AI in corporate lending, without exposing your clients’ accounts
Analyzing financial statements, reasoning a risk class, preparing a committee, yes, but never by pasting a client’s figures into an AI without safeguards.
Credit request, financial statements, group chart, table of exposures, valuation of the property offered as security: a lending file holds everything a business owner has entrusted to the bank. Pasted into a consumer AI with no data processing agreement, it leaves your control, and banking secrecy and data protection rules still hold you accountable.
Your analysts and relationship managers already use AI to draft and summarize. The point is not to ban it, but to set what goes into the tool and what never does.
- Evenings spent restating financial statements the night before a committee where nobody else has opened the accounts
- A risk class that is hard to defend, because the reasoning is written down nowhere
- Exposures of linked companies added up by hand, with the risk of missing one
- A client’s accounts pasted into a public AI, outside any control by the bank
See for yourself
A prompt structured in 5 blocks: Instruction · Role and audience · Data · Constraints · Format. An unframed AI invents; the frame stops it.
In the workshop we adapt these prompts to your bank, each with its safeguards: no client data goes into a public AI, and the credit decision stays human.
Client group · linked exposures
The request comes from a sister company or a holding company, and the bank already finances other companies of the same manager. Before setting the overall amount to commit, the analyst has the organisation chart, each company’s financial statements and the table of current exposures. This prompt draws the group, adds up the exposures and flags the cross dependencies before any figures are set.
Repayment capacity · accounts
The credit analyst receives a client company’s last three sets of financial statements, with the credit request, a few days before the committee. This prompt draws from them an analysis a committee member who has not opened the accounts can read: profitability, liquidity, debt, cash flows, adjustments, and a reasoned verdict on repayment capacity, with the questions to put to the client.
Rating · reasoned class
A new client has to be rated, or the annual review of an existing client is due. The analyst has the bank’s rating grid, the financial analysis and the file. This prompt writes the risk class argued criterion by criterion, checks that it fits the figures, shows the effect on terms and pricing, and lists the events that would change the class.
Property security · value retained
A client offers a property as security, and the relationship manager must set the loan to value before presenting the case. This prompt builds the valuation sheet · market value, income value where it applies, lending value retained, rate, independence of the valuation, and says whether the bankers’ association guidelines cover this loan or exclude it.
Credit agreement · clauses
The credit decision is taken and the agreement must protect the bank, with the legal department. The bank’s standard agreement does not fit this transaction · unusual term, several securities, financial commitments from the client. This prompt produces the outline of the agreement and the proposed clauses, and lists the points the legal department must settle before it goes to the client.
30 use cases cover your line of work in the Chaptal catalog, out of 750+ in the corpus · each one states what it produces, what it expects from you, and what it refuses to do.
« Le Collaborateur, augmenté »
You and your credit teams learn to frame AI on your real files, analyses, ratings, agreements, without exposing a client or a confidential figure.
See the training →AI usage audit
A review of your uses, a register and clear rules before a client’s accounts end up in the wrong tool.
See audit & advisory →Do it in a conversation
Jacquard is the Palambur AI assistant. You describe what you need, it knows your line of work and the laws of your country, asks for what is missing and delivers an answer or a ready-to-use document. You choose the model for every question.
Frequently asked questions
Can I paste a client’s financial statements into an AI to analyze them?
Not as they are. Without a data processing agreement, what you paste leaves your control, and banking secrecy binds you. Anonymize first, or use a solution approved by your bank; each sheet in the catalog restates this safeguard.
Can AI decide to grant a loan or set the risk class?
No. It prepares the analysis, writes the class argued criterion by criterion and lists what would change it. The decision, the final rating and the accountability stay with your committee.
Does AI know my bank’s rating grid and guidelines?
No, and that is intended. You supply the grid, the credit policy and the applicable guidelines, AI applies them to the file and flags what it cannot settle.
Can it set the value of a property offered as security?
It builds the valuation sheet and checks that it is consistent, but the appraisal remains an independent expert’s and the value retained is your bank’s.
Do you need a large bank for this to be worthwhile?
No. A regional bank or a small credit team benefits first, because analyses, ratings and agreements rest on few shoulders. The catalog prompts work as they are, with no technical setup.