Yet as organizations deepen their partnerships with major cloud and AI providers, regulators and executives alike are sharpening their focus on concentration risk, the concern that reliance on a relatively small number of technology providers might create critical business vulnerabilities. 

Rather than viewing cloud dependency as a threat, forward-looking leaders regard it as an important facet of modernization. The challenge is not to avoid concentration; it is to manage it intelligently, helping a firm maintain control, enhance resilience, and remain flexible amid changing conditions.  

For financial services firms in many jurisdictions, exit planning—a structured process to safely disengage from critical providers—has moved from a theoretical consideration to a regulatory expectation and an important component of operational resilience. 

Managing risk and exit planning in an evolving landscape 

Concentration risk has long been framed as systemic exposure (“What if a key provider fails?”), prompting regulators to mandate exit plans that assume full termination. In theory, this seems straightforward; in practice, it rarely is. 

Modern financial institutions operate in a deeply interconnected ecosystem where critical third-party providers are embedded in core operations and strategic innovation. These partnerships go beyond simple outsourcing; they often underpin transformation initiatives and are key to resilience when managed well by the organization. As a result, in highly integrated environments, full disengagement may be operationally complex and unlikely in practice, but firms are still required to maintain feasible, risk based exit plans. 

In this regard, Microsoft has introduced important capabilities (such as standardized architectures, diversified cloud regions, and built-in failover options) that customers can incorporate into their resilience and exit planning strategies. They can effectively reduce dependency risk for critical services and ensure continuity, but they stop short of enabling a full provider exit. Regulators increasingly acknowledge that perfect exits are not always technically or economically feasible. What they require are proportionate, well tested plans that reflect operational reality. The priorities are transparency, control over critical workloads, and pragmatic dependency management.  

Against this backdrop, regulators are recalibrating expectations, focusing on actionable, tested strategies rather than theoretical full exits. Two major frameworks illustrate this shift: 

• The European Union Digital Operational Resilience Act (DORA): Requires institutions to maintain tested transition plans that enable the removal or migration of contracted information and communication technology (ICT) services and data.
• The United Kingdom Prudential Regulatory Authority (PRA) SS 2/21 and the Critical Third Party (CTP) oversight regime: Requires firms to maintain documented and tested exit strategies for any “material” (such as critical and high-impact) outsourcing arrangement, with clear definition of roles, responsibilities, and continuity plans. 

Both frameworks emphasize proportionality, focusing on critical or important business functions, and integration into broader business continuity and resilience of governance.  

Integrating exit planning within a broader resilience strategy 

Exit planning is no longer optional, it is a compliance essential. Fortunately, given the complexity of today’s hybrid and multi-cloud environments, regulators do not expect “perfect” exit plans. Instead, they encourage risk-based, practical, and tested practices that dovetail with broader efforts.  

Exit planning should be embedded within a comprehensive, structured approach to strengthen operational resilience. To support such an integrated approach, Microsoft has developed a six-step resilience framework that aligns closely with the requirements of DORA: 

1. Update cloud risk governance: Systematically review policies and controls to ensure that cloud adoption aligns with business priorities, regulatory requirements, and risk tolerance.
2. Identify concentration: Specify critical third-party and indirect nth-party dependencies, such as a vendor’s suppliers, subcontractors, or technology partners. 
3. Assess alternatives: Evaluate potential providers and exit strategies—comparing cost, resilience, and compliance to ensure continuity and mitigate concentration risk before making final decisions. 
4. Design for resilience: Plan systems and recovery processes that can withstand disruptions from hardware failures and service outages, recover quickly, and maintain critical operations. 
5. Test business continuity plan: Prepare for loss of a data center or region, or long-term failures, with regular testing that identifies gaps and validates recovery procedures. 
6. Prepare exit plans: Develop and test detailed exit strategies—including timelines, resource allocation, and contingency measures—to ensure seamless provider transition and maintain compliance under stress scenarios. 

This integrated approach ensures that exit plans remain both practical and sustainable, and do not exist in isolation. Ultimately, exit planning is part of a larger system of controls and safeguards, evolving alongside the business’s cloud and AI innovation cycles. 

Enhancing exit planning with guidance and tools from Microsoft 

Recognizing the criticality of continuity, reversibility, and secure data transfer in financial services organizations, Microsoft has developed a comprehensive framework of contractual commitments, technical solutions, and support services to empower firms to manage exit scenarios with confidence and control. 

For example, if a regulator intervenes in a company’s operations, Microsoft is committed to granting the regulator full administrative control over the institution’s cloud environment. In cases of reorganization or acquisition, Microsoft enables the assignment or transfer of service rights to successor entities, ensuring that critical services remain uninterrupted. Importantly, Microsoft will not suspend or terminate services solely due to a transfer of rights, provided contractual obligations are met, and offers flexible service extensions to facilitate smooth transitions and data retrieval. 

Beyond contractual measures, Microsoft equips customers with a suite of advanced technical tools to support seamless data migration and workload portability. These include:  

• Azure Arc, a bridge that enables hybrid and multi-cloud management, letting firms extend Microsoft Azure services to on-premises or other clouds for flexible migration and reduced concentration risk.
• Containerization and portability: Using containers (such as Azure Kubernetes Service and Docker) and microservices makes applications portable—simplifying workload transfers between Azure and other environments.
• Automated data migration: Built-in tools like Microsoft Azure Data Factory automate extract transform-load (ETL) processes, streamlining bulk data migration during exit events.
• Microsoft 365 data management, provided with Microsoft Purview and other solutions, to provide key capabilities, including:
  • eDiscovery tools that can export emails, documents, and collaboration data in standard formats for easy transfer.
  • Backup solutions to create point-in-time snapshots, supporting reversibility and continuity.
• Hybrid, private, and sovereign cloud options for Microsoft Exchange, SharePoint, OneDrive, and Skype for Business enable migration across platforms. 

By combining clear contractual safeguards, advanced migration tools, and ongoing investment in hybrid cloud and open APIs, Microsoft empowers financial institutions to plan and execute exit strategies that align with regulatory mandates and business objectives. Exit planning then becomes a proactive process, one that safeguards business continuity and regulatory compliance at every stage of the cloud journey. 

Learn more 

• For an in-depth analysis, download our whitepaper, “Addressing concentration risk and building practical exit strategies for Microsoft Cloud.”
• Read more about our approach for managing operational risk in financial services on Microsoft Learn.
• Visit our blog for stories of how Microsoft for Financial Services helps firms accelerate business value.

The post Managing concentration risk and exit requirements: A framework for financial institutions appeared first on Microsoft Industry Blogs.

As banks compete aggressively with AI, many are gravitating toward the concept of the Frontier Firm—a new kind of enterprise that doesn’t just use AI, but rearchitects itself around it. Frontier Firms view AI agents as digital colleagues, empower employees to act as agent bosses, and operate with intelligence on tap to work smarter, scale faster, and create new value.

Characteristics of the Frontier Firm in banking

The speed of transformation sparked by generative AI is unprecedented, leaving banks precious little time to make critical decisions. Across industries, 82% of leaders say 2025 is a pivotal year to rethink their organizational strategy, and 81% expect AI agents to be deeply integrated into their workforces within the next 12 to 18 months. In banking, 70% of companies that have adopted AI are realizing cost savings.² The challenge is to forge a strategy that delivers immediate ROI while also fostering long-term transformation.

The Frontier Firm concept brings clarity and a workable blueprint to this high-stakes challenge. It blends machine intelligence with human judgment, resulting in systems that are AI-operated but human-led. The Frontier Firm features the following characteristics:

• Intelligence on tap: AI capabilities are embedded across workflows and decision-making.
• Work chart versus org chart: Teams form around outcomes, not departments.
• Agent–boss mindset: Every employee manages and collaborates with AI agents.

With these principles in mind, banks can advance their innovation efforts without waiting for perfect conditions. Most banks are already well positioned to make quick strides.

