{"id":13924,"date":"2026-08-19T05:12:05","date_gmt":"2026-08-19T05:12:05","guid":{"rendered":"https:\/\/www.exporis.ch\/swiss-finance-is-moving-deeper-into-the-technology-stack\/"},"modified":"2026-08-19T13:10:11","modified_gmt":"2026-08-19T13:10:11","slug":"swiss-finance-is-moving-deeper-into-the-technology-stack","status":"publish","type":"post","link":"https:\/\/www.exporis.ch\/fr\/swiss-finance-is-moving-deeper-into-the-technology-stack\/","title":{"rendered":"Swiss Finance Is Moving Deeper Into the Technology Stack"},"content":{"rendered":"
\n

With this article, Exporis starts a regular look at Switzerland\u2019s technology scene, following the companies, funding, regulation and ideas shaping finance and deeptech. For the first edition, we look at why AI, wealthtech and deeptech are moving closer to the core of Swiss financial services in 2026.<\/em><\/p>\n

In July 2026, Geneva-headquartered banking software company Temenos completed its acquisition of Zurich wealthtech company additiv. Temenos supplies core banking, digital banking and wealth-management software to more than 950 banks, while additiv specialises in technology that connects investment products, client data and the processes used by advisers. During the same month, European financial-software group Objectway agreed to acquire FNZ\u2019s Swiss private-banking technology business, adding more than 40 private-bank clients in Switzerland and Liechtenstein. FINMA, meanwhile, told financial institutions to start preparing their encryption systems for the eventual arrival of quantum computers.<\/p>\n

A software acquisition and guidance on encryption may appear unrelated, but both concern the machinery behind financial services: the systems that hold client information, connect applications, protect data and increasingly allow software to perform work that employees previously handled themselves. Much of the fintech<\/a> boom of the previous decade concentrated on products clients could see, from mobile banking and digital brokers to robo-advisers and online investment platforms. In 2026, banks and technology companies are putting more effort into the systems underneath those services because AI exposes quickly where information is fragmented, processes depend on manual work and applications cannot communicate properly with one another.<\/p>\n

Swiss deeptech is moving closer to finance<\/h2>\n

Switzerland already has an unusually large share of its venture capital tied to technically demanding companies. Between 2020 and 2026, 63 percent of venture capital invested in the country went into deeptech, ahead of China at 56 percent and the United States at 54 percent. Swiss deeptech companies raised a record $2.6 billion in 2025, while Switzerland ranked first in Europe for deeptech investment per capita.<\/p>\n

The first half of 2026 continued that pattern. Swiss startups raised $1.58 billion overall, hardware companies attracted more than $411 million in their strongest half-year on record, and seed funding rose almost 69 percent. Much of this investment has little connection to financial services; robotics, biotechnology and aerospace remain important parts of the Swiss deeptech market. But several fields now touch banking directly, including AI, cybersecurity, advanced computing, semiconductors, cryptography and quantum research.<\/p>\n

For Swiss finance, deeptech is beginning to play two roles. Banks and wealth managers can invest in these companies, while also buying, integrating or relying on the technology they produce. A private bank will never build its own semiconductor, for example, but the cost and availability of computing power affect which AI systems it can run. It may never develop quantum technology, yet it already has to consider how future quantum computers could affect the encryption protecting client information.<\/p>\n

The overlap is therefore practical rather than theoretical. As financial institutions use more AI, automate more processes and depend on larger quantities of data, they also depend more heavily on the technologies that make those systems fast, secure and reliable.<\/p>\n

Temenos and Objectway want to connect more of the bank<\/h2>\n

The deals announced in summer 2026 show how banking software companies are responding. Temenos already provides the core systems that banks use to run accounts, transactions and other day-to-day processes, alongside digital and wealth-management software. Additiv sits closer to investment and advisory services, providing technology that connects financial products, advisers, client information and digital channels. Bringing additiv into Temenos allows the group to link more of the systems where banks hold information with the applications used by advisers and clients.<\/p>\n

Objectway works in a more specialised part of the same market. The European financial-software company supplies banks, wealth managers and asset managers with technology for investment management, client servicing and banking operations. Its acquisition of FNZ\u2019s Swiss private-banking business, formerly New Access, gives it a larger presence among Swiss and Liechtenstein private banks and extends the range of systems it can provide to them.<\/p>\n

The logic becomes clearer when looking at how many private banks actually operate. A bank may keep client records in one system, portfolios in another and documents, reporting and communications in several more. Each application may work perfectly well on its own, yet employees still lose time finding information, checking whether two records match or moving data manually between systems.<\/p>\n

AI makes those weaknesses harder to ignore. A system cannot prepare a reliable briefing for a relationship manager if recent transactions sit in one database, investment restrictions in another and previous correspondence somewhere else. Before a bank can automate more of that work, it has to decide which information is correct, how systems exchange it and which data an automated tool may use.<\/p>\n

Temenos and Objectway are effectively betting that banks will want fewer gaps between those systems. Broader banking platforms can make information easier to move and reuse, although no acquisition can fix poor records, inconsistent internal processes or unclear responsibility for data by itself.<\/p>\n

