What happens when AI evolves from a tool into a trusted co-worker? According to Microsoft’s 2025 Work Trend Index, that’s already the reality for ‘frontier firms’: a new wave of organisations where humans and AI agents collaborate to drive innovation and performance.
“A frontier firm is an organisation that combines human expertise with AI agents to improve efficiency, accelerate growth and create new value,” says Dalia Ophir, director of business strategy for worldwide financial services at Microsoft. “AI handles tasks while humans provide oversight and direction.”
But how does this translate into banking and insurance?
“Being a frontier firm in financial services means embracing a new operating model – one where AI agents and human teams work side by side to deliver faster, smarter and more personalised outcomes,” says Tyler Pichach, global head of AI strategy and go-to-market for payments and banking at Microsoft. “It’s not just about automation; it’s about augmenting human judgement with real-time intelligence and adaptive systems that can learn and evolve.”
In the insurance sector specifically, becoming a frontier firm boils down to reinventing the value chain with AI at its core.
“Becoming a frontier firm in the insurance sector involves rethinking operational models by integrating AI agents into core business processes,” says Ophir. “This transformation impacts the entire insurance value chain, including sales and distribution, underwriting, risk assessment, claims management, customer engagement and product innovation.”
Current challenges like economic uncertainty, evolving customer expectations and the rising demand for personalised products mean that insurance firms need to act if they haven’t already done so.
“Now is the right time because technology has matured, the regulatory frameworks are catching up and customer expectations have shifted,” says Pichach. “Institutions that delay risk falling behind – not just in innovation, but also in trust, efficiency and relevance. The frontier firm will be perhaps the greatest equaliser of our time. Smaller banks and financial firms can build agents and agentic workflows to scale to the same level as larger banks that have thousands of people. At the same time, larger institutions can transform their agent workforce to grow without adding incremental employees. The frontier firm is no longer a future vision; it’s a competitive imperative.”
For many banks, the conversation around AI and core modernisation has been ongoing for years but now, their focus is shifting from exploration to execution.
“Banks are moving beyond pilots and proof of concepts and starting to embed AI, especially generative AI, into the heart of their modernisation efforts,” says Pichach. “Some of the exciting areas are mainframe and application transformation. Historically, these have been a slow, high-risk process. But with tools like GitHub Copilot and Microsoft Azure OpenAI, we’re seeing banks accelerate code understanding, documentation and test generation.”
In Microsoft’s mainframe modernisation programmes, generative AI is helping teams reverse-engineer millions of lines of legacy code, generate test cases and assist in rewriting code into code languages like C# or Java. “This isn’t just about speed, it’s about reducing risk and improving quality,” says Pichach. “In fact, developers using GitHub Copilot report writing code up to 55 per cent faster, with higher satisfaction and fewer errors.”
Faster coding means teams can focus more time on innovation and delivering business value, rather than getting bogged down in repetitive or manual tasks.
Banks are also applying generative AI to streamline onboarding, automate document processing and modernise lending platforms, all while maintaining compliance and control.
“The key is that AI isn’t just a layer on top of legacy systems, it’s becoming a catalyst for rethinking how those systems are built, maintained and evolved,” says Pichach.
This shift is not just about core systems; it’s also about unlocking value across the entire business. In retail banking, that means using generative AI to drive productivity gains and support more consistent, compliant customer interactions.
“What’s different now is that we can drive efficiency without sacrificing control,” explains Pichach. “We’re seeing banks use generative AI to reduce manual effort, improve auditability and accelerate time to insight, all while staying within the guardrails of regulatory expectations. Take regulatory document review, for example. What used to take weeks of manual scanning, impact analysis and control mapping can now be done in a fraction of the time. Using a suite of AI agents to manage regulatory updates, control quality assurance and gap analysis agents means banks can automate the end-to-end compliance lifecycle. In one case, regulatory compliance processes became five times faster following implementation, with over 5,000 unique mappings generated and more than 300 regulatory gaps identified and addressed.”