The Frontier Firm in banking: Three-phase AI transformation journey

The journey to becoming a Frontier Firm plays out in three phases, each phase representing a deeper integration of AI into business operations. Organizations may operate in multiple phases at the same time, depending on function and maturity.

Phase 1: Human with assistant

In this phase, the goal is to empower employees with AI agents such as copilots and digital assistants that help improve productivity, generate efficiencies, and reduce drudgery.

Early innovation with generative AI in banking was limited, focused primarily on internal needs and designed to evaluate the technology and its impacts. These initial use cases quickly demonstrated both the immediate value and long-term potential of AI.

For many banks, an especially powerful productivity driver has been the adoption of Microsoft 365 Copilot, which embeds generative AI into everyday apps like Word, Excel, PowerPoint, Outlook, and Teams. In the UK, for example, with Copilot, Hargreaves Lansdown reduced the time required to record customer meeting notes from an average of four hours to just one. In Australia, Copilot helped Bank of Queensland cut the time required to produce drafts of internal manuals by 99%, marketing content by 88%, and human resource documents by 75%.

Complementing Microsoft 365 Copilot are a set of role-based agents that support specific job functions, one of which is Microsoft Copilot for Finance. Designed to help streamline operations and make faster decisions, Copilot for Finance connects with financial systems such as Dynamics 365 Finance ERP and even third-party platforms. At Microsoft, it delivered 22% in cost savings on reconciliation tasks for our corporate Treasury organization, doing in 10 minutes what previously took more than an hour. 

A key lesson here is that integrating AI into familiar productivity tools and daily workflows promotes quick adoption, as opposed to introducing new applications or interfaces. To amplify the impact, Copilot solutions can be enhanced to seamlessly work with a bank’s internal data and key partner connectors. For example, Wells Fargo built an agent for 35,000 bankers across 4,000 branches to help its employees find information to better assist customers. As a result, 75% of searches now happen through the agent, and query response times have gone from 10 minutes to just 30 seconds.³

Elsewhere, Barclays deployed Copilot to 15,000 users, and the results soon led to an expansion to 100,000 employees worldwide, incorporating the bank’s broad ecosystem of collaboration tools, portals and online resources. Likewise, using Azure OpenAI Service and Azure AI Search, Swiss bank UBS developed a set of “Smart Assistants” to help client advisors deliver more personalized insights by synthesizing 60,000 documents, plus a Legal AI Assistant (LAIA) that transforms how teams search a repository of 26 million multilingual legal documents.

An important counterpart to embedded copilots is an emerging class of personal agents within the Microsoft 365 Copilot suite, which can tackle deeper, domain-specific tasks. The Researcher Agent delivers in-depth insights by synthesizing internal and market data to support functions like strategic planning, compliance, and competitive analysis. The Analyst Agent works like a virtual data scientist, transforming raw data into forecasts, customer behavior visualizations, and automated reports.

Becoming a Frontier Firm: AI in financial services

See real-world examples of how Frontier Firms are leading with AI.

Read the e-book

Phase 2: Human–agent teams

In the second phase, AI agents take on specific tasks under human direction. Employees delegate tasks to them, review outputs, and intervene only for exceptions.

Some banks are now developing powerful agents to assist employees across a broad range of key tasks such as reconciling transactions, performing KYC checks, or conducting background verifications. Agents can also, help manage onboarding journeys, verify documents, and deliver training. The net effect is to free employees to focus on higher-value work at a greater scale.

For example, Dutch ABN AMRO Bank replaced its legacy chatbots with two new AI-powered assistants, Anna and Abby, that autonomously manage employee and customer conversations using Azure AI Language for intent recognition. Employees delegate routine tasks to the agents, which escalate to humans only for exceptions. This reduced drop-off rates, improved Dutch language accuracy by 7%, and now supports more than 3.5 million conversations annually.

Beyond customer service, banks are deploying agents to streamline complex, high-volume processes. In mortgage lending, agents can automate document verification, income validation, and regulatory checks—reducing cycle times and improving transparency. This helps lessen or eliminate bottlenecks caused by manual dependencies, accelerating approvals and improving customer satisfaction.

AI innovation in financial services is moving to a more powerful agent-based model in which AI serves as a collaborative tool. Financial services provider Virgin Money built a new contact center agent called Redi that triages customer inquiries, executes predefined journeys, and seamlessly escalates sensitive exceptions, such as bereavements, to human agents. Designed with input from customer center staff to emulate live interactions, Redi embodies the idea of “human-in-the-loop” governance, where AI handles the bulk of execution, but employees retain control over edge cases. Staff now view Redi as “another colleague” that supports them by triaging tasks and enabling them to focus on empathy and relationship-building.

Phase 3: Human-led, agent-operated

In this advanced phase, AI agents do more than assist or collaborate, they own and execute complete business processes. Humans provide direction, oversight, and exception handling, but day-to-day operations are managed by agents.

Agentic systems can reason, plan, and act independently to achieve goals. For example, an agent that can shop for clothing, plan a vacation, or buy groceries based on a consumer’s preferences and limits. This is the vision behind a new AI-powered platform that enables agents to “find and buy” on behalf of users.⁴ Features such as tokenized digital credentials, which confirm that an agent is authorized to act on a consumer’s behalf, foreshadow new ways agentic AI can deliver seamless, secure, and personalized experiences, and create new value.

Agentic AI-powered commerce and payments are driving a new suite of tools being developed by PayPal, designed to help developers build AI agents that can transact, manage invoices, and track shipments using PayPal’s APIs.⁵ As part of a unified platform for commerce, these tools let agents autonomously execute end-to-end commerce workflows using natural language.

Many banks are exploring innovation in agentic AI with scenarios spanning a broad range of business services, including advisory and customer service support; channels, like kiosks, online, social, and contact center; and operations, such as trading, payments, treasury, and more.

A key enabler of the Microsoft vision is the unique role of Microsoft’s global partner ecosystem, which encompasses an unparalleled range of independent software vendors (ISVs), global systems integrators (GSIs), and advisory firms. Our partners are building domain-specific Copilots, workflow agents, and Environmental, Social, and Governance (ESG) dashboards and regulatory compliance tools embedded within Microsoft AI, Microsoft 365, and Microsoft Azure. By incorporating agents into everyday tools and workflows, they are enabling the advanced real-time decision making, personalized customer engagement, and intelligent operations that make human-led, agent-operated AI a reality for banks.

The key role of governance in advanced AI

The promise of the Frontier Firm is to reimagine banking in ways that advance competitiveness and customer value. This can only happen with effective governance frameworks, which help ensure that all AI is developed and deployed safely and responsibly.

AI must be trustworthy, auditable, and aligned with corporate governance frameworks, so businesses can utilize its power without losing control. While many providers focus narrowly on compliance, Microsoft embeds governance into every layer of our AI stack, grounded in Responsible AI principles—fairness, reliability, privacy, inclusiveness, transparency, and accountability—and operationalized through centralized councils, cross-functional oversight, and tooling like Microsoft Purview.

For banks, this means AI systems that are not only compliant but also auditable, explainable, and aligned with regulatory expectations. We deliver governance at scale with a blueprint for responsible transformation and safeguards that protect customers, reputations, and regulatory standing.

Concurrently, a secure foundation is also critical. As your employees and customers interact with AI services, it is emerging as a new attack surface that requires world-class protection. Microsoft provides a comprehensive security platform, Microsoft Security Copilot with Microsoft Sentinel, which is fully integrated into our AI platform.

Learn more and explore Agentic AI

Helping banks chart their unique, comprehensive journey to becoming a Frontier Firm is central to our work at Microsoft. We build long-term relationships with customers, technology partners, data providers, and industry stakeholders to help banks create new value and customer relationships.

We have developed a five-step maturity journey and a set of foundational elements for any bank to become a Frontier Firm. To explore how your organization can move forward, start by engaging with your Microsoft representative or service provider.

