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New integration adds data-centric protection to Temenos Transact, streamlining compliance, secure modernization, and AI analytics.

WIESBADEN, GERMANY – EQS Newswire – 18 February 2026 – comforte AG, a global leader in data-centric security, and ITSS Global, a premier Temenos delivery partner, have announced a collaboration to help retail, commercial and private banks using Temenos Transact eliminate the risks associated with clear-text personally identifiable information (PII) and payment data across core banking systems and their connected environments.
As banks accelerate digital transformation and data-driven programs such as fraud prevention and AI, exposure of sensitive data across systems has become a growing concern. Regulators and industry standards worldwide are also raising the bar for how banks protect sensitive data and prove control across connected environments, including PCI DSS, privacy requirements, and resilience expectations. The comforte and ITSS collaboration addresses these challenges with a co-developed solution that extends data protection into Temenos Transact environments without complex customization.
Delivered by ITSS as part of its Temenos services, the integration leverages comforte’s TAMUNIO technology for centralized policy management, tokenization, and controlled de-tokenization, keeping sensitive data protected across environments while still supporting reporting, analytics, and downstream processing, including fraud detection workflows and AI-driven insights built on Transact data.

Turning Security into an Enabler
“The modern threat landscape demands a shift from securing systems to securing the data itself,” said Henning Horst, CTO at comforte. “Today’s regulators and auditors expect readable data to stay out of places it doesn’t belong. Together with ITSS, we help banks prove that control and move faster on analytics, fraud initiatives, and AI programs using protected data.”

Safe Implementation into Temenos Transact
“As banks modernize their Temenos environments, the real security challenge is no longer the perimeter. It is protecting sensitive data as it moves across core systems, analytics platforms, and the cloud,” said Somasundaram M, Regional Sales Director, MEA at ITSS. “Through our partnership with comforte, we enable Temenos clients to embed data-centric tokenization directly into their transformation journeys. This significantly reduces breach exposure, supports compliance with evolving regulatory mandates such as PCI DSS 4.0 and GDPR, and allows banks to adopt cloud, analytics, and AI-driven use cases without compromising data sovereignty or performance.”

To learn more or request a briefing, visit comforte.com. You can alsocontact us via email: [email protected] / [email protected].Hashtag: #comforteAG

The issuer is solely responsible for the content of this announcement.

About comforte AG

comforte AG is a leading provider of data-centric security solutions that empower enterprises to protect sensitive information throughout its lifecycle while maintaining its usability for business operations. Headquartered in Wiesbaden, Germany, comforte is a trusted partner for global enterprises across various industries. The TAMUNIO data security platform automates the discovery, classification and protection of data within complex IT environments. With over 25 years of expertise, comforte safeguards data for over 300 global customers, including industry leaders like Visa and Mastercard, enabling them to drive digital transformation, optimize operations, and achieve sustainable growth with confidence.
For more information, visit comforte.com and follow comforte AG on LinkedIn.

About ITSS
ITSS Global is a Geneva-headquartered technology services and solutions provider with a presence in more than 25 strategic locations worldwide. Since 2001, ITSS Global has delivered best-in-class outcomes through deep banking expertise and strong technical capabilities, supporting organizations with end-to-end IT modernization and operational excellence. The company provides expertise across infrastructure, cybersecurity, and managed services—helping clients enhance performance, strengthen security, and scale with confidence.

A multi-certified Temenos partner, ITSS Global has supported 300+ clients globally as a system integrator across the full Temenos suite, while also delivering complementary solutions that extend and enhance the Temenos core—enabling future-ready banking transformation through cloud adaptability, AI enablement, and continuous innovation.

For more information, visit www.itssglobal.com and follow ITSS on LinkedIn and X.

Singapore’s drive to harness artificial intelligence as an engine of economic growth is entering a decisive phase marked by abundant ambition and clear signs of strain across company ranks. Government fiscal policy and private-sector deployment are converging on AI, but weak data infrastructure, skills gaps and uneven returns are tempering expectations even as enterprises escalate investments and policy support grows.

Last week, the nation’s Budget for the 2026 fiscal year unveiled a suite of measures aimed at elevating AI adoption across multiple industries. Prime Minister and Finance Minister Lawrence Wong confirmed the establishment of a National AI Council, to be chaired by himself, tasked with coordinating research, regulation and investment to align public and private interests in developing AI capability. The plan also includes National AI Missions focused on advanced manufacturing, connectivity and logistics, finance and healthcare, sectoral areas where government and business leaders see the most potential for productivity gains and value creation. The budget expands fiscal incentives with enhanced tax deductions for AI-related expenditures over the next two assessment years and widened grant schemes to support adoption, workforce training and enterprise transformation. Leaders of major consultancies said these measures signal a shift from experimentation to enterprise-scale adoption and give firms a clearer pathway to embed AI into core operations.

Despite this policy momentum, data from industry surveys and corporate research paint a more nuanced picture of utilisation and outcomes. Adoption of AI tools in Singapore is now near universal among larger firms, with about 96 per cent reporting some level of use. But a significant gap remains between deployment and measurable returns on investment. Only a minority of organisations consider themselves leaders in achieving strong, sustained ROI, indicating an emerging disconnect between AI deployment at scale and operational readiness to turn it into business value. Executives widely acknowledge that sprawling and complex data environments, coupled with cybersecurity concerns, are contributing to operational friction and risks that constrain potential gains.

