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Author: Malte

KYC involves more than collecting identity documents.

Deutsche Bank has deployed an agentic AI solution for source-of-wealth work in its private banking centres in Singapore and Hong Kong. It researches approved sources, prepares documentation and identifies gaps. People review the assessment.

A Swiss leasing company faces different questions, but much the same problem of fragmented evidence. An application, company register, identity checks and information on beneficial owners must agree. Someone needs to spot conflicting names, missing records and facts that require clarification.

An assistant could prepare that comparison for the operations team. It should not convert an unresolved match into an approval. In a difficult case, the useful result is a clear explanation of what remains uncertain and who must review it.

The aim is a more complete, auditable file, with less time spent moving between systems.

Which recurring question delays onboarding most often in your organisation?

Source: https://wealth.db.com/en/about-us/news/2026/deutsche-bank-private-bank-launches-agentic-ai-kyc-processes.html

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The right benchmark for Switzerland as a business location

A location can look strong in a regional comparison and still come under pressure.
In “Climbing higher”, McKinsey and Swiss AmCham note that around 80 per cent of the CEOs interviewed compare Switzerland with global locations. Those interviewed mainly represent the perspective of internationally active companies.
I consider this finding relevant for Swiss SMEs as well. The right benchmark follows from the customer’s decision. What quality can they obtain elsewhere? How quickly is it delivered? How reliably are problems solved?
Anyone who answers these questions only by looking at familiar competitors may be making the judgement too easy.
The same applies to investment. A new asset should be measured by whether it improves our position in the competition we actually face. Progress compared with our own machine fleet is not yet a sufficient justification.
The strength of a business location grows out of many such decisions. And out of the courage to choose a comparison from which we can still learn something.

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Switzerland Needs to Trust Freedom Again

Switzerland is successful because it gives its citizens and businesses comparatively broad freedom. Not because the state directs particularly much.

Perhaps we should remind ourselves of that more often.

Ludwig von Mises, Friedrich August von Hayek and Frédéric Bastiat were separated by more than a century of economic history. Yet one conviction united them: society works better in the long run when people are free to make as many decisions as possible themselves and when the state focuses on setting reliable rules.

That may sound theoretical.

For Switzerland, it is highly practical.

Freedom starts with the recognition that no one possesses enough knowledge to centrally steer a complex economy.

Hayek described this problem as early as 1945. Economically relevant knowledge is not concentrated in one place. It is dispersed across millions of businesses, households and individual decisions. Prices coordinate this knowledge without any authority having to possess it in full.

An entrepreneur knows more about his customers than a public agency.

A craftsman knows more about his capacity than a ministry.

An investor knows more about his risk than a commission.

This does not mean that markets always produce perfect outcomes.

It means something else: government decision-makers do not possess perfect knowledge either.

Regulation should therefore not be judged by whether its intention is good. What matters is what consequences it actually produces.

This is where Bastiat becomes relevant.

His famous principle of “what is seen and what is not seen” may be more relevant today than ever. Political measures usually make their immediate benefits highly visible. Subsidies create visible winners. Support programmes finance visible projects. Regulation addresses visible risks.

What is less visible are the opportunity costs.

Which company was never founded?

Which investment never took place?

Which employee was never hired?

Which innovation was abandoned because permits, documentation requirements or regulatory risks became too burdensome?

Bastiat’s point was not that public spending is inherently useless. His point was that its costs must also be taken into account.

This is precisely where the debate becomes concrete for Switzerland.

The OECD continues to describe Switzerland as an exceptionally successful, open and market-oriented economy. At the same time, it notes that the administrative burden on companies is above the OECD average and that reducing bureaucracy could strengthen productivity and economic dynamism. State ownership also remains significant in parts of the Swiss economy.

SECO itself sees room for improvement. Monitoring published in 2026 showed that the number of regulatory obligations imposed on companies increased regularly between 2005 and 2025. At the same time, instruments have been introduced to reduce administrative burdens.

This is not a crisis.

But it is a warning signal.

Mises would probably have asked a simple question: do we automatically respond to every new problem with a new intervention?

His criticism of interventionism was not a rejection of the state as such. Mises also regarded rules protecting property and peaceful cooperation as necessary. His warning concerned a different dynamic: interventions alter incentives, decisions and prices. When new problems emerge as a result, the response can easily become yet another intervention.

That is why freedom requires institutional discipline.

Not every inequality requires a subsidy.

Not every economic risk requires a new rule.

Not every desired development requires government support.

And not every social problem has an economic policy solution.

The alternative, however, is not “state or no state”. That distinction is too simplistic.

A free economic order requires an effective rule of law, functioning courts, property rights, competition, accountability and rules against fraud and abuse of power.

Externalities, information failures or natural monopolies may also justify state intervention.

The decisive question is therefore not whether the state is allowed to act.