• Visit Microsoft for financial services to learn more about how Microsoft empowers financial services organizations to achieve more. 
• To see how leaders in financial services are successfully using AI to transform complexity into opportunity, watch Leading at the Frontier: AI in Financial Services. 
• Get a practical transformation framework and see how Frontier Firms lead with agentic AI in our Becoming a Frontier Firm: AI in Financial Services e-book.
• Learn more about using Copilot in Financial Services and download the Financial Services scenarios kit.

¹ Forbes, The Future of AI in Financial Services, October 3, 2024

² KPMG, Intelligent banking report, February 2025

³Microsoft Work Trend Index Annual Report – 2025: The year the Frontier Firm is born, April 23, 2025

 ⁴ Visa, Find and Buy with AI, Visa unveils new era of commerce, April 30, 2025

⁵ PayPal Newsroom, PayPal brings together developers, AI leaders to power agentic commerce, April 29, 2025

The post The Frontier Firm in banking: A blueprint for advanced AI innovation appeared first on Microsoft Industry Blogs.

To keep abreast of the opportunities surrounding these changes, many central banks are actively experimenting with the idea of issuing digital versions of national currency, in the form of central bank digital currencies (CBDCs). This promising new form of digital money is made possible by advanced technology, which Microsoft is helping to enable through our global technology partner network. It is part of our commitment to Microsoft Cloud for Financial Services, which helps banks and other businesses unlock business value and deepen customer relationships. 

Microsoft Cloud for Financial Services

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How CBDCs are unique among digital currencies 

The growing preference for digitized money and payments has generated waves of innovation across governments, banks, and the global financial system. Cryptocurrencies like Bitcoin have demonstrated the potential value of new forms of digital currency. But because cryptocurrencies are unregulated, they remain too volatile to be widely trusted and broadly accepted as legal tender. 

By contrast, CBDCs are digital assets issued backed by a nation’s monetary authority, or central bank. A CBDC is a digital form of fiat money (or government-decreed currency) which shares the essential properties of a nation’s cash: the same denominations, values, liquidity, and stability; the same financial liability to the central bank; and the same applicability for any type of payment—extending the functionality of the country’s currency. CBDCs remain interoperable with existing financial structures and are reliably overseen by the central bank. 

Initially intended for use in wholesale banking with the prospect of extending to the retail banking system, CBDCs offer compelling benefits as compared to cash and current digital financial tools. These benefits include: 

• Streamlined cross-border payments enabled by reduced reliance on intermediaries, with benefits in lower transaction costs and improved transparency in international transactions. 
• Integrated smart contracts (basically, self-executing contracts with terms of an agreement written into code), which can automate and enforce terms. These provide a high level of efficiency and precision and offer composability (the ability to create and combine modular services and products across complex systems). 
• Liquidity and settlement finality. CBDC assets can be readily converted into other forms of money or assets, which facilitates a seamless flow and instantaneous settlement without delay or risk of reversal. 
• More accessible government-to-person payments, such as tax refunds or stimulus funds, with direct deposits into digital wallets that don’t require bank accounts. 
• New formats for payments and transfers, which are enabled through efficient processes that are usually not feasible with traditional payment systems (for example, by means of crypto wallets.)
• Financial inclusion through easier access to financial services, particularly for unbanked populations in developing countries, such as through offline payments. 

For these and other reasons, CBDCs hold enormous market potential. The annual value of transactions involving CBDCs is projected to reach USD213 billion by 2030, a remarkable growth rate of over 260,000% in just seven years.²  

The Drex project: How Microsoft is working with the Brazilian Central Bank 

In their earliest iterations, CBDCs are being introduced into national and regional economies in limited circulation, offered alongside cash as an equivalent monetary option, with the possibility of becoming more broadly circulated as they become more popular and accepted. Currently, more than 130 countries are exploring or developing CBDC initiatives, with varying degrees of maturity. Progress in the United States is nascent, while China has the world’s largest pilot in the world, with 260 million digital wallets.³  

Brazil is one of the earliest nations to pilot CBDC as it moves to build a more modern digital economy. Microsoft and our partners are working with Banco Central do Brasil (BCB) and commercial banks to help develop a solution for its CBDC, known as Drex.⁴ It will be one of the most advanced CBDC initiatives in the world. 

Drex is designed to help advance and democratize the nation’s economy by broadening access to intelligent financial services with greater ease and lower costs. A key feature is tokenization—creating digital representations of financial assets—which opens the door to many new options for trading and transactions. Tokens are managed on a distributed ledger technology (DLT) to ensure a secure, shared, and decentralized environment for transactions. This can make financial services more programmable, standardized, and secure, while ensuring optimal privacy.  

Drex could also be integrated into Brazil’s fast payment system, called PIX, which allows for quick and efficient transactions, and even with the global payments network SWIFT. Longer term, it also aligns with the innovative Finternet framework and Unified Ledger concept proposed by the Bank for International Settlements (BIS) to transform the global financial system. 

Empowering economies with CBDC initiatives worldwide 

The Drex project is a long-term effort that entered the second phase of its development in June 2024, which will continue for another 14 months with extensive privacy testing and new use cases. Ensuring the privacy and security of CBDC transactions is critical, so Microsoft and our partners, BCB, commercial banks,⁵ and other interested parties are working together to meet emerging requirements and ensure appropriate safeguards. 

Elsewhere, Microsoft is engaged in early CBDC initiatives in nations around the world. For example, we’re members of the Ensemble Project proposed by the Hong Kong Monetary Authority (HKMA), which aims to develop a set of industry standards to support interoperability among wholesale CBDCs, tokenized money, and tokenized assets.⁶ 

Microsoft is uniquely positioned to empower a CBDC project like Drex in several critical ways: 

• Infrastructure support: The Microsoft Azure platform provides robust infrastructure, AI services, and enterprise security—combined with our deep expertise with blockchain and other technologies critical for the design and implementation of a secure, scalable, and interoperable CBDC platform. 
• Privacy and security: Azure provides a broad catalog of security services that can be used as perimeters protecting CBDCs, with innovations such as a Zero-Knowledge Proof (ZKP) solution (called ZKP Nova) to help ensure privacy for digital assets. Additionally, Microsoft Azure Managed Confidential Consortium Framework (CCF) provides features to assure customers that data is inaccessible to unauthorized third parties including cloud service providers.  
• AI innovation: Generative AI copilots, for example, can help create smart contracts, analyze document inputs, write code, and identify vulnerabilities and risks. 
• Global reach and availability: Azure has a global network of datacenters, which enables central banks to deploy CBDC solutions in proximity to their users—reducing latency and ensuring high availability.  
• Robust partner ecosystem: Innovation in CBDC solutions is spearheaded by Microsoft’s vibrant global network of partners and developers, who can provide central banks with access to expertise, best practices, and pre-built solutions, such as a CBDC sandbox. 

Explore the possibilities of CBDC with Microsoft 

Microsoft is excited to share our insights and expertise on CBDCs with nations and commercial banks across the global financial ecosystem. For more details on Microsoft’s work on the Drex project and our participation in FEBRABAN TECH 2024 in São Paulo, Brazil, see our press release.

Learn more about Microsoft Cloud for Financial Services.

¹When – and why – did people first start using money? The Conversation.

²Jupiter Research, CBDC Transactions to Exceed $213bn by 2030, as Pilots Accelerate Rapidly, August 2023.

³ The Central Bank Digital Currency Tracker, The Atlantic Council.

⁴See Drex – Digital Brazilian Real (bcb.gov.br) and Piloto Drex (bcb.gov.br).

⁵Microsoft, CONSÓRCIO CAIXA, ELO E MICROSOFT REALIZA A 1ª COMPRA DE TÍTULOS PÚBLICOS POR MEIO DO DREX EM LEILÃO DO TESOURO NACIONAL, October 2023.

⁶Hong Kong Monetary Authority – HKMA establishes the Project Ensemble Architecture Community.