Banks and insurers are embedding AI into the core of their operations to reimagine how work gets done. Microsoft’s own finance division has deployed AI agents to streamline everything from quote-to-cash to tax compliance and financial close processes. This has enabled Microsoft to achieve a 75 per cent time saving on reporting and compliance, reduced invoice processing duration by 60 per cent, and cut tax file preparation effort by 97 per cent.
“In the broader industry, we’re seeing financial institutions, as well as Microsoft, use AI to automate reconciliation and collections, streamline document-heavy processes and enable intelligent agents for treasury and risk,” says Pichach. “Microsoft’s platform approach, combined with our ecosystem of partners, is helping institutions modernise without needing to rip and replace. It’s about building a bridge from legacy to future ready.”
Microsoft AI is also empowering insurance firms to deliver more personalised, proactive and impactful services through innovative collaborations like the one with dacadoo. Imagine an insurance customer whose wearable device shows a steady drop in physical activity and irregular sleep patterns over several weeks. dacadoo’s Digital Health Engagement Platform, powered by Microsoft Azure and generative AI, detects the changes in real time and flags them as potential early indicators of a health issue. Instead of waiting for a health insurance claim to be filed months down the line, the system sends a nudge through the insurer’s wellness app, offering personalised advice to encourage healthier habits and suggesting a virtual check-in with a healthcare provider. At the same time, the insurer’s risk model updates automatically, allowing for more accurate and timely policy adjustments. This kind of early, tailored intervention helps reduce long-term costs for insurers while supporting better outcomes for the customer.
“Generative AI will have a significant impact on claims processing,” says Ophir. “It has the power to reduce claims payout by 20 to 30 per cent and decrease loss-adjustment expenses. Across the insurance enterprise, employees will benefit from simplification in how they work, live and consume knowledge. It will remove all the low-touch, tedious activities so people can interact with each other and technology to help get the job done.”
Insurers are also using Microsoft Copilot to summarise emails, meetings and documents so employees can focus on more important tasks, like building stronger client relationships and making faster, more informed decisions.
Insurance firm Hiscox, for example, rolled out Copilot to 300 end users for three months in a pilot that grew to include 1,000 employees over one year. “During the pilot, we saw 15 per cent of users gaining an hour of time back per day, 20 per cent saving half an hour and 20 per cent reclaiming 10 to 15 minutes per day,” says Chris Loake, group chief information officer at Hiscox.
These time savings are particularly valuable given the challenges of traditional insurance workflows, which involve manual processes, multiple approvals and siloed systems that hinder operational efficiency.
Hiscox employees have saved up to an hour per day with Copilot
“Institutions are faced with complex, time intensive and inefficient claims and underwriting processes that waste time and resources, and impact the policyholder’s experience,” says Ophir. “The standard process today takes between days and multiple weeks from the point at which a policyholder gets into an accident to finally paying them their claim.”
Policyholders expect the process to be much faster. With generative AI solutions, insurance companies can accelerate the claims process from weeks to hours, enhance accuracy by enabling faster reporting and streamline claims evaluation.
“We’re entering a new phase in financial services – one where AI isn’t simply augmenting workflows, it’s beginning to operate them,” says Pichach. “The shift to agentic AI is reshaping how core systems are designed, deployed and governed. These aren’t just smarter tools, they’re autonomous agents capable of executing tasks, orchestrating processes and even collaborating with other agents across the enterprise. In payments, for example, we’re seeing AI agents handle everything from transaction reconciliation and exception repair to dispute resolution and know your customer. These agents don’t just automate – they reason, learn and adopt. They can interpret SWIFT messages, diagnose errors, draft responses and even take corrective action through legacy systems using computer-using agents.
“This evolution is truly shaping the frontier firm, a model where humans set direction and AI agents operate the business across three phases: AI copilots assist employees, agents join teams as digital colleagues, and agents run entire workflows with humans in the loop for oversight.”
Both Pichach and Ophir warn that the success of financial organisations will increasingly hinge on their ability to harness AI’s potential.
“Banks must embrace AI and modernise their core platforms or risk becoming as obsolete as a floppy disk,” says Ophir, who advises firms follow six strategies. “First, they need to rearchitect core systems then they need to invest in data foundations and build unified data estates that break down silos and enable real-time analytics.”
