Can Polat’s professional background reflects a long-term technical evolution shaped by risk, complex systems, and international regulatory environments. His experience spans traditional banking, global financial institutions, and emerging digital-asset platforms, where he has focused on the practical implementation and operation of cybersecurity systems in highly regulated contexts.
Across more than two decades, his work has combined governance awareness with deep, hands-on technical execution, contributing to security approaches that are transferable across banking, fintech, and insurance environments rather than tied to a single organisation.
Can you briefly describe your technical focus in cybersecurity?
My technical expertise centres on designing, architecting, and configuring enterprise cybersecurity platforms for regulated banking, fintech, and digital‑asset environments. I work directly with the core mechanics of production systems, including SIEM log ingestion like WinCollect agents, database inspection through S‑TAP agents, credentialed vulnerability scanning, endpoint protection with integrated DLP modules, privileged access vaults with automated credential rotation, enterprise email gateways (DKIM, SPF, DMARC), and data governance platforms for data classification and lifecycle control.
These components are integrated through consistent configuration, shared telemetry, and cross‑platform correlation to operate as a single security system capable of detecting credential abuse, privilege misuse, and data exfiltration in regulated environments.
How did your early career influence this hands‑on technical approach?
My early work within financial IT risk and audit teams exposed recurring technical weaknesses in security implementations, such as incomplete log collection that left critical events invisible, expired certificates that weakened authentication controls, and poorly tuned monitoring that generated false assurance.
This experience pushed me to focus on the internal behaviour of security platforms: how authentication integrations such as LDAP enforce access control, how vulnerability visibility degrades during infrastructure change, and how encrypted backups and recovery mechanisms must be configured to remain reliable during cyber incidents. From this, I developed repeatable technical implementation patterns to address configuration drift and degraded visibility, applied across multiple regulated financial environments.
My ongoing leadership in senior executive capacities focuses on pioneering these in regulated banking and digital-asset platforms, ensuring performance under stress and contributing to standards like BRSA and CMB for cyber resilience.
How do you approach SIEM architecture and configuration in financial environments such as Q-radar?
SIEM platforms in banking and fintech often underperform due to insufficient attention to ingestion quality and parsing accuracy. My work in this area focuses on identifying all systems generating security‑relevant telemetry, correctly configuring log sources, parsers, timestamps, and retention policies, and eliminating generic or unknown event classifications through parser correction and custom mapping.
Once ingestion stability is achieved, I tune detection logic by disabling high‑noise default rules and creating correlation logic aligned with real financial‑sector attack behaviour such as credential abuse, privilege escalation, insider misuse, and transaction manipulation. Thresholds and time windows are adjusted based on observed baseline behaviour. A strict requirement is that all alerts remain traceable to raw events for technical validation and forensic investigation.
What is your technical approach to Privileged Access Management platforms like CyberArk?
Privileged Access Management platforms frequently fail when deployed with shallow configuration or without integration. My work focuses on structuring vaults and safes to separate personal, service, emergency, and system accounts; enabling automated credential rotation with verification; enforcing session recording and command‑level visibility; and integrating authentication with enterprise directories and multi‑factor authentication.
Resilience is treated as a technical requirement through replicated vaults, tested failover scenarios, and offline custody mechanisms for recovery credentials. Privileged access telemetry is forwarded into central monitoring platforms to enable correlation with endpoint, network, and database activity.
How do you configure Database Activity Monitoring systems such as Guardium‑class platforms?
Database Activity Monitoring platforms require careful tuning to be effective. My work includes deploying and tuning agents across heterogeneous databases such as Oracle, MSSQL, and PostgreSQL; validating performance impact under peak transaction loads; differentiating application traffic from batch processing and interactive DBA activity; and defining granular rules for sensitive SQL activity across DDL, DML, and DCL operations—such as schema changes (CREATE/ALTER/DROP), data manipulation (INSERT/UPDATE/DELETE), and privilege/role modifications (GRANT/REVOKE), including monitoring of bulk extract patterns.
DAM telemetry is integrated into central monitoring platforms to correlate database behaviour with privileged access, authentication events, and endpoint activity. Baselining is applied per database/user/application context to identify anomalous access patterns during system changes or emergency interventions, enhancing forensic visibility and traceability.