The post Central bank digital currencies: Accelerating a digital economy with advanced technology appeared first on Microsoft Industry Blogs.

Transacting through our marketplace connects you to thousands of pre-vetted Microsoft partner solutions, enabling you to rapidly accelerate your AI transformation and drive business outcomes. Whether that’s helping to enrich employee experiences, reinvent customer engagement or reshape business processes.  

It also represents smart spend. To move at the speed of business today, many companies prefer buying to building cloud apps, handing off the associated costs and management to SaaS partners while provisioning end-to-end solutions quickly and reliably. 

In this series of four blogs, we’ll dive into some exciting new AI-powered software solutions and how they can benefit your business. Here’s a taste of what follows.

Decision intelligence for service operations 

Imagine if every decision that service operations teams make were consistently more accurate, timely and planned for. That’s countless micro-gains every minute of the day – at your fingertips. Delivering “decision intelligence” for service operations in banks, insurance companies and healthcare providers,

ActiveOps’ blend of AI and human intelligence delivers the most complete and useful set of predictive and prescriptive insight to help make better decisions at the right time – resulting in over 20% more capacity, over 30% boost in productivity, and significant business impact, quickly. 

Find ActiveOps ControliQ on the marketplace

Guarding against cyber disruption, 24/7 

Darktrace offers global leadership in cybersecurity AI. Rather than study attacks, Darktrace DETECT’s “Self-Learning AI” technology continuously learns about your organisation, inside and out, and applies that understanding to optimise your state of cybersecurity. Darktrace is fuelling a continuous end-to-end security capability that can autonomously spot and respond to novel in-progress threats within seconds.

Find Darktrace DETECT on the marketplace

Read Blog 2: Safeguard your business with AI-powered security solutions 

Harness emerging Causal AI to go beyond prediction 

Causal AI is a new class of machine intelligence that overcomes many of the issues seen with traditional machine learning and AI. Using Causal AI models, organisations can now go beyond making predictions to answer “what-if?” questions.  

causaLens is the only company to have productised Causal AI through its decisionOS solution – enabling customers to optimise pricing and promotions strategies, fine-tune the marketing mix, anticipate and pre-empt customer churn, and much more. decisionOS is available via the Microsoft marketplace.

Find causaLens decisionOS on the marketplace

Read Blog 3: Optimise business operations through AI-powered solutions 

Delivering outstanding people processes 

Zellis is the largest provider of payroll and HR software, and managed services, to companies in the UK & Ireland. Built on Microsoft Azure, Zellis HCM Cloud connects into PowerBI for analytics, and Power Automate to create integrated solutions for payroll, HR, benefits, and recognition – driving efficiencies and staff satisfaction across your entire organisation.

Find Zellis HCM Cloud on the marketplace

Read Blog 4: Deliver transformational employee experiences through AI-empowering solutions

Empowering smooth operations from start to finish 

Innovation is thriving across sectors such as banking, finance and insurance, with support from the Microsoft cloud. Enate helps large enterprises to better manage end-to-end workflow smoothly, harnessing the power of automation and AI.

Powered by the Microsoft Azure OpenAI Service, EnateAI saves Operations teams from having to buy, train and test costly AI MLops solutions from third-party vendors. Instead, just “switch on” EnateAI to extract data from documents, categorise and automate email processing, and understand your customers’ sentiments, driving efficiency and cost savings straightaway.

Find Enate solutions on the marketplace

Making smarter decisions, faster 

Imagine building your own AI-powered data extraction models with no data scientists required. That’s AI with real ROI, a solution offered by Eigen that reduces the amount of time your organisation spends on manual processes by up to 90%.  

Eigen’s no-code AI platform automates the extraction, classification, and understanding of data from any kind of document, so customers can make faster, smarter decisions. Leveraging Microsoft capabilities, Eigen’s software integrates multiple AI technologies, including natural language processing, machine learning, and computer vision.  Building a model requires only a small number of training documents, which means business users can start automating their document workflows quickly. 

Find Eigen solutions on the marketplace

Using AI to make working capital more accessible 

Trade Ledger’s mission is helping every business get the capital they need to thrive, through enabling banks and alternative lenders to simplify complex business lending. Using Large Language Models, finance professionals can query their business systems using natural language and get rich analysis and insights into their working-capital needs. AI matches their funding needs with appropriate lending products; once a product is selected, it performs the loan application process.  

By integrating AI, Trade Ledger bridges the gap between what businesses need and what lenders have on offer. It also speeds the application and decision-making process, contributing to a more accessible and transparent working-capital market. 

Find Trade Ledger solutions on the marketplace

Reimagining trade transactions 

Meanwhile, Traydstream – a trade finance document-checking automation and digitisation platform – has partnered with Microsoft Azure to reimagine the paper-based processes that support trade finance. Available on the Microsoft marketplace, Traydstream uses a machine learning-based engine, slashing the time to complete checks on the dozens of documents and over 400,000 rules-permutations generated by a single transaction. Traydstream is now collaborating with Citi to provide their clients with access to this cutting-edge and automated trade-document processing capability. 

Find Traydstream solutions on the marketplace

Start your AI transformation journey today  

Whether it’s safeguarding your organisation and data, amplifying human ingenuity or delivering transformational customer experiences, buying cloud-driven AI software solutions through the global marketplace allows your business to be more innovative, agile and resilient, with less complexity, time and cost. 

That’s because the Microsoft marketplace offers the most comprehensive catalogue of certified cloud solutions anywhere. We’ve made procurement simple, enabling you to complete your entire journey in one place, with straightforward invoicing.

Your organisation’s existing Azure cloud commitment means you can benefit from faster time-to-value, integrating solutions that work with your current technology. In addition, software/IP costs incurred by buying solutions contribute 100% off your Azure Marketplace invoice. You can also rest assured that you’re buying and running solutions on a trusted cloud that boasts industry-leading security. 

We hope you enjoy the other blogs in our series. Meanwhile, why not check out more solutions on the Azure Marketplace? For more information and partner introductions, contact our ISV team.

Other blogs in this series

Blog 2: Safeguarding your business with AI-powered security solutions 

Blog 3: Optimising business operations through AI-powered solutions 

Blog 4: Deliver transformational employee experiences through AI-empowering solutions

The post Driving AI transformation with the Microsoft commercial marketplace appeared first on Microsoft Industry Blogs.

Helping banks improve productivity through better teamwork, insights, and communications is a key focus area for Microsoft, and something Azure OpenAI Service and our rapidly evolving copilot offerings are well positioned to enable. Additionally, Microsoft Cloud for Financial Services provides a strong industry-specific platform and data model built for greater industry relevancy. Many of our banking customers are energized by these products and are exploring use cases and other innovations.

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Paying down the digital debt for banking employees

Banking employees continue to get bombarded with data, applications, messaging, devices, and communications channels. We call this gap between the volume of data and the ability to process it the digital debt. Every minute spent paying this debt down is a minute not spent on more productive or creative work.

This is where banking leaders and employees are interested in generative AI—specifically, its promise of dramatically improving the employee experience by automating mundane tasks, summarizing and comparing data sets, recommending key actions, and providing real-time insights.

The goal of copilot is to empower everyone to achieve more and to assist humans in being more productive and creative in their roles. And the proof is already being realized: In a recent Work Trend Special Report, 70% of Microsoft Copilot users reported being more productive, 29% were faster with searching, writing, and summarizing, and 68% said it improved the quality of their work.

These benefits are now readily available to banks, thanks to Azure OpenAI Service, Copilot for Microsoft 365, Copilot for Dynamics 365, and other Microsoft Copilot capabilities that make it easy to build new generative AI solutions for high-value use cases.

Improving the employee experience from the front line to the back office

Generative AI promises to advance productivity in banking and financial service firms by integrating powerful insights into daily tasks, summarizing documents and meetings, digesting and distilling content from myriad sources, and creating new, high-quality reports, presentations, images, and much more. The implications span every level of the business, and the innovation will ultimately impact every employee.

