Call-center speech analytics for Banking
Call-center speech analytics for banking. Banks operate under Central Bank of Azerbaijan supervision and banking-secrecy rules, so customer data cannot go to foreign clouds.
Speech Analytics Built for Azerbaijani Banks
Banks operating under Central Bank of Azerbaijan supervision face a distinctive compliance challenge: extracting actionable intelligence from thousands of daily customer calls without ever routing sensitive data through foreign or shared cloud infrastructure. Allmaz addresses this directly with a single-tenant, private-cloud speech analytics platform that transcribes, diarises, and scores every conversation — 100% of calls, not a statistical sample — while keeping all recordings, transcripts, and derived data entirely within your regulatory boundary. Whether your priority is collections oversight, complaint management, or continuous quality assurance, every interaction becomes a structured, auditable record the moment the call ends.
Why Azerbaijani Banks Choose Allmaz
Complete data residency compliance — the platform is deployed as a single-tenant private cloud within your own infrastructure perimeter, so no call recordings, transcripts, or customer data are ever transmitted to external or foreign cloud services, satisfying banking-secrecy obligations and Central Bank of Azerbaijan requirements by design.
Total call coverage with no sampling gaps — every inbound and outbound conversation is transcribed, diarised, and scored automatically, eliminating the blind spots that traditional random-sampling approaches leave in compliance and quality coverage.
Purpose-built Azerbaijani language accuracy — the speech-to-text engine is designed specifically for Azerbaijani and handles the mixed Azerbaijani and Russian speech common in local bank contact centres, producing reliable transcripts without the manual correction overhead associated with general-purpose engines.
Automated, defensible compliance evidence — every scored call is stored as a structured, searchable audit record containing the transcript, speaker diarisation, sentiment and risk tags, QA scores, and analyst notes, ready to support Central Bank of Azerbaijan examinations or internal compliance reviews at any time.
Early detection of complaints and compliance risk — semantic AI models identify negative sentiment, escalation language, and policy-risk signals across all calls in near real time, allowing supervisors to intervene before incidents escalate into formal disputes or regulatory findings.
Flexible hybrid QA scoring that keeps humans in control — rule-based policy criteria, semantic AI judgment, and human analyst override operate together in a single workflow, so your quality team can accept, adjust, or reverse any automated score and maintain authoritative oversight of the entire QA process.
Platform Capabilities
100% Call Transcription and Diarisation
Every inbound and outbound call is automatically transcribed and speaker-separated. No call is skipped, giving supervisors and compliance officers a complete, searchable record of all customer interactions.
Purpose-Built Azerbaijani Speech-to-Text
The speech engine is designed specifically for Azerbaijani and handles the mixed AZ/RU code-switching common in Azerbaijani bank calls, delivering accurate transcripts without manual correction overhead.
Complaint and Sentiment Detection
Semantic AI models identify complaints, negative sentiment, and escalation patterns as they emerge, allowing team leads to intervene quickly and log incidents before they become formal disputes.
Compliance Risk Scoring
Calls are automatically scored against your regulatory and internal policy rules. Risky interactions are surfaced for review, creating a defensible audit trail for Central Bank of Azerbaijan examinations.
Hybrid QA Scoring Engine
Scoring combines rule-based criteria, semantic AI judgment, and human override in a single workflow. Quality analysts can accept, adjust, or override any automated score, keeping human expertise central to the process.
Single-Tenant Private Cloud
The entire platform runs in a dedicated environment within your infrastructure perimeter. There is no data egress to shared or foreign cloud services, satisfying banking-secrecy rules by design.
How It Works
Frequently Asked Questions
How does the platform satisfy banking-secrecy and data residency requirements?
The platform is deployed as a single-tenant private cloud within your own infrastructure. No call recordings, transcripts, or customer data are transmitted to external or foreign cloud services at any point in the processing pipeline. Because the entire environment is dedicated to your organisation and runs inside your perimeter, data residency compliance is built into the architecture rather than dependent on contractual assurances from a third-party provider.
Does it really analyse every call, or is there still some level of sampling?
The platform analyses 100% of calls without exception. Every conversation — inbound and outbound — is transcribed, diarised, and scored automatically. There is no sampling threshold or volume cap, which means your compliance and quality coverage has no gaps regardless of daily call volumes.
How well does the speech engine handle the way agents and customers actually speak in Azerbaijan?
The speech-to-text model is purpose-built for Azerbaijani and is specifically designed to handle the mixed Azerbaijani and Russian code-switching that is common in Azerbaijani bank contact centres. This focus on local language patterns reduces transcription errors and removes the need for manual correction that typically arises when general-purpose engines encounter code-switched speech.
Can our QA team still apply their own judgment, or does automation override their decisions?
Scoring is hybrid by design and human judgment is never removed from the process. Rule-based policy criteria and semantic AI models produce an initial score for every call, but quality analysts can review, adjust, or fully override any automated result within the same workflow. The platform is built to support and augment your team's expertise, not to replace it.
What evidence does the platform produce for regulatory audits, and how is it accessed?
Every call generates a structured audit record containing the full transcript, speaker diarisation, timestamped sentiment and compliance-risk tags, QA scores, and any analyst notes or score overrides. All records are stored in a searchable archive within your private environment and can be retrieved or exported to support Central Bank of Azerbaijan examinations, internal compliance reviews, or customer dispute resolution at any time.
Ready to Bring Full Visibility to Your Contact Centre?
Talk to the Allmaz team about deploying speech analytics inside your bank's private infrastructure — compliant, complete, and built for the way Azerbaijani banks operate.
Request a demo