Private banks have more reason to cut repetitive work<\/h2>\n

Swiss private banks also enter this technology cycle under tighter economic conditions. Higher interest rates supported earnings for several years, but Swiss rates have returned to zero, forcing banks to pay closer attention to costs and fee income. Technology budgets therefore have to do more than produce a cleaner client interface. Management wants to know whether a system can save advisers time, shorten an internal process or allow a team to handle more relationships without reducing service quality.<\/p>\n

AI can help when the work follows recognisable patterns. Relationship managers often prepare for meetings by collecting portfolio information, recent transactions and previous client requests from several sources. Investment teams repeatedly test portfolios under different constraints, while compliance staff review documents that contain recurring types of information. Automating part of that work can reduce the time specialists spend searching, copying and checking before they apply their own judgement.<\/p>\n

Swiss companies are already working on such tasks. Aisot uses predictive AI in portfolio construction and investment decisions, while fore ai develops autonomous testing technology for regulated financial software. Their products address different problems, but both focus on clearly defined work rather than giving a general-purpose AI system free access to a bank\u2019s internal processes.<\/p>\n

That narrower approach also makes control easier. A bank can specify which data a tool may use, what output it should produce and where an employee must review the result. In regulated finance, that is easier to manage than a vaguely defined \u201cAI assistant\u201d whose role expands without clear limits.<\/p>\n

Digital providers are moving into more financial products<\/h2>\n

Banks are not the only companies widening their role. Finpension passed CHF 6 billion in assets under management and 75,000 clients during summer 2026 and is now seeking a banking licence as it prepares to enter mortgages.<\/p>\n

The commercial logic is straightforward. Once a company already manages a client\u2019s pension or investment assets, it does not have to build the relationship again before offering another financial product. Mortgages can sit beside investments and retirement savings rather than beginning with a completely new customer-acquisition process.<\/p>\n

Finpension does not compete directly with every Swiss private bank. Wealthy international families often need complex lending, cross-border structuring and investment services that a digital pension provider does not offer. The longer-term effect lies with clients who spend years managing pensions and investments through software before they ever speak to a private banker. By the time some of them reach private-banking levels of wealth, they will already expect fast access to information, straightforward digital processes and a much more connected view of their finances.<\/p>\n

The boundaries between fintech, banking and wealth management therefore become harder to maintain as companies expand. Pension providers add investments and credit, software groups move further into core banking, and banks themselves rely on outside technology for parts of the business they once handled almost entirely in-house.<\/p>\n

FINMA is already dealing with technology banks may use years from now<\/h2>\n

FINMA\u2019s July 2026 guidance on quantum computing shows how deeply technical questions have entered banking supervision. The regulator surveyed 60 Swiss financial institutions between November 2025 and January 2026 and found that most understood the cyber risk posed by sufficiently powerful quantum computers, although many had not yet prepared a clear plan for moving towards quantum-safe encryption.<\/p>\n

No commercially available quantum computer can currently break the cryptography protecting Swiss bank accounts. Banks still have to prepare early because some financial information must remain confidential for many years and replacing encryption across a large institution can itself take years. Attackers could also collect encrypted information now and try to decrypt it later once the necessary computing power exists.<\/p>\n

A technology still largely confined to laboratories can therefore affect decisions banks make in 2026 about systems they expect to use for another decade. AI creates similar questions much sooner. Once software starts preparing investment recommendations, summarising client information or carrying out part of an internal process, banks need to know which data it used, how it reached an output and who can intervene when it gets something wrong. Technology teams cannot answer those questions alone because compliance officers and business managers remain responsible for what the institution ultimately does with the result.<\/p>\n

AI depends on what sits underneath it<\/h2>\n

For years, banks could show customers technological progress through visible improvements such as digital onboarding, better reporting or a more convenient investment app. Those features remain useful, but competitors can copy them and clients quickly begin to expect them as standard.<\/p>\n

AI places more pressure on the systems behind the interface. Most banks will be able to buy access to capable models, but they will not all have equally reliable data or equally well-connected systems. A sophisticated model cannot compensate for client records scattered across several databases if nobody knows which version is correct, nor can it automate a process safely when permissions and responsibilities remain unclear.<\/p>\n

That is why the Temenos-additiv and Objectway-FNZ deals say more about Swiss financial technology in 2026 than another bank announcing that it has introduced generative AI. Banks first need software that can find the right information, move it between systems and control who or what can use it. Only then can automation become part of everyday financial work rather than another application sitting beside it.<\/p>\n

Switzerland starts from a strong position. The Swiss universities ETH Zurich and EPFL continue to produce deeptech companies, Zurich and Geneva remain major banking and wealth-management centres, and Zug has built a sizeable digital-assets industry. Swiss deeptech companies still rely heavily on foreign investors when they raise the largest growth rounds, so scientific strength does not automatically translate into Swiss ownership at scale.<\/p>\n

What the summer of 2026 shows more clearly is how these parts of the economy are beginning to interact. Banks are buying software that connects more of their operations, regulators are asking how new technologies will affect the security of those systems, and deeptech companies are building tools that banks can use in portfolio management, cybersecurity, computing and internal workflows. As more financial work moves into software, banks will depend increasingly on the quality of the data, systems and controls underneath it, bringing Switzerland\u2019s deeptech companies closer to the everyday business of finance.<\/p>\n

 <\/p>\n<\/div>\n

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