Private forecasts and vendor research suggest that enterprises are committed to accelerating AI spending even as returns lag. Surveys of business leaders show average investments in AI of around SG$18.9 million, with expectations for investment growth of roughly 38 per cent over the next two years and ROI projections rising to an average of 29 per cent during the same period. Yet analysts note that these returns will depend significantly on firms’ ability to bridge gaps in data readiness and workforce capability. Many Singapore companies acknowledge limited internal training, fragmented data integration and widespread informal use of ungoverned AI tools, all of which undermine robust enterprise-level strategy and governance structures.

Structural issues are as salient as technical ones. Industry leaders point to weaknesses in reliable data foundations and the need for stronger leadership alignment to embed AI into strategic operations rather than relegated to pilot projects or isolated business functions. Senior executives contend that competitive advantage over the coming decade will be determined less by technology choice and more by how effectively organisations build hybrid human-AI teams and integrate AI into everyday workflows.

Talent acquisition and retention also feature prominently in conversations around Singapore’s AI trajectory. Advanced AI, cloud and cybersecurity skills are in high demand globally and Singapore is no exception, with firms reporting difficulty scaling teams with the specialised expertise needed to support complex AI systems. This talent shortage both drives up costs and slows the pace at which organisations can absorb and leverage new technologies.

Cloud infrastructure and advanced digital foundations are another determinant of success. Financial services institutions in Singapore, for example, are among the most advanced globally in cloud adoption, with a majority running core workloads in cloud or hybrid environments that facilitate large-scale AI deployment. This infrastructure supports use cases ranging from compliance and risk management to fraud detection and transaction monitoring. However, budget constraints, talent gaps and integration challenges remain headwinds even in these relatively strong pockets of adoption.

Commentators outside the corporate sphere emphasize the importance of inclusive growth, noting that small- and medium-sized enterprises must not be left behind in the national AI push. Business federation and consultancy leaders warn that without targeted support for smaller firms to sustain, not just adopt, AI technologies, widening capability divides could undermine broader economic innovation and productivity goals.

Debjani Ghosh, who leads Anthropic’s operations and policy engagement in India, said the scale of adoption by developers, enterprises and start-ups has placed the country just behind the United States in terms of usage and integration of Claude’s models. She described India as a “strategic growth engine” for the company, citing strong demand from sectors including financial services, healthcare, education and software development.

Anthropic, founded in 2021 by siblings Dario Amodei and Daniela Amodei, has positioned Claude as a competitor to models from OpenAI and Google. The company has attracted substantial backing from Amazon and Google, with Amazon committing up to $4 billion as part of a strategic partnership to integrate Claude into Amazon Web Services infrastructure. The funding has enabled Anthropic to expand globally, with India becoming a focal point due to its developer base and digital economy.

India’s prominence in the AI adoption cycle reflects broader structural factors. The country has one of the world’s largest pools of software engineers, a fast-growing start-up ecosystem, and a government push towards digital public infrastructure. Enterprises across banking and fintech have begun embedding generative AI tools to automate compliance checks, summarise documents and enhance customer interaction. In healthcare, pilot projects are under way to use AI systems for clinical documentation and triage support, while education technology platforms are deploying AI-driven tutoring tools.

Ghosh indicated that India’s market dynamics differ from those of Western economies. Cost sensitivity and the need for scalable deployment across diverse languages and devices have shaped how enterprises experiment with large language models. Claude’s emphasis on constitutional AI — a framework designed to make outputs safer and more aligned with human values — has resonated with corporate clients concerned about regulatory risk and reputational exposure.

Regulatory considerations are central to the AI conversation in India. The Ministry of Electronics and Information Technology has signalled its intent to craft a framework that balances innovation with safeguards against misinformation, bias and misuse. While India has not enacted a standalone AI law, policy discussions have intensified around data governance and algorithmic accountability. Companies operating in the country must also comply with the Digital Personal Data Protection Act, which imposes obligations on data fiduciaries and processors.

Industry analysts note that India’s large English-speaking population has historically accelerated the adoption of global technology platforms. However, the next phase of growth in AI is expected to depend on multilingual capabilities. Claude’s ability to handle multiple languages is seen as an advantage in a country with 22 constitutionally recognised languages and hundreds of dialects. Developers are increasingly testing generative models for vernacular content generation and customer support.

Competition in the Indian market is intensifying. OpenAI’s ChatGPT has built a strong user base, while Google has integrated its Gemini models into productivity tools and cloud services. Domestic start-ups are also entering the field, building foundation models trained on local datasets. Analysts say that enterprise adoption, rather than consumer usage alone, will determine long-term market leadership.

Anthropic’s expansion strategy in India includes partnerships with cloud providers and enterprise software companies. By leveraging Amazon Web Services’ presence in major Indian cities, Claude is being offered as part of broader digital transformation packages. Ghosh emphasised that collaboration with academic institutions and start-up incubators is another priority, with the aim of fostering responsible AI research and skills development.

The rapid uptake of generative AI has also raised concerns. Experts warn of the risks of hallucinations, data leakage and overreliance on automated systems. In financial services, regulators have cautioned against using AI outputs without human oversight. Cybersecurity specialists highlight the potential for AI tools to be misused for phishing or deepfake generation. Anthropic has sought to address such issues by embedding guardrails into its models and conducting external safety evaluations.