Let’s take a look at how workers in three different levels of a bank can be more productive though traditional productivity applications combined with generative AI.

The relationship manager: Delivering customer satisfaction to drive revenue

The relationship manager is often the face of the bank to the customer. This role drives revenue and wallet share for the bank by building trusted relationships and providing superior insights and relevant products to the customer. Relationship managers can use Copilot for Microsoft 365 to automate administrative tasks, instantly draft emails to customers, and even suggest customized replies to customer inquiries or requests for proposals. Copilots can also help prioritize daily follow-up actions, streamline preparations for customer meetings, or recap action items post-meeting. Relationship managers can also use Microsoft Copilot for Sales to improve sales productivity by pulling in key account details from customer relationship management (CRM) systems or instantly generating product comparisons, and instantly drafting new proposals.

The wealth manager: Making superior financial recommendations

Wealth managers and investment bankers need market insights that lead to better financial decisions for clients. This requires optimal access to data—from knowing the client to keeping abreast of market changes—and strong customer engagement.

Wealth managers can use copilots in Outlook and PowerPoint to communicate more effectively. Microsoft Fabric and Copilot for Power BI can instantly pull together multiple data sources, do complex financial analysis, identify key trends and patterns, and then optimize client portfolios. Copilot in Outlook can triage, identify, and summarize the most important messages, then instantly create client replies based on existing email threads and key points. Copilot in PowerPoint can be used to rapidly create new slides from existing sources, add speaker notes based on existing slides, or instantly create a visual rendering of a concept or idea.

The compliance officer: Protecting the bank by minimizing risk

The compliance officer needs to ensure security, privacy, and control of customer and financial data. Communication and collaboration are key, as the role touches critical functions across the bank, and reporting to management is a major responsibility.

Compliance officers are becoming more productive with copilots in Microsoft 365 and Microsoft Teams that speed a wide range of writing and reporting tasks, augmented with tools such as data loss prevention and rights management. Compliance officers can use Copilot in Microsoft Teams to avoid meeting conflicts for diverse cross-group virtual teams, and recap key action items for people who can’t attend meetings. Compliance officers can use copilots to summarize comments from coworkers, list outstanding actions, and even include missing citations. They can use copilots to instantly create an executive summary at the top of a new document or generate an internal FAQ based on the Word document. And, when needed, they can use Microsoft Purview eDiscovery to make the content more discoverable across communications (email and video) and documents.

Empowering the banking industry to achieve more

Many banks regard the advent of generative AI with a mix of excitement and trepidation, which is only to be expected with such seminal new technology. We and our highly capable partners help banks begin their generative AI journeys by identifying discernable use cases that can be developed, then working iteratively to discover what works best. Typically, this includes the contributions of Microsoft partners from across our global ecosystem, who are experts in Microsoft technology and generative AI, and who can help identify strong use cases and determine the best path forward for implementing solutions that meet their needs.

Together with our partners, Microsoft is dedicated to helping banks take full advantage of generative AI by partnering for the long term. Trust, security, and compliance are the cornerstones of our value proposition to banking customers and we are committed to the advancement of responsible AI, driven by ethical principles.

To learn more about how banks and financial services firms can unlock business value, deepen customer relationships, and manage risk with AI and the Microsoft Cloud, read the “Empowering Your Banking Employees to Thrive” e-book, visit the Microsoft Cloud for Financial Services website, or get in touch with your Microsoft sales representative or Microsoft partner.

The post Empower the banking employee experience with generative AI appeared first on Microsoft Industry Blogs.

Microsoft Cloud for Financial Services is unlocking new value for customers and helping partners deepen customer relationships. At Sibos 2023, we were proud to highlight the work of independent software vendors (ISVs), including Finastra, Intellect Global Transaction Banking (iGTB), LSEG, Symphony AI, Temenos, Trade Ledger, Traydstream, VeriPark, and Zafin, as well as global systems integrators (GSIs) like Accenture–Avanade and PwC. Each of these partners has done amazing work to create, implement, and enhance solutions tailored to the requirements and needs of financial services organizations.  

Microsoft Cloud for Financial Services

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Partners on the cutting edge of generative AI

This year, groundbreaking generative AI projects from our partners are proving the value of investing in new solutions.  

To explore new opportunities for payments, iGTB has showcased how they extract transactional insights from payment flows, opening up new horizons for the industry. In the complex domain of trade finance, Traydstream is addressing complexities head-on through the digitization and automation of trade processing, seamlessly integrating Microsoft technologies with their AI-powered platform. Finastra is modernizing its trade platform through a full microservices architecture using Microsoft Azure, that will give banks increased agility, flexibility, and scalability, enabling them to continue to provide service excellence to customers throughout their modernization journey.

In the realms of financial risk and crime, Symphony AI, ASC Technologies, and Temenos are forging innovative solutions to enhance security. Temenos, specifically, is combatting money laundering while facilitating secure international payments. Symphony AI is using generative AI to power-up investigative processes and teams. And Trade Ledger is using generative AI to create new channels for commercial banks and support working capital management decision making across small and medium-sized businesses. 

Amid the array of innovations showcased at this year’s event, we also presented demonstrations of an integrated copilot experience tailored for asset management. This new user journey spans analytics, workplace services, and data intelligence, offering a comprehensive and dynamic experience.

Our partner ecosystem continues to grow

The partner ecosystem for Microsoft Cloud for Financial Services continues to grow and evolve with continued innovation with Microsoft technologies. As applications of AI capabilities rapidly expand, our financial services partners are finding new ways to build customer trust with responsible AI, meet customer demands, offer transparency, and deliver groundbreaking solutions that drive industry best practices forward.  

“Customers are eager to transform their trade finance and supply chain offerings, and to access the latest innovations, working with partners across the ecosystem. Partnering with Microsoft builds on our joint strategic vision to help accelerate the digital transformation of financial services, and support customers on their journeys.”

—Isabel Fernandez, Executive Vice President for Lending at Finastra.

Through powerful partnerships, organizations can bring innovations to their customers, faster than ever.  

And at iGTB, Chief Executive Officer Manish Maakan says that, together with Microsoft, they are “piloting a roadmap that unlocks the potential [of] artificial intelligence in financial services and seeks to showcase the transformative capabilities of Microsoft Azure OpenAI Service in the commercial banking space.”  

According to Craig Ramsey, Head of Real-Time Payments at ACI Worldwide, “By hosting ACI’s Real-Time Payments Cloud in Microsoft Azure, financial institutions will now have access to an award-winning, end-to-end solution to enable their processing of 24/7 payments.” This provides simplicity of operations and promotes interoperability. 

Make the most of Microsoft Cloud for Financial Services

Discover the optimal technology solution for your organization through our array of ISV, system integrator (SI), and advisory partners.

Our financial services partner ecosystem remains dedicated to empowering our customers, enabling them to provide exceptional customer experiences, streamline their operations, and explore new avenues for growth. Our commitment includes ongoing investments in flexibility and extensibility within Microsoft Cloud for Financial Services, fostering the expansion of our partner network.

To continue providing the capabilities our partners need, Microsoft announced a set of new solution partner designations under the Microsoft AI Cloud Partner Program (MAICPP) at Microsoft Inspire 2023. These designations certify that our partner solutions are optimally built on Microsoft Industry Clouds to deliver their solutions.

We eagerly anticipate announcing more ISV partner solutions in the coming months as part of this program. We look forward to welcoming our industry partners.

New possibilities are always emerging

As financial institutions embrace cloud technology, they unlock numerous benefits. This includes harnessing standardized data models for innovative business paradigms, customer-centric experiences, and future growth. They also explore AI integration with confidence in Microsoft Cloud’s secure solutions.

