Consider, for example, that Americans who live past the age of 70 can expect on average to spend $172,000 for long-term care over their lifetimes.¹ But most families (as many as 83%²) say it would be impossible or very difficult to afford $60,000 for annual in-home or assisted living care expenses.

Life and health insurance companies are working to help bridge this ever-widening gap with long-term care insurance (LTCI). And thanks to a broad range of new innovations enabled by AI, Microsoft and our partners are helping to improve LTCI for policyholders and insurers alike. This is part of our vision for intelligent insurance and our work with Microsoft Cloud for Financial Services. 

In this case, helping to make long-term care more accessible and affordable is good not just for enhancing societal well-being and reducing the strain on public resources, but also for the viability of a critical insurance product.

The unique challenges of long-term care insurance

LTCI insures people for a very costly circumstance that is very likely to occur.

About 70% of seniors will require long-term care at some point in their lives,³ and Americans spend more than $471 billion annually for long-term care.⁴ Yet Medicaid covers only 42% of long-term costs. LTCI aims to address a significant portion of long-term care costs by covering a range of services for people who need assistance with daily living activities—for example, bathing, dressing, and eating—over an extended period, often provided at home.

Despite the prevalence and urgency of the need, however, LTCI has proven challenging for insurers. Rising healthcare costs and higher-than-expected claims have created unforeseen financial pressures. People are living longer, increasing the likelihood of needing to use LTCI, and fewer customers than expected are letting their policies lapse. For insurers, this results in profitability challenges and uncertainty, while customers face higher premiums, and thus reduced access.

How AI can help improve LTCI profitability and growth

The success of insurance companies in addressing the growing need for LTCI will depend on a variety of factors, including education, awareness, and the efficiency and effectiveness of regulation. Above all, technology holds the key for transformation in profitability and growth.

We are seeing tangible results in AI innovation with our insurance customers worldwide that have direct relevance for LTCI providers. These potential benefits are prompting many insurers to accelerate their cloud migration and data management investments—a transition that is key to the LTCI sector, which lags other insurance segments. With the scale, security, and resilience of the Microsoft Cloud combined with the advanced data and analytics capabilities of Microsoft Fabric and the AI development opportunities enabled by Azure AI Studio, insurance companies can innovate rapidly and confidently to meet their specific needs.

The future of insurance in the era of AI

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Here are some of the important benefits that insurers can apply to their LTCI offerings.

Enhance underwriting and claims management

AI can streamline underwriting and claims processing in ways that improve both accuracy and efficiency. One important area of focus is straight-through processing (STP)—the automation of an entire workflow, from the initial data entry to the final decision, without the need for human intervention. STP helps to reduce delays, minimize errors, and free up valuable human resources.

In the underwriting process, AI helps enable STP for tasks such as analyzing historical data, assessing risk factors, and predicting the likelihood of claims, which helps underwriters make more informed decisions and reduces the time required for manual reviews. It can also handle a larger volume of applications without a corresponding increase in resources.

In claims processing, STP can automate the assessment and triage of claims—for example, by quickly extracting and analyzing information from a wide range of documents, including medical records, policy applications, and claims forms. Many insurers have long used optical character recognition (OCR) technology to digitize these types of documents. But the addition of generative AI supercharges how they can be understood, evaluated, and acted upon.

Automate contact center experiences

With generative AI’s natural language processing and content creation capabilities, insurers can optimize contact center operations in ways that help both the customer and the company.

AI-enabled copilots and virtual assistants can handle larger volumes of routine inquiries, helping agents and customer service representatives provide faster, more accurate responses to policyholders’ questions about coverage, claims status, and more. For example, John Hancock implemented a new AI solution to provide support for common customer issues and questions, which helps call center representatives focus their efforts and expertise on the most complex cases, with better customer experiences and reduced wait times.

Automated systems can understand and respond to customer inquiries in a conversational way, and even authenticate caller identities with voice biometrics, streamlining the identification process and enhancing security. For LTCI, AI can enable corresponding benefits through more efficient operations, better resource allocation, and enhanced customer experiences.

Prevent fraud, waste, and abuse

In the realm of fraud detection, advanced analytics and AI-powered tools can analyze vast amounts of data from healthcare vendor invoices to identify patterns and anomalies indicative of fraudulent activities in a timely manner. With better insights, insurers can proactively detect and prevent fraud, helping ensure that legitimate claims are processed swiftly while minimizing financial losses.

