming
5. Application Deployment & Maintenance
Automated deployment pipelines with
fabric,invoke, or integrating with Jenkins/GitLab APIRemote configuration updates via SSH automation
Service health check & restart scripts
Blue-green deployment orchestration
Rollback automation using versioned backups
6. Reporting & Reconciliation
Automated report generation (PDF, Excel) using
pandas,xlsxwriter, orreportlabTransaction reconciliation by comparing internal vs. external datasets
Regulatory report automation (e.g., RBI, SEBI formats)
Scheduled report uploads via API or SFTP
Interactive dashboards using
dashorstreamlit
7. Disaster Recovery & Failover
Automated DR switch-over scripts via cloud SDKs
Database replication monitoring (PostgreSQL, MySQL, Oracle)
Data synchronization scripts between regions/sites
Post-failover system verification with automated functional tests
✅ Why Python is heavily used in banking:
Strong data processing capabilities (Pandas, NumPy)
API-friendly for integrating with banking systems
Excellent automation & scripting ability with cross-platform support
Works with cloud & on-prem systems equally well
Easy integration with machine learning for fraud detection & risk scoring
If you want, I can now map each of these Python banking use cases to an actual working script snippet so you have ready code for interviews or projects — just like I did for Bash.
Do you want me to prepare that Python banking automation code pack? That would make this list instantly practical.
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