In this AI-driven era, we’re deeply committed to advancing together with our partner community. We’ll build on innovations, work closely with financial services partners to identify use cases, and explore generative AI and large language models (LLMs). Microsoft Cloud for Financial Services partners can create novel solutions and elevate existing ones, leveraging the Microsoft Cloud platform. This collaborative effort is about more than just business; it’s about empowering our end customers to achieve a smarter, more interconnected future in financial services—delivering distinctive and exceptional value.

For more inspiring partner news and engagement opportunities, look for Microsoft and our partners at Money 20/20 and InsureTech Connect (ITC), where you can go deeper into AI innovations built on Azure OpenAI Service and our copilot offerings. 

Learn more

• Visit Microsoft Cloud for Financial Services.
• Review Microsoft Cloud for Financial Services partner assets.

The post Shaping the future of financial services: Microsoft partners at Sibos 2023 appeared first on Microsoft Industry Blogs.

With Microsoft Cloud for Financial Services, our customers are managing financial services data at scale and building solutions that improve customer experiences and operational efficiencies. With the advent of generative AI capabilities in Azure OpenAI Service, businesses can now unlock new value from their data not only to drive better customer outcomes but also to improve their protection against various kinds of financial crime—including fraud, electronic crime, and money laundering.

The financial costs and scale of these crimes are staggering. Worldwide, the estimated total of laundered money in a year is at least two percent of global gross domestic product, or USD800 billion.¹ For financial services organizations, the cost of financial crime compliance reached USD213.9 billion in 2021²—USD56.7 billion in Canada and the United States alone in 2022,³ a 13.6 percent increase from 2021.

Until recently, financial services organizations have felt hamstrung in their ability to combat the worst forms of criminal activity. They play a cat-and-mouse game with bad actors who use a wide variety of financial instruments in sophisticated ways, exploiting the distributed nature of the financial system to perpetrate their crimes. Criminals might, for example, engage in small transactions across many different institutions, or across different accounts in the same financial institution, to mask their activities.

Protecting privacy while advancing security

The global focus on digital privacy in an increasingly interconnected world is a cornerstone of trust, human rights, and individual empowerment. Privacy is mandated by legislation around the world, such as the Digital Charter Implementation Act 2022 in Canada and in the European Union’s General Data Protection Regulation. And of course, banks and other financial services firms also know that customers will vote with their feet if their data is leaked or mishandled.

At its core, privacy is about protecting personal information. And this poses some challenges in fighting financial crime, because it impairs organizations from knitting together a complete picture of what an individual bad actor or a group of bad actors may be doing. The keys are all there in transaction records, account information, customer relationship databases, and so on. But they remain off limits when they are associated with personally identifiable information.

Fortunately, businesses can now attack the problem using novel technologies such as confidential computing and AI that allow multiple parties to safely gain insights from financial data without violating privacy requirements.

Confidential computing and de-identification: New layers of protection

A host of modern, cloud-based capabilities and methods enables this shift. For one, data can be better protected in the cloud with solutions like Azure confidential computing. This unique service encrypts data while it’s being processed, meaning that data is no longer only protected at rest and in transit, but also in use. While in memory, it simply cannot be accessed by cloud operators, malicious administrators, or even privileged software such as a hypervisor.

The root of trust in Azure confidential computing resides in independent hardware. Not even Microsoft operators can access the encryption keys. This is what enables government customers to independently, cryptographically verify the identity and “known good state” of the cloud operating environment they are relying on.

Concurrently, regulators are beginning to recognize the impact of new techniques for de-identification, which obfuscates or removes personally identifiable information from data sets. Data masking, data perturbation, and differential privacy are some of the powerful tools and methods of de-identification that are proving their effectiveness by making data available to AI to deliver important insights without putting privacy at risk.

While securing the benefits of strong privacy protections, financial services organizations are now able to work across enterprise data sets—to reason over data from not just one location, but across different locations and potentially even different institutions. This dramatically changes how a firm handles data. Swift is just one recent example of a financial services firm that has benefited from these innovations in building an anomaly detection model for transactional data without copying or moving data from secure locations. And, significantly, it means that AI and related tools and technologies will now be able to explore, analyze, and spot trends and insights that not only help their businesses, but can have positive societal impact as well.

How AI helps financial services organizations

With AI, financial services firms have new capabilities for risk assessment and scoring, which can help prioritize investigations and resources. They can also benefit from pattern recognition, which can detect anomalies and suspicious activities across large sets of financial transactions, customer data, and other sources. This has significant implications for fraud management, which financial services organizations rely on to mitigate their risks. If a firm can show new levels of due diligence, underwriting costs can potentially be reduced.

Additionally, generative AI can be used to analyze a wide array of unstructured data from a variety of internal repositories to spot indicators of potentially suspicious activities. Natural language processing will assist in the delivery of regulatory documents, legal texts, and compliance reports. And financial institutions may realize broad organizational benefits through integration into productivity applications. At Microsoft, we’re all about democratizing AI and making these tools approachable and available not simply to the data analysts and mathematicians, but to people across the business. This is reflected in the broad innovations announced recently at Microsoft Build 2023, in which we have integrated AI into Azure, Microsoft 365, our development tools, and much more. These AI-powered products help surface more useful information for better decision-making and greater efficiencies across the organization.

The art of the possible

In our work with customers, we see a wave of interest in exploring the potential of these powerful new tools to fight fraud, money laundering, and other forms of financial crime. In Canada, privacy enhancing capabilities have long been bolstered by affirmation from the Information and Privacy Commissioner of Ontario that de-identification is a legitimate and valuable way to protect information, and enterprises have been provided with guidance on how to proceed. It’s powerful confirmation that organizations can leverage new approaches to address privacy considerations as they explore new opportunities. Once we light up the art of the possible, the dialogue quickly shifts and we can work collaboratively to solve these tough challenges.

Fight financial crime with the Microsoft Cloud

Collaboration is the key to industry-wide progress in the fight against all kinds of financial crime and fraud. Working well together is a core Microsoft value, and that means much more than ensuring that our products and tool sets are integrated. It means that we recognize that these challenges are bigger than us or any one company, organization, or entity. So, we promote and support the roles that every player in the ecosystem performs, from industry partners to government officials, regulators, law enforcement agencies, and of course customers.

For financial services organizations who want to explore these new possibilities, an exploratory engagement or proof-of-concept is a good way to examine how the technology and process puzzle pieces fit together. We’re constantly amazed at the inventive and impactful ways that customers are employing these tools to do better for their organizations and the world at large.

Read further in a recent post about how the Microsoft Cloud helps banks manage risk and discover real-world customer examples and other resources that show how Microsoft and our global partners can help banks deepen risk insights, facilitate regulatory compliance, and combat financial crime.

¹24 Alarming Money Laundering Statistics [New Data 2022 & Infographic], BusinessDIT.

²Global spend on financial crime compliance at financial institutions reaches $213.9 billion, Finextra.

³True Cost of Finacial Crime Compliance Study for the United States an Canada, LexisNexis Risk Solutions.

The post Combat financial crime with AI and advanced technology from Microsoft appeared first on Microsoft Industry Blogs.

For the people and teams responsible for managing risk and ensuring compliance, however, this paradigm shift comes with some new anxiety, as stringent security and compliance requirements must be met. While on-premises risk assessments and audit strategies may have been straightforward in a pre-cloud world, when data moves to a third-party cloud provider operating a shared environment at hyperscale, the lines shift. Security and access controls are automated, DevSecOps becomes more commonplace, knowledge gaps arise, and the regulatory context is changed drastically. Adding to the pressure, if compliance assessments and audits are disrupted, innovation can grind to a halt.

Fortunately, there are some excellent resources to guide you productively on this journey. Microsoft makes a significant investment to help customers get the assistance they need to optimize cloud risk assessments at scale. In this post, I’d like to share some of the learning we’ve gained through our deep engagements with customers, point you to a few Microsoft online gold mines, and invite you to check out our Compliance Program for Microsoft Cloud, which I think you’ll love.