AI can also help insurers identify unusual patterns or anomalies that could indicate fraudulent or wasteful activities, such as flagging a particular facility if it consistently submits higher-than-average claims for certain treatments. Analyzing historical data can also help inform insurers to create more robust, data-driven processes to determine which facilities to audit or to benchmark best-in-class operators.

Expedite regulatory, contracting, and auditing activities

LTCI is inundated with regulatory, contracting, and auditing activities, many of which rely on cumbersome manual processes. AI can improve the efficiency of many of these workflows while also improving accuracy, turn-around times, and regulatory compliance. Data validation, risk assessment, and regulatory monitoring can all benefit. Moreover, AI’s predictive analytics can spot potential compliance issues, and its enhanced reporting capabilities can aid strategic decision-making.

Advancing LTCI with AI and Microsoft

We believe that with focused, creative innovation with AI, LTCI providers and their customers can look forward to a bright future in which more people can live with dignity and financial security in their senior years, thanks to high-quality, robust insurance products and services. We are excited to work with industry and our global partner ecosystem to strengthen LTCI, in line with Microsoft’s responsible AI principles and our Secure Future Initiative. 

To learn more about all our solutions, visit our Microsoft Cloud for Financial Services website.

¹AARP, “Long-Term Care Costs May Double to $5.6 Trillion by 2047,” March 2018.

²KFF, “The Affordability of Long-Term Care and Support Services: Findings from a KFF Survey,” November 2023.

³Morningstar, “100 Must-Know Statistics About Long-Term Care: 2023 Edition,” March 2023.

⁴A Place for Mom, “Long-Term Care Statistics,” September 2023.

The post How AI is improving long-term care insurance for insurers and customers alike appeared first on Microsoft Industry Blogs.

It is no wonder then that AI is so appealing to leading insurers. Its amazing ability to glean insights from data, create documents, and enable people to build powerful solutions using natural language promises to help insurers meet the unprecedented demands of the moment. This is central to our vision for intelligent insurance and our work with Microsoft Cloud for Financial Services.  

Most of the insurance companies we talk to are seriously exploring generative AI. For many, however, the scope of the opportunity is so wide-ranging that it can be difficult to identify productive early steps. Fortunately, there is an option available today that can deliver clear near-term productivity benefits and also help lay the groundwork for a successful long-term AI journey. 

How Microsoft Copilot for Microsoft 365 can impact insurance 

Imagine two years ago if a vendor promised a solution that resulted in employees spending 64% less time on email or that resulted in 70% of employees self-reporting as more productive. What seemed unbelievable until very recently is the impact of Microsoft Copilot for Microsoft 365 just months after its introduction last year.  

Copilot for Microsoft 365 is a unique offering that integrates generative AI features into the Microsoft 365 applications that many employees use on a regular basis. In effect, it is a real-time, intelligent assistant built into Word, Excel, PowerPoint, Outlook, Microsoft Teams, and more, applying the power of large language models (LLMs) to an organization’s data to significantly reduce the time and energy required to perform an endless number of rote tasks.  

In November 2023, Microsoft surveyed 297 early adopters, across industries, to quantify the impact of Copilot for Microsoft 365. As detailed in the Work Trend Index Special Report, it delivered significant productivity gains among employees, with the promise of fostering broader organizational improvements over time. This is especially exciting for insurance companies, which have a wide range of roles that could benefit from this assistance. 

Copilot for Microsoft 365

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How Copilot for Microsoft 365 empowers six key roles in insurance 

On the one hand, insurers operate in a world of exacting processes, strict compliance, and regulatory considerations. On the other hand, competitiveness demands greater efficiencies, faster speed to market, and improved customer service. Copilot for Microsoft 365 addresses both dimensions. Among its many benefits, it helps employees easily find and navigate business data, analyze trends, and rapidly create insightful reports and documents, without requiring the company to build customized solutions for specific use cases.  

In our work with insurers, we have identified multiple ways that Copilot can assist in key roles across the business.  

