Disclosures verified after the fact
Identification, consent, the mandatory lines of a loan or card conversation — checked on a sample, weeks later, by the quality team. The gap between a missed line and anyone knowing is a quarter.
Solutions · Banks
Bank contact center software that hears every call: every disclosure checked, every reason counted, every repeat contact seen.
Labs, clinic networks and insurers run their patient lines on Ender Turing because a scheduling call is where demand, satisfaction and revenue meet — and only a sample of them was ever heard. Every call, chat and email is transcribed, categorized and scored the moment it ends; personal data is masked; the summary lands in your CRM or appointment system. In any language.
The problem
A bank's contact center is audited on the 3% of calls somebody heard.
One scorecard per country, none comparable
Each subsidiary keeps its own rubric in a spreadsheet, in its own language. Leadership cannot compare a branch in one country with a branch in another, and agents hear feedback 11 days late.
The reasons behind the volume are guessed
Card blocks, payment questions, loan status, complaints about a fee — the ACD counts them as calls; the reasons, the repeat contacts and the promises to pay live inside recordings nobody can search.
What the contact center gets
Every function below is documented — the link on each card is the guide.
Contact-center templates are installed on sign-up; personal-data masking, executive boards and engineer-set connectors come with the Business plan; private cloud or on-premise with Enterprise.
Every required line, checked on every call
Compliance rules score whether identification, consent, the product's mandatory disclosures and the closing lines were said — on 100% of calls, chats and emails, with a script-adherence score per conversation and the exact moment linked. An automation escalates the misses to compliance the same day.
One scorecard across every subsidiary and language
AutoQA scores the same scorecard in every language your customers speak, shows its accuracy against your reviewers per point, and puts every branch on one board — so a quality number in one country means the same in another.
Why customers call, and which calls come back
Topics categorize each conversation — card blocked, payment not received, loan status, fee complaint — and your repeat-contact rules link a call to the customer's previous one; the reasons behind a volume spike and the products behind repeat contacts are a chart, not an assumption.
Sales, retention and collections conversations, measured
The offer that was made and the one that was accepted, the retention objection, the promise to pay — funnels follow each conversation to its outcome per agent, branch and campaign, and the calls that converted become the playlist the rest of the team learns from.
Personal data masked, access scoped, your cloud
Account numbers, names and identifiers masked in transcripts per language; roles decide who opens which conversations; SOC 2 Type II and GDPR-compliant handling on every plan; private cloud (AWS, GCP, Azure) or on-premise deployment with your own speech engines on Enterprise.
Ask the contact center a question
"Why did calls about blocked cards rise last week, and which branches drove it?" EnderGPT answers from the conversations, with the calls cited; a scheduled chat delivers the same answer every Monday; executive boards and scheduled reports put quality next to volume and satisfaction.
Numbers we've helped customers move
What changes when every conversation is analyzed.
- 100%Calls automatically scored (vs. 3–5% manual baseline)Quality coverage
- +19%Average lift in customer satisfactionCSAT
- −15%Reduction in average handle timeAHT
- 68hQA hours saved per specialist per monthProductivity
Averages across our contact-center deployments — each customer's own numbers are in the case studies. Case studies →
Customer result
Read the OTP Bank case study → OTP Bank: from a 3% sample to every conversation — customer satisfaction from 6.8 to 8.0.
Central and Eastern Europe's largest banking group rebuilt its quality program on Ender Turing across its subsidiaries and languages; the case study describes the rollout, the scorecard and the compliance loop.
In the product
What the head of the contact center sees.
Product screenshots — dashboards and analyses from the platform, not illustrations.
The same conversations, three more ways
From the compliance check to the whole operation.
Quality management
AutoQA on every conversation with the accuracy measured against your reviewers; disputes, review queues, coaching from the scores.
Contact center operations
Why customers call, which calls come back, where the time goes — the operations view of the same conversations.
Real-time agent assist
The matching script step, disclosure or reminder on the agent's screen while the customer is still talking — a separate product, rolled out with our engineers.
