Complaint and correspondence handling automation for financial institutions

Built to your own complaint categories and your own procedures, running on your infrastructure. There’s no product to license here. We scope the automation against your process, prove it on your historical mail, then hand over a system your team owns.

Scope a PoC on your inbox
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Credit Agricole – AI Service Assistant, in production

95%
classification accuracy
62%
of incoming tickets automated
50%
faster processing

Four things break when correspondence volume outgrows the team

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Shared inboxes get triaged by hand

Your most expensive minutes go to sorting mail instead of closing cases.
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Keyword rules break on the first typo

And once their author leaves, nobody dares touch the rule set.
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RPA bots move mail without reading it

A complaint raising three issues gets filed under one. The other two return as escalations.
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The awkward pile has no owner

Handwritten letters, scans of scans, a phone recording running past the ten-minute mark, an email with five attachments. It waits for whoever handles the difficult stuff, which is where regulatory deadlines quietly expire.

Your categories, your procedures, your servers

We start from the process you already run and the rules you already follow. Three things then change about how correspondence moves through it.

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    • Everything arriving gets read. Whatever form it takes. Each case is classified against your taxonomy, prioritized, and checked for the risks that matter in your industry: regulatory escalation, likely legal action, a customer about to leave.
    • Replies are drafted from your own documents. Terms, procedures, promo rules. Every answer cites the passage it came from, and a complaint raising several issues gets checked for whether the draft answered all of them.
    • You set the autonomy level per category. Full auto-reply where the process is simple and the stakes are low. A draft waiting for sign-off where it isn’t. A task list for the handler where the work happens offline anyway.
    • All of it runs on-premise or in your cloud tenant. We pick the model that fits your data rules and swap it if those rules change; where nothing may leave the country, we run an open-source or Polish-language model behind your firewall.

Five things happen between arrival and answer

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01. Intake

Vision models read scans and handwriting. Speech-to-text handles call recordings. Every attachment links to its case by ID, so one customer complaint stays one record regardless of channel.
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02. Classification and risk

Your categories and subcategories, plus a priority, an emotion read, and a complexity score. Cases flagged for regulatory or legal risk jump the queue while they’re still cheap to fix.
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03. Drafting

Answers are grounded in your documents and cite their source. For multi-issue complaints, the system reports which issues the draft covers and which it missed.
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04. Verification

Generated output passes deterministic checks before a customer sees it. Cases below your confidence threshold go to a human queue rather than getting an automatic answer. We learned this on real bank data: a model’s confidence and a model’s correctness are two separate measurements.
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05. Routing and scale

Automatic routing by category and load, containerized for tens of thousands of messages a day. Peaks get absorbed with compute. Every step is logged, so an auditor can replay why a case ended up where it did.
Each stage earns the next one

Every engagement starts small on purpose. Each stage has its own go/no-go decision, backed by numbers from the previous one.

Discovery [1-2 weeks]

A map of your correspondence types and volumes, with the processes worth automating ranked by value.

PoC [5-10 days]

A KPI report on your historical data: accuracy per category, automation rate, processing time. No integrations, so nothing touches production.

Pilot / MVP [6-8 weeks]

A working system on one department’s live traffic, connected to your mail infrastructure and first business systems.

Production rollout [phased]

More mailboxes and channels, automation rates raised category by category, handed over to your team to operate.

Managed / Continuous improvement

Monitoring, model and prompt tuning, category updates as your processes change.

Testimonial

What clients tell us, on the record

By automating certain customer interactions, bank employees are provided with a prepared “semi-product”, which enables them to dedicate more time to personalizing and empathizing with customer communication, and thus taking even better care of their needs.

Katarzyna Tomczyk – Czykier
Director of the Innovation and Digitization Division – Retail Banking
Let’s talk about your project
In 5–10 days you’ll know your automation rate, your classification accuracy, and your time-to-first-reply, all measured on your own historical messages. We go through your correspondence types and your data constraints, then scope the PoC together.
Book the scoping call

let’s get in touch

Contact our consultant

Book 1-on-1 consultation 

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Grzegorz Motriuk

Head of Sales | Application Development

Our consultant is at your disposal from 9 AM to 5 PM CET working days from Monday to Friday for any additional questions.

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Frequently asked questions

  • What happens when the model isn’t sure?

    It doesn’t guess. Confidence thresholds route uncertain cases to a human queue, and auto-reply only fires above the threshold you set per category. You control where the line sits.

  • Where does our data go?

    Nowhere. The system runs on your infrastructure or in your cloud tenant. If policy says data can’t leave the country or touch a US API, we run an open-source or Polish-language model behind your firewall.

  • Will it work with our legacy stack?

    The PoC deliberately needs no integrations, so you can validate accuracy before any IT project starts. From MVP onward we connect over standard interfaces: mail infrastructure, CRM, ITSM via API.

  • Which languages does it handle?

    Polish and English are proven in production. Other languages depend on the model you pick; we’ll test yours in the PoC.

  • Are we locked in?

    The underlying model is swappable, and your team edits categories and reply guidelines through configuration, without a developer. If we part ways, the taxonomy and knowledge base are yours.

  • When does it pay back?

    Typically 6–12 months, but that depends on your volume and the share of repeatable cases. The PoC report gives you the inputs to calculate it for your own operation instead of trusting a vendor’s slide.