1. The agent and broker, who markets, advises, sells, and services insurance coverage for policyholders, can use Copilot to: 

• Help customers understand their insurance options, with customer-specific reports and summaries of products written in plain language. 
• Provide prompt customer service, with a fast and accurate summary of a Teams meeting with a customer, including recommendations and actions.  
• Be more responsive to customers by generating customized emails in response to specific queries and needs. 

2. The claims employee, who handles claims from first point of contact to resolution, can: 

• Accelerate settlement discussions by drafting summarizations of claims content and meeting recaps.  
• Enable contact center employees to be more efficient when assisting policyholders when they first report a loss. 
• Summarize and annotate company policy, processes, and guidelines to expedite processing of claims. 

3. The underwriter, who assesses risk factors in providing insurance to customers, and helps to establish policy pricing, can: 

• Research multiple sources of data and insights in evaluating risk and pricing options.  
• Get instant access to guidelines and regulations relative to an application. 
• Summarize complex documents used throughout the underwriting process. 

4. The financial advisor, who provides insurance policies and annuities to clients based on their financial situation, can: 

• Combine insights such as changes in the market and client life events to inform and personalize financial planning discussions.  
• Manage accounts more efficiently by summarizing emails, chats, and meeting notes, and drafting presentations specific to the client based on existing documents and data. 
• Improve customer follow-up with emails that recap conversations and include draft proposals based on discussions. 

5. The leader or manager, who manages multifunctional teams in complex organizations, can: 

• Quickly create new business plans and update objectives and key results (OKRs) or key performance indicators (KPIs) based on existing documents and organizational inputs. 
• Gain new insights on product sales and industry trends based on myriad sources. 
• Quickly build presentations with discussion notes for specific leadership events.  

6. The contact center representative, who listens to customer needs and provides solutions through inbound and outbound calls, can:  

• Recap customer meetings and conversations. 
• Proactively identify issues, and draft recommendations or resolution messages, to distribute to targeted recipients or channels. 
• Measure sentiment and conversational trends associated with conversations or posts. 

Key considerations for successful adoption of Copilot for Microsoft 365

As with any promising new technology, realizing the full value of Copilot for Microsoft 365 adoption requires careful planning and implementation across the organization.  

There is no single roadmap for success. The key is to clearly define how Copilot will support business strategy. Some insurers choose to invest in a significant upgrade of their technical infrastructure. For example, global property and causality insurer Canopius migrated from dual datacenters to Microsoft Azure, determining that it would help meet their goals across international markets and set the stage for AI solutions, including Copilot for Microsoft 365. Other companies choose a more incremental approach based on their current cloud investments.  

From a technology perspective, AI innovation in insurance can only happen on a modern cloud platform that delivers hyperscale computing power with the requisite security and regulatory compliance attributes. Concurrently, you need a clear data strategy to ensure that all data made accessible to AI is properly protected by permissions and access controls, so that only the right people in the right roles can access sensitive information. Data governance and accountability structures are also essential. 

Then, it is important to recognize that readiness is as much a cultural challenge as a technical one. Employee training and support are essential costs that should not be shortchanged.  

Getting started with Copilot for Microsoft 365

For insurers considering adopting Copilot for Microsoft 365, our advice is to start with your Microsoft solutions partner and Microsoft representative and discuss developing a plan. We often advise companies to start small, and begin experimenting on a role-specific basis, in cases of specific friction or bottlenecks that copilots can immediately address. This helps you identify important issues and sets you up to experiment with broader scenarios and role types.  

But as previously noted, every AI journey is unique. The important thing is simply to begin. For a framework and supporting resources to help foster successful adoption of Copilot, see our Copilot Success Kit. For more on the impact of Copilot on business productivity and creativity, see the Work Trend Index Special Report. For a roadmap to create business value with AI, see The AI Strategy Roadmap.  

The post How Microsoft Copilot for Microsoft 365 is redefining insurance, one role at a time 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.

Back in June 2023, Sasha Sanyal, Microsoft Global Insurance Leader, blogged about the unprecedented excitement among insurance customers over the promise of generative AI. Customers were inspired by Microsoft’s vision for intelligent insurance and how the Microsoft Cloud and our global partner ecosystem were providing opportunities to build solutions that could not just deliver efficiencies but also create industry-changing competitive advantages.

Today, many visions are on their way to