Three road-tested strategies for governing cloud risks

Through our compliance community, we get an amazing stream of insights, feedback, and stories about what does and does not work. Here are three strategies that we see at the heart of every organization that successfully governs cloud risks:

1. Establish a cloud risk governance body. Risk organizations are complex, and siloed approaches are likely to hit walls when different risk stakeholders across all three lines of defense each make their own assessment of a cloud service provider. We often see problems with a poor understanding of cloud technologies and risk controls. Inefficiencies tend to spring up as questions are raised repeatedly by different stakeholders (“Where is my data stored?” or “Who can access it?”). Many problems can be solved or prevented through a unified cloud risk assessment approach. We advise setting up a cloud risk governance board or body that engages all key functions in a single, integrated process that leads to faster deployments and addresses resource constraints and skills gaps.
2. Adhere to common standards and apply risk-based approaches. Not every use case is the same, yet too often we see customers apply an extremely large set of mandatory controls to any and every cloud use case, irrespective of its significance. Moreover, cloud providers apply different risk control measures compared to what might be expected on-premises, and that can lead to endless control discussions. A good way to prevent these challenges is to align internal control frameworks to industry standards, such as SOC 2 and Cloud Security Alliance’s Cloud Controls Matrix (CCM). This approach gives you structure and guidance for implementing appropriate controls that can be applied in risk-based ways to individual use cases, each time aligned to your organization’s risk, security, and compliance requirements.
3. Take maximal advantage of third-party assurance. Another pitfall is that some financial institutions will try to evaluate or audit every cloud control independently. This is a waste of time because there are already certifications and audit reports available where multiple reputable third parties have attested to the soundness and safety of these same controls and related risk areas. These should not be ignored. Microsoft is a leader in compliance and offers a very extensive compliance offering for Azure, Dynamics 365, and Microsoft 365 with more than 100 certifications and attestations.

Our framework for assessment in the cloud

Once these foundations are established, you can execute cloud risk assessments across these six basic dimensions:

You can now achieve a cloud-optimized risk assessment process that drives maximum efficiency as you cycle through different use cases. Critically, this process will remain resilient as the enterprise gradually deploys more business functions onto Microsoft Cloud, each of which will require a contextual assessment of risks.

How to take advantage of Microsoft Cloud risk and audit resources

Microsoft understands the critical need for financial services risk, compliance, and audit teams to be well supported with tools and resources that empower them to fully understand and assess cloud-related risks.

To explain how we operate our cloud and help customers through their risk assessments and audits, we have created a one-stop shop describing Microsoft compliance that points to our compliance offerings. This includes a service assurance section that describes in great detail how we operate our Microsoft Cloud services, which is a great starting point for risk and audit functions to start their assessments. The service assurance section is organized by 14 risk domains and describes in detail how Microsoft works to secure our customer data. It includes on-demand learning paths available for customers to learn at their own pace.

A second excellent resource is our Service Trust Portal, where you can download external audit reports, useful whitepapers, and artifacts such as third-party vulnerability reports, business continuity, and disaster recovery plan validation reports. You’ll also find detailed regional financial services regulatory compliance checklists which can be used to meet regulatory requirements in each country.

Next, Microsoft Purview Compliance Manager is a unique tool that allows you to get to the next level and manage risk and compliance not just from the Microsoft side but also for your multi-cloud deployments, ensuring that your configurations meet all regulatory requirements as well as cybersecurity and privacy best practices. You’ll find more than 320 compliance assessments aligned to various industries and regions across the globe. You can double-click into each control and review detailed information—including Microsoft control implementations—and how each control was tested by external auditors and the results.

Don’t forget that cloud involves a shared responsibility, and after successfully having assessed Microsoft as your provider you also must ensure your deployments are compliant by default and optimally secure. The good news is that this is all integrated into service assurance as a starting point following the same risk-based structure.

Need the best? Check out the Compliance Program for Microsoft Cloud

The Compliance Program for Microsoft Cloud is a premium “white glove” service specifically created to support risk and compliance professionals through their assessments. This program originated 10 years ago when the first financial services organizations started to embrace the cloud, and it facilitates three-way engagements among customers, regulators, and Microsoft experts. The program continues to evolve, and it gives customers direct access to legal, cybersecurity, privacy, risk, and regulatory compliance experts both from within Microsoft and the industry as a whole.

Customers will receive the best answers to very specific questions and concerns and can submit entire questionnaires to accelerate risk assessment and audit activities. The program has tremendous educational value through webinars and global and regional compliance summits; offers opportunities to engage in a community with other customers and industry experts; and delivers proactive updates related to regulatory and compliance developments around the world.

Join the program today

The insights and tips in this article have largely been built on the experience of this community over the past years. If this resonates for you and your organization, I invite you to join the Compliance Program for Microsoft Cloud and connect with your peers today.

Learn more about Microsoft Cloud for Financial Services.

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The post 3 strategies for governing Microsoft Cloud risk in financial services appeared first on Microsoft Industry Blogs.

In the financial services industry, there has been greatly heightened interest in AI and the transformative opportunities of this new wave of breakthroughs. With the industry’s focus on managing risk and generating returns, generative AI has the potential to drive marked improvements in employee productivity, operational efficiency, and customer experience. In my current conversations with customers and partners, I’m asked how Microsoft can help businesses and organizations get started on the journey. This is especially true in banking, where technology is playing an increasingly decisive role in addressing a broad range of financial, regulatory, and competitive challenges. Generative AI has added a whole new dimension to what we mean by intelligent banking and the possibilities it creates to unlock greater innovation and business value at an accelerated pace.

Reimagine banking

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What generative AI means for banking

As generative AI capabilities become available to everyone, banks and other institutions will want to build intelligent solutions to provide revolutionary new capabilities—first with their employees and, over time, for their customers. Microsoft will help enable this with Microsoft 365 Copilot, which we announced last month. Integrated across Microsoft 365, this copilot will provide generative AI capabilities to the entire Microsoft productivity suite.

For banks that want to rapidly apply intelligence to improve operations and drive efficiencies, they can apply for access to Azure OpenAI Service to accelerate the deployment of their use cases. Azure OpenAI Service brings together advanced models from OpenAI, including ChatGPT and GPT-4, with the enterprise capabilities of Azure. Critically for banks, it is deployed on their Azure tenants so that all data—including training data and content—stays within the bounds of their organizations. By being fully integrated into Azure, banks also get all the advantages of enterprise-grade security and role-based access included. You also get the benefit of building on the Microsoft Cloud platform where we are infusing AI into all our products, making it easier to integrate these new capabilities into your applications. And it’s only getting better, as we recently announced the availability of GPT-4 in a preview release. GPT-4 is OpenAI’s most advanced LLM, enabling you to drive insights with greater accuracy than previous LLMs developed by OpenAI.

Azure OpenAI Service lets you deploy large, pre-trained, foundational models developed by OpenAI. This means you can potentially transform important tasks such as:

• Writing assistance and content generation.
• Reasoning over structured and unstructured data.
• Summarization of reports and text.