How do you handle vulnerability management beyond default scanning like Tenable?
Default vulnerability scanning produces volume rather than insight. I focus on enabling credentialed scans, separating infrastructure and application scanning, defining asset‑specific profiles, and scheduling scans to balance coverage with operational impact.
Dashboards are configured to highlight vulnerability age, recurrence, and remediation failures, enabling technical teams to prioritise effectively rather than react to raw counts.
What is your approach to endpoint security and data protection configuration such as Trellix?
Endpoint security platforms degrade over time due to configuration drift and inconsistent agent management. My work includes standardising agent versions, validating update mechanisms, verifying policy inheritance, and identifying unmanaged endpoints.
At the same time, I configure integrated Data Loss Prevention capabilities at endpoint and network level, tuning content inspection rules to real data flows, ensuring forensic‑quality evidence capture, and eliminating common bypass paths. Endpoint antivirus, EDR, and DLP telemetry is consolidated in a central monitoring platform to analyse malware activity, endpoint behaviour, and data exfiltration attempts together.
How do you configure and tune email security platforms such as SMG‑class gateways?
Email security gateways are often under-tuned despite being one of the most critical attack surfaces in regulated financial environments. My approach starts with hardening email authentication and trust boundaries by correctly configuring and enforcing SPF, DKIM, and DMARC policies, including alignment checks, policy enforcement modes (quarantine/reject), and continuous monitoring of authentication failures to prevent domain spoofing and brand impersonation. Detailed email telemetry is forwarded into central monitoring platforms to correlate message delivery, user interaction, and subsequent endpoint or credential activity.
On top of authentication controls, I tune phishing and impersonation detection to identify executive spoofing, lookalike domains, and supplier fraud scenarios. This includes differentiating legitimate business communication patterns from anomalous sender behaviour and applying stricter inspection rules to high-risk message types.
How do you configure and operate data governance platforms in regulated financial environments such as Insight Information Governance?
I configure data governance platforms as active data-visibility systems, not reporting tools. This involves discovering and classifying sensitive data across file systems and unstructured repositories using content patterns, metadata, and access context.
I tune access-behaviour analytics to baseline normal data usage and detect anomalies such as excessive access, off-hours activity, or unexpected permission changes. Permission analysis is used to identify over-privileged access and orphaned rights, supporting least-privilege enforcement.
Information governance telemetry is integrated into central monitoring platforms and correlated with endpoint, database, and privileged access activity, enabling data-centric incidents to be analysed end-to-end rather than in isolation.
How do you integrate multiple cybersecurity platforms into a single operational system?
Integration is configuration‑driven. Telemetry from PAM, DAM, endpoint protection, email security, vulnerability management, and data protection platforms is normalised and forwarded into SIEM with consistent field mapping. Integrations are validated using controlled scenarios and continuously monitored for silent failures caused by authentication, certificate, or network changes.
What technical guidance would you give to banking and fintech organisations?
Organisations should prioritise architectural rigor over tool proliferation. Vendor defaults must be treated as placeholders rather than production‑ready configurations. Parsing rules, correlation logic, and policies should be reviewed, disabled where necessary, and tuned to reflect real transaction patterns and authentication models.
Telemetry quality must be validated early, including timestamp accuracy, field mapping, and event completeness. Configuration drift should be treated as a zero‑tolerance technical risk, requiring continuous validation. Detection logic must be tested using controlled scenarios such as simulated credential misuse or data exfiltration attempts.
Security platforms should be operated as continuously engineered systems, with configuration, tuning, integration testing, and validation embedded into normal operational processes.
How do you see cybersecurity evolving in regulated financial services?
Cybersecurity in regulated financial services is evolving toward data-driven, continuously validated security systems. AI will primarily be used to analyse large volumes of security telemetry—identity, endpoint, database, and data-access events—to detect behavioural anomalies that static rules miss. Zero-trust enforcement will become identity- and context-based, requiring tight integration between authentication, endpoint posture, and data-layer visibility. At the same time, security platforms will adopt immutable, cloud-native configurations and automated validation to prevent configuration drift and ensure consistent behaviour across environments.
