Training for the team
AI training in banking and leasing
AI Syntalith training for banking, leasing and intermediary teams covers document handling and correspondence regarding completing the application. The price starts from €1,150 net per day. The proposed program includes reading the requirements from the approved list, describing the deficiencies and passing the matter to the next person. Creditworthiness assessments, financial decisions and AML activities remain outside this scope.
- net per day of closed training for the team
- from €1,150
- people in one training group
- up to 15
- after this time, we measure the effect on the same tasks
- 30 days
- conversation with an engineer and a written plan within 2 business days
- €0
or call+48 888 78 48 78WhatsAppMon–Fri 9:00–17:00 CET
We belong to the OpenAI and Anthropic partner programmes and learn through their official courses. What this means ↓
Statistics
How much does AI training for banking and leasing cost and when does it pay off?
Short answer
AI training for banking and leasing costs from €1,150 net per day. In our Polish cost example, a PLN 4,900 training fee pays back in 2.6 months: 10 people save an hour a week, and after the licenses they have PLN 1,905 left per month. The team practices working with applications, client documents and correspondence, with confidentiality rules. We measure task time before the training and after 30 days.
10%
According to ESET and DAGMA (2026), 10% of employees admit to pasting sensitive company data into open AI models.
Source: ESET and DAGMA, Cyberportrait of Polish business (2026) ↗
70,9%
According to Eurostat (2025), 70.9% of companies in the EU that have considered AI but are not using it cited a lack of knowledge within the team as the reason.
27%
According to ESET and DAGMA (2026), only 27% of companies have a written policy on the use of AI.
Source: ESET and DAGMA, Cyberportrait of Polish business (2026) ↗
Figures checked: 22 October 2026
Scope step by step
How to explain to the client what is missing?
The first module starts with a list of materials required by the company. The participant compares it with a fictional set of documents and prepares a working note. For every discrepancy, they must indicate the basis: what was expected and what was actually provided. AI can help organize the text; the meaning of requirements is explained by the person responsible for the process.
In the example task, the client sends the correct type of document, but for a different period. The model describes the entire position as complete. The participant checks the period, corrects the note, and writes one message covering the remaining gaps. The instructor evaluates whether the recipient knows what to send and whether the text does not suggest that completing the documents means the grant has been approved.
The client's response changes the list of questions
The second module includes further correspondence. The participant compares the response with the previous request and updates the case. They also practice concise communication with their colleague: which materials have arrived, what needs to be checked, and what has already been asked.
Another participant takes over the case based on this note. If they had to ask again for the provided document, we go back to the part that was skipped during the update. After the feedback, the author corrects the material. In a self-contained task, the client explains that the request concerns a different entity than the attached document. The participant should point out the discrepancy for review, without independently confirming identity or authority.
Team and working conditions
We select people who compile documents, client supervisors, and process coordinators. Their knowledge of requirements is needed regardless of experience with AI. Beginners work on short cases; more advanced participants may get a longer exchange of messages with partial responses.
Exercises are conducted on fictional data or previously approved materials for this tool. The institution sets access rules. The program is a proposal for work on reading and editing skills; it is not an audit of supervisory requirements or evidence of implementation in a bank.
If the issue is transferring attachments between systems, an evaluation of the current workflow will be helpful. The difference is described in the guide on automating the compilation of documents for financing. System integration is not part of this training.
Cost and program setup
Format online or at the client's location, number of groups, and potential post-practice evaluation are included in the offer. Participant access is discussed before the sessions; Syntalith does not sell licenses. Describe the stage where conclusions return after completion, and we will determine the scope of team training and necessary materials. No client documentation needs to be sent for the first meeting.
How much does the training cost and when does it pay off
The training starts at €1,150 net per day. We calculate the return on one process, without assumptions about the entire company.
- Time saved
- 43.3 hours/month
- Value of time
- 2,877 PLN
- ChatGPT Business Licenses
- 250 USD (972 PLN)
- Remaining after licenses
- 1,905 PLN/month
Return on training for 4,900 PLN
2.6 months
10 people × 1 hour weekly × 4.33 weeks = 43.3 hours. We cautiously assume one hour of time saved per person weekly and verify it by measuring the time of tasks before and after 30 days. An hour of work at 66.45 PLN is the average wage according to GUS from September 2026, including employer costs. Licenses: ChatGPT Business Standard 25 USD per place monthly, kurs NBP 3.8889 PLN. If the team already has licenses, the return is faster.
According to a study published in Science (2023), the time for writing tasks with ChatGPT has decreased by 40%. Therefore, the scenario adopts a cautious weekly hour and verifies it through measurement.
„I already use AI.”
Your people too. Just no rules.
From our conversations with companies
5 na 10 employees paste sensitive data into private AI accounts: contracts, invoices, customer data.
In ESET survey (2026)
1 na 10 admits this in the survey.
Customer data pasted into a private AI account without an data processing agreement is a violation of the GDPR.
Don't worry, we won't tell anyone :)
What do we see in companies that "already use"
- Only ChatGPT or Claude accounts, without plugins, skills, integrations and MCP servers with company tools.
- Company programs are not connected to AI. People still click through systems and Excel, and enter chat data manually.
- Lack of company standards: everyone writes instructions in their own way, no one shares what works.
- No rules for personal data, GDPR and company secrets.
- No limits and no visibility: no one knows who uses AI, how much and for what.
62% Polish employees use AI at work · 27% companies have written rules for working with AI.
Source: ESET and DAGMA, Cyberportrait of Polish business 2026 (March 2026, 1,026 people) ↗
ChatGPT or Claude space review
Accounts, permissions, rules for working with data and 5 tasks set for the team. 1 day.
€450 net
Training on your team's tasks, from €1,150 net per day.See range and price →
Scope and price
From €1,150 net per day
We determine the program, number of groups and time to discuss the work before the quote.
1:1 course participants
People we've trained one-on-one.

Kuba Koziej
CEO and co-founder, MoreGrowth
View the original training review on LinkedIn ↗„We started with my own AI agent. During the training that followed, I learned to build new applications myself. Today I am bringing this way of working with AI into my business. Working with Syntalith gave me exactly the skills and tools I needed.”
„A large stream of documents passes my desk every week. I now review, draft and prepare them with Claude in a fraction of the time, and research that used to eat an afternoon takes minutes. It is wired into the services I already work in, so the documents reach me instead of me hunting for them.”
Hlib UtkinPublic administration„I came in using coding agents ad hoc and left orchestrating them: loops, an agent kanban, a full development cycle that ships. What stayed with me is running context and cost on purpose, and building my own harnesses instead of waiting for a tool to ship one. It changed how I work day to day.”
Ivan ChepurinSenior Software Engineer, Immutable„I run a design studio, not an engineering team, and I still left with something working. We built an agent loop that pulls in leads and keeps an eye on the competition, and I put my own site together with Claude. It was hands-on, on my real work, not a talk about AI.”
Oleksandr UsykCo-founder & Art director, jakotako.design
Let's talk
Just write, call or choose a date.
We work fast because we hate corporate cotton wool. We don't have salespeople or managers to keep an eye on managers. You talk immediately to engineers who then build your system. We respect each other's time and yours too.
We will accept 3 more companies by the end of the year.
- Write
- contact@syntalith.ai
- Call
- +48 888 78 48 78
- write on WhatsApp
Mon–Fri 9:00–17:00 CET