Use cases in banking

As we engage with our customers, we are seeing powerful new use cases emerge. For any scenario, we believe human agency and supervision are critical to ensure that generative AI is empowering and enabling human creativity. In our own products, we enable this through our copilots. The copilot is there to support you and work under your direction, with the human in charge. For example, GitHub Copilot provides code suggestions for developers as they enter code right inside the developer environment. In other situations, a chat-based experience will be a better fit when you are looking to embed knowledge search capabilities or a search bar to accept a prompt to generate some new content. Key banking use cases where generative AI can have the greatest impact include:

• Empowering contact center agents. Generative AI enables you to summarize conversations and get insights across various conversations. Customer sentiment can be measured from the start to the end of the conversation. In addition to summarization, generative AI can provide coaching to contact center staff in real-time, and partially automate the customer journey with human supervision of the next step. It can also feed new intelligence into the contact center knowledge base to enable agents to respond faster to future questions. For all these capabilities, we can aggregate insights for tracking key performance indicators (KPIs) for customer satisfaction, engagement, and impact to the Net Promoter Score (NPS), all of which can be used to continuously improve the experience for customers.
• Empowering advisors. Financial products have extensive documentation that can be difficult to search, making it a challenge to get to an answer quickly. In some scenarios, advisors are certified in their product knowledge. Many banks are exploring the opportunity for generative AI to help advisors retrieve the answers they need from financial product documentation. Generative AI makes it easier to do this through powerful summarization and contextualization capabilities. It can even summarize the key attributes of products in a comparison table. In addition to advisory roles, these enhanced knowledge search capabilities can be built once and used by multiple roles across the bank such as branch staff and contact center agents.
• Content generation. Banks are exploring how generative AI can accelerate the development of content such as pitch books. Pitch books are used by investment banks to generate a proposal for a capital raise or merger and acquisition for an institutional investor. Pitch books are developed collaboratively with content from multiple sources such as an overview of the client, the deal strategy, and marketing materials. For every content generation scenario, human oversight is critical to ensure the quality and accuracy of generated content.
• Code generation. GitHub Copilot was released last year, and developers can now take advantage of generative AI to provide code suggestions for dozens of programming languages, access application programming interfaces (APIs) faster, and accelerate software development. In March 2023, we announced the upcoming GitHub Copilot X, which is trained on GPT-4 and brings AI capabilities to the entire development lifecycle.

Responsible AI by design

As next-generation AI innovation gains momentum, we are optimistic about what it can do for people, industry, and society. Microsoft’s advancements in AI are grounded in our company mission to help every person and organization on the planet to achieve more. We’re committed to making the promise of AI real—and doing it responsibly. Our approach to AI is based on three principles: meaningful innovation, empowering people and organizations, and responsibility.

Accordingly, we’re dedicated to the responsible development of AI systems for the industry, ensuring they will function as intended and be used in ways that earn trust. We were one of the first major technology companies to call for thoughtful government regulation on facial recognition technology and are committed to creating responsible AI by design through our Responsible AI standard. For more information, see “What is Microsoft’s Approach to AI?“.

What’s next

Empowering our customers with intelligent banking capabilities is core to our mission, and we are excited to bring generative AI innovations to them through our Azure OpenAI Service and our copilot offerings. Additionally, we will work with our industry partners to enable them to take advantage of these same capabilities in their own solutions. I look forward to seeing what our customers and partners will create with generative AI in partnership with us. Together, we can apply the world’s most advanced AI models to meet business imperatives responsibly, securely, and with the confidence that can only be achieved with Microsoft Cloud.

Stay tuned for upcoming blog posts that will explore the possibilities of generative AI in the insurance and capital markets segments along with more guidance on responsible AI. We’re excited to help the financial services industry embrace this new era of AI and accelerate transformation.

Finally, learn more about the era of generative AI across the financial services industry by reading other posts in this series:

• The era of generative AI: Driving transformation in insurance

The post The era of generative AI: Driving transformation in banking appeared first on Microsoft Industry Blogs.

Clearly, finance is about data. Data is the connective tissue that brings context, value, and understanding of risks through its continuous, real-time flow. In financial services, as with other experiential industries, data is the pivot on which transformation is happening across all market segments, be they enterprise or consumer.

Becoming data-driven, however, is not just about technology or its cool tools. Rather, it entails a fundamental change in approach, particularly in traditional banks that have well-defined product silos with well-scripted domain experiences. In these institutions, being data-driven requires having a broader view of the bank’s role and potential, and the value it can bring to clients and the ecosystems that connect them. We might refer to this as intelligent banking.

Retail banking is a case in point. It seemed illogical that it would ever become a hotbed for data-centric change, given the well-entrenched consumer habits, data privacy concerns, and other mass-market challenges involved. Who knew that the ubiquitous adoption of smartphones by billions of people in a short period of time would facilitate such a wholesale transformation, with data as the prime driver of value?

For retail banks, the change came in the nick of time. The economics of their businesses were already under stress from a triple whammy of perpetually low-interest rates, consumer unwillingness to pay fees for routine services, and the high cost of brick-and-mortar operations. There was even doubt as to whether they could profitably serve multitudes of individual clients without a mass scale beyond that of most bank franchises. It was a perfect storm where the value of data insights saved the day.

Corporate banks observed this from a distance, seemingly immune from the forces of consumer adoption of mobile and the acceleration of e-commerce driven by COVID-19 shutdowns. Now, their staid world is fast approaching a similar inflection point.

Data: The key to commercial banking transformation

Cloud-native financial technology (fintech) has transformed retail banks by delivering appealing, low-friction customer experiences. They have also been savvy enough to anchor their business models around the value of data, for which the stock market has rewarded them with high valuations. Corporate banking, by contrast, involves a much richer palette of cross-industry data. Entire economies literally flow through business banking client accounts day in and day out.

Data is the heart and bloodstream of all working capital and contains an unparalleled richness of contextual information across all business-to-business ecosystems—such as those in manufacturing, logistical supply chains, and retail sales. These data flows are rich with insights and trend information that can be used, for example, to forecast cash flows that enable corporate treasurers to control enterprise risk and optimize operations. No longer will working capital be estimated through guesswork derived from spreadsheet manipulation. Rather, the role of a corporate treasurer will become more strategic in understanding the value of vast forests of data rather than the timber of individual trees.

Wholesale banking was the first to structure data flows around common standards beginning in the 1970s with the adoption of SWIFT messages. While that meant more efficiency in payment processing, it did not portend a fundamental shift in the use of messaging data to drive client value beyond rudimentary reconciliation services.

The new ISO 20022 standards, which are currently being adopted, hold the promise of redefining value-added services that banks can deliver through enriched, machine-readable extensible markup language (XML) formats. These new standards must be recognized as something more than expensive compliance projects. Rather, they hold the key to reimagining fundamental banking propositions. That much is self-evident. The question is where and how best to do it.

Where data and intelligence will drive new banking scenarios

As we have seen in recent financial crises, real-time flows move literally at the speed of light where counterparty risk analysis and decision-making need to be instantaneous. Similarly, dealing with fraud, crime detection, account takeovers, and money laundering all require a multifaceted view of data that only AI and machine learning can achieve. Anomaly detection in trade-based money laundering (TBML) is a typical example of a compliance challenge where banks are expected to decipher context and intent from subtle signals and telemetry. This degree of data analysis simply cannot be accomplished through manual operations. The volume is too heavy and the connections are too complex.

AI is also an essential tool for the modern and efficient operation of a bank. “Next best offer” is a typical use case of how surfacing the right data at the right time in client discussions can help achieve the best results for both the client and the bank. This is particularly true in modern banks where staff churn or the breadth of product portfolios is just too extensive for everyone to master the challenge of making the best suggestions all of the time.

Here, tools in the graph of a modern workplace—like Microsoft 365 and Dynamics 365 with Copilot-based suggestions—can be as empowering as they are powerful. In a regulated industry like banking, these tools are designed with security, privacy, compliance, and ethical considerations at their core while large language models (LLMs) make them easily relatable to real-world interactions. This is not the “data processing” of yore as we would have once imagined it.

The coming redefinition of banking

Banks, with their richness of real-time data flows, will evolve at the center of client relationships. No longer will a bank be a place to go simply for routine financial processes like making a payment. Rather, in the new world, banks become operating partners in achieving the outcomes their clients desire. AI-infused products, along with the agility that only cloud-based services can provide, will transform bank business models by adding data as a third economic dimension to the traditional two of accepting deposits and making loans in a spread business.

Learn more

In upcoming blog posts, we will continue to highlight the developments and opportunities we see in the evolution of banking. See our website for insights on how to reimagine banking and get in touch with your Microsoft representative or trusted partner to learn what our cloud can do for your business.

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