Then, firms can implement frameworks for AI transparency, fairness and accountability. “Develop the guardrails, set the right culture and experiment with Copilot and AI technology as it will become the norm for enterprise applications,” she explains.
The final three strategies include upskilling the workforce by training them in AI literacy, prompt engineering and agentic workflows; prototyping and scaling use cases by starting with high-impact, low-risk cases like fraud detection and policy intake; and engaging with ecosystems to co-innovate and derisk adoption.
“The re-engineering process is a great way to get into the heart of the core business; it’s a science in itself,” says Ophir. “After you’ve built a proof of concept, you should capture the potential time saved and the return on investment. Also, make sure to embed compliance checks where it makes sense to save time and effort later.”
Leaders must also prioritise data readiness, composable architectures, and governance and trust.
“AI is only as good as the data it learns from,” says Pichach. “Harmonising structured and unstructured data – ISO 20022 in payments for example – is foundational. Legacy systems need to be opened up with APIs and cloud-native services. And, as AI agents take on more responsibility, clear policies around authentication, authorisation and auditability become critical. Microsoft’s work with Mastercard, PayPal and Visa on using tokens to secure agentic payments are examples of how we’re addressing this.”
PayPal is using Microsoft technology to secure agentic payments
Mastercard’s Agentic Payments Program uses agentic tokens and payment passkeys to enhance trust, security and control across transactions. It is working with Microsoft to integrate Microsoft Azure OpenAI Service and Microsoft Copilot Studio with its payment solutions to develop and scale agentic commerce. The tokenisation technology will enable payments to be initiated through conversational interfaces and conducted by the millions of merchants of all sizes that support online commerce today.
“Mastercard is transforming the way the world pays for the better by anticipating consumer needs on the horizon,” says Jorn Lambert, chief product officer at Mastercard. “The launch of Mastercard Agent Pay marks our initial steps in redefining commerce in the AI era, including new merchant interfaces to distinguish trusted agents from bad actors using agentic technology.”
With the rapid evolution of AI from a supporting tool to the very foundation of business operations, the imperative for leadership is clear, says Pichach.
“The bottom line? AI is no longer a layer on top of core systems – it’s becoming the operating model. Leaders who embrace this shift now will define the next generation of financial services.”
Partner perspectives
We asked selected partners how they are helping banks and insurance firms to modernise their core systems with Microsoft’s AI capabilities.
“We have developed an enterprise data and AI environment built on Azure, which provides FIS teams with access to data-driven capabilities, enabling AI use cases across a range of applications,” says Firdaus Bhathena, chief technology officer at FIS. “Beyond foundational infrastructure, FIS is breaking new ground with agentic AI capabilities powered by Azure Databricks.”
“IBM is helping banks and insurers modernise their core and next generation systems by combining the power of IBM’s AI with Microsoft’s AI capabilities,” says Sridhar Penumetcha, service partners leader for financial services at IBM Technology. “Together, we’re enabling clients to accelerate transformation through solutions like IBM watsonx Orchestrate, which automates complex workflows, and Copilot, which enhances productivity and decision-making.
“M-Files helps financial institutions modernise by natively storing content within Microsoft 365 and integrating with Microsoft Copilot to deliver AI-powered document workflows,” says Yohan Lobo, senior industry solutions manager at M-Files. “Banks and insurers benefit from automated governance, secure collaboration and metadata-driven access to critical content – enhancing compliance, customer service and operational agility.”
“Moody’s is helping banks and insurers modernise core systems by embedding AI into their most knowledge-intensive workflows – from credit assessment to portfolio oversight,” says Cristina Pieretti, general manager at Moody’s Digital Content and Innovation. “Powered by Microsoft’s cloud and AI infrastructure, our agentic solutions automate multi-step processes with transparency and precision.”
Discover insights from these partners and more in the Autumn 2025 issue of Technology Record. Don’t miss out – subscribe for free today and get future issues delivered straight to your inbox.