It is: where is state action genuinely necessary, and where are people better placed to decide for themselves?

For Switzerland, this question is particularly important.

Our prosperity is built on entrepreneurship, international trade, innovation, competition, federalism and a remarkably strong tradition of individual responsibility.

These institutions are not historical decoration.

They are an economic competitive advantage.

Perhaps Switzerland therefore does not need a new programme for every new problem.

Perhaps it needs the courage, more often, not to create one.

Fewer rules where existing rules are sufficient.

More competition where structures are protected.

Faster permits.

Simpler procedures.

More responsibility for those who also bear the consequences of their decisions.

That would not be a revolution.

Quite the opposite.

It would be distinctly Swiss.

And Mises, Hayek and Bastiat would probably recognise a shared idea in it:

Freedom is not the absence of order. Freedom is an order that leaves individuals as much room as possible to decide for themselves.

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Who instructed this payment: a person or an agent?

Mastercard is building Agent Connect to link merchants, platforms and authorised AI agents. The Bundesbank has examined how agents might prepare or initiate payments under a mandate. These are developments in infrastructure, rather than a ready-made payment process for every financial firm.

For a leasing company, the first useful question comes before execution. Does the supplier on the invoice match the approved contract? Has the asset been accepted? Has the beneficiary account changed? Are all conditions for disbursement documented?

An agent could assemble those answers and draw attention to exceptions. I would keep a firm boundary around the payment itself: software prepares; authorised people review and release. Any move beyond that deserves a separate decision with precise limits and a means of stopping the agent.

The more an agent can do, the more clearly its identity, mandate and permissions need to be defined.

Could your organisation show who authorised every automated step in a payment today?

Source: https://www.mastercard.com/global/en/news-and-trends/press/2026/september/mastercard-gives-merchants-a-simpler-way-to-build–connect-and-s.html
https://publikationen.bundesbank.de/content/1007712

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Financing belongs on the CEO agenda

In most SMEs, financing is discussed after the order has already been signed.
The sequence is surprisingly common: need identified, specifications prepared, offers compared, supplier selected, investment approved. Only then is the finance department or fiduciary adviser asked how it will all be paid for. Financing appears as settlement rather than design.
By then, the most important design option has already been lost. Cash-flow effect, balance-sheet effect, term, residual-value risk and risk allocation all depend on the financing structure, which can then only adapt to a fixed decision rather than help shape it.
This has consequences beyond the individual case. Anyone who considers financing only at the end will almost automatically use the familiar structure. In most companies, that structure has never been reviewed. It simply evolved over time: this is how the father did it, this is what the main bank knows, and this is how it appears in the last financial statements.
In an environment where banks assess applications more selectively, attach greater weight to collateral and take longer to decide, this sequence is risky. [Evidence: current survey of SME access to credit] A commercially sound investment may fail for lack of financing even though a different structure would have worked. It also regularly causes companies to consume their entire credit line for an asset that could have been financed differently, leaving no room for the next project.
The alternative is unspectacular but effective: review financing options in parallel with procurement. What happens to our liquidity over the next 24 months? What does this investment mean for our credit capacity on the next project? Which structure fits the asset’s usage cycle? Which risks do we want to carry ourselves?
That requires a few weeks’ lead time and changes the decision surprisingly often, rarely in amount but frequently in structure. It also moves the topic to where it belongs: the executive agenda, not the settlement process.
A food producer considers leasing, a bank loan and self-financing in parallel before ordering a new packaging line.
A question for executive teams: at what point in your investment process does financing enter the discussion, and who introduces it?

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The transparency register makes KYC easier to test

When financing a machine, a leasing company should know who controls the business behind it.

On 1 October 2026, Switzerland’s Legal Entities Transparency Act (LETA) and the revised Anti-Money Laundering Act come into force. Many Swiss limited companies and private limited companies will have to identify, verify and report their beneficial owners to a new federal register. The register, maintained by the Federal Office of Justice, will not be public.

For finance leasing, this changes the information available to the lender. The duty to identify customers and controlling persons already exists under Swiss anti-money laundering rules. The Swiss Leasing Association’s self-regulatory organisation expressly addresses it. A register entry can provide another source for a review; it cannot take the place of the leasing company’s own inquiries or accountability.

Consider an SME held through two holding companies. Its application identifies one individual as the controlling person; the register lists another. Neither an automatic rejection nor a blind copy of the register entry resolves the issue. The ownership chain must be clarified, the difference documented and, where the legal conditions are met, reported to the register.

Companies within the Act’s scope acquire their own reporting and updating duties. For leasing providers, the operational task is to bring existing KYC files, register data and customer questions into one traceable process.

The register offers a better point of comparison. The quality of the assessment still depends on the individual case.

Could you explain the control chain behind a commercial leasing customer today?