Banking FAQ
What banks ask before choosing contact center software.
What does Ender Turing do for a bank's contact center?
It reads every call, chat and email the moment it ends and scores it against your scorecard: identification, consent, the mandatory disclosures of the product, the closing lines — on 100% of conversations instead of a sample. It categorizes the reason (card blocked, payment, loan status, complaint), links repeat contacts, estimates satisfaction from the dialogue, masks personal data in the transcript and escalates the exceptions to compliance the same day. One scorecard works across every subsidiary and language, so quality is comparable across countries.
How does it check mandatory disclosures and consent?
Compliance rules define the lines a conversation must contain — a consent question, an APR or fee disclosure, a cooling-off statement, an identification step — with the wording tolerance you set; every conversation gets a script-adherence score and the missed lines are linked to the exact moment. An automation sends the misses to a review list or to compliance by email, immediately or as a daily digest.
We have subsidiaries in several countries. Does one setup cover them?
Yes. Speech recognition runs in any language, the same scorecard and topics apply across countries, and roles scope each team to its own conversations while leadership sees every branch on one executive board. A language we do not run yet is added on request or connected through your own speech-recognition engine.
What results have banks seen?
OTP Bank moved from sampling calls to analyzing every conversation with Ender Turing and improved customer satisfaction from 6.8 to 8.0 on a 10-point scale; the case study describes the rollout across its subsidiaries. OTP Bank, Dila Med Labs and Fozzy Group report doing marketing analysis and NPS 20 times faster and 50 times cheaper with Ender Turing.
How is customer data protected?
Personal data — names, account and card numbers, identifiers — is masked in transcripts, configured per language, on the Business plan; roles and permissions decide who can open which conversations; data handling is SOC 2 Type II and GDPR-compliant on every plan; Enterprise runs in your private cloud (AWS, GCP, Azure) or on-premise with your own speech engines, services and monitoring. The current controls, regions, retention periods and sub-processors are on the data security page.
Does it work with our telephony and CRM?
Documented apps for Genesys Cloud, Five9, Zendesk and other platforms; connectors to recording systems and a CRM connector set up by our engineers on the Business plan; the REST API, SFTP and upload for everything else. Results — the score, the topics, the summary — flow back to your CRM by webhook and API. Nothing is written into your telephony platform.
Can it measure sales, retention and collections performance?
Funnels follow each conversation to its outcome — offer accepted, product opened, customer retained, promise to pay, callback — per agent, branch and campaign; scorecards check the required steps of the script; the calls that converted become playlists for coaching. The figures are yours to publish; we never publish them for you.
How is this different from Verint, NICE or CallMiner?
Compare on the same things: coverage (Ender Turing scores 100% of conversations, with the accuracy of its scorecards measured against your own reviewers), time to numbers (a workspace in minutes with contact-center templates; implementation engineers and first auto-scored production calls within 28 days on the Business plan), who runs it (a contact-center manager with EnderGPT and scheduled reports, not a program team), languages (any language, others added on request), and price (published per agent, with a free plan that does not expire).
Which languages does it support?
Any language. Production speech recognition today covers English, Spanish, Portuguese, French, German, Polish, Ukrainian, Arabic, Chinese, Japanese and more; a language we do not run yet is added on request or connected through your own speech-recognition engine.
What does it cost, and how do we start?
Free for up to 5 agents, 200 calls per agent a month, with no expiry. Team is $39 per agent per month with no limits, your own scorecards and compliance rules, the accuracy loop and the REST API. Business is $79 per agent with personal-data masking, executive boards, scheduled reports, connectors set up by our engineers, the CRM connector and a 28-day onboarding. Enterprise adds private cloud or on-premise deployment, custom integrations and additional languages. Book a demo with your own recordings, or start free and connect one queue yourself.
Security, hosting regions, sub-processors and response times are documented on the Data Security page; SOC 2 Type II examination completed.
Free for up to 5 agents
Hear every customer call — starting with the disclosures nobody checked.
Book a demo with your own recordings, or start free and connect one queue yourself: the first scored calls come back the same day.