Sources:
https://www.bj.admin.ch/de/newnsb/x3sKLxCJ6S3dQJtfvy0Tb
https://www.bj.admin.ch/de/schweizerisches-transparenzregister
https://www.transpareg.admin.ch/de/wer-muss-melden
https://www.transpareg.admin.ch/de/registerzugang-und-meldung-von-unterschieden
https://www.leasingverband.ch/de/downloadFileContent?id=3080C602-9B1D-4842-8D1C-3793D133189D
https://www.finma.ch/de/ueberwachung/branchenuebergreifende-themen/geldwaeschereibekaempfung/
https://cms.kellerhals-carrard.ch/uploads/Neues_Gesetz_ueber_die_Transparenz_juristischer_Personen_TJPG_6d2dcd0e17.pdf
https://www.finma.ch/news/2026/05/20260512-mm-anh-gwv-finma/
https://www.sif.admin.ch/de/geldwaeschereigesetz-gwg

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A convincing AI answer is not yet financial analysis.

OpenAI has introduced a financial services product that brings professional data, analysis and granular citations into one environment. Its initial emphasis is on research and investment banking. The question it raises for leasing is more familiar: can we trace every number in a credit file to its source?

An application draws on accounts, statements, company records and asset documents. When a system turns these into a credit memo, the reader needs to see which document supports each claim, when it was produced and where the model has made an inference. A polished paragraph cannot stand in for evidence.

A faster first draft has value. A draft without reliable references merely transfers the work to the person asked to approve it.

I would start with a simple rule: no decision-relevant figure without a traceable source. The model may assemble and question the evidence. Credit authority remains with the people responsible for the decision.

How much time does your team spend finding the evidence behind a credit recommendation?

Source: https://openai.com/index/introducing-chatgpt-financial-services/

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AI starts in the engine room

Most AI projects do not fail because of AI. They fail because of Excel.
In almost every discussion about artificial intelligence, someone eventually asks which data the model is actually supposed to access. Then the room goes quiet.
The uncomfortable truth for many mid-sized businesses is that production data is on paper or in the shift supervisor’s head. Inventory is recorded in a spreadsheet maintained by exactly one person. The machines provide no data because they date from a time when nobody wanted any. And the ERP system was last seriously addressed when the predecessor’s predecessor was still in charge.
Nobody likes to discuss this because it sounds like the company has fallen behind. Yet it is simply the normal state of an economy whose substance lies in machinery and expertise rather than data architecture.
AI is not software that you simply install. It is the top layer of an infrastructure that must work beneath it: ERP, sensors, connected equipment, data quality and defined processes. Without that foundation, even the best model produces precise answers based on incorrect figures, and nobody notices because the answer is well written.
That is the real investment, and it is not glamorous. Nobody gives a keynote about barcode scanners. That is precisely why it is postponed: it is difficult to market as innovation and easy to classify as “later”.
The practical answer lies in sequencing, not abstention. These preliminary investments can be staged. Each stage must create value in its own right. Telematics saves kilometres before any algorithm joins the calculation. Financing with predictable instalments makes this staging budgetable in the first place because it avoids a new capital request every year.
A logistics SME leases telematics systems and modern scanners. Only then does AI-assisted route planning become a realistic option rather than a presentation slide.
An honest question for the room: how many AI workshops have you completed, and how many interfaces have you built in the same period?

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AI starts in the engine room

Most AI projects do not fail because of AI. They fail because of Excel.
In almost every discussion about artificial intelligence, someone eventually asks which data the model is actually supposed to access. Then the room goes quiet.
The uncomfortable truth for many mid-sized businesses is that production data is on paper or in the shift supervisor’s head. Inventory is recorded in a spreadsheet maintained by exactly one person. The machines provide no data because they date from a time when nobody wanted any. And the ERP system was last seriously addressed when the predecessor’s predecessor was still in charge.
Nobody likes to discuss this because it sounds like the company has fallen behind. Yet it is simply the normal state of an economy whose substance lies in machinery and expertise rather than data architecture.
AI is not software that you simply install. It is the top layer of an infrastructure that must work beneath it: ERP, sensors, connected equipment, data quality and defined processes. Without that foundation, even the best model produces precise answers based on incorrect figures, and nobody notices because the answer is well written.
That is the real investment, and it is not glamorous. Nobody gives a keynote about barcode scanners. That is precisely why it is postponed: it is difficult to market as innovation and easy to classify as “later”.
The practical answer lies in sequencing, not abstention. These preliminary investments can be staged. Each stage must create value in its own right. Telematics saves kilometres before any algorithm joins the calculation. Financing with predictable instalments makes this staging budgetable in the first place because it avoids a new capital request every year.
A logistics SME leases telematics systems and modern scanners. Only then does AI-assisted route planning become a realistic option rather than a presentation slide.
An honest question for the room: how many AI workshops have you completed, and how many interfaces have you built in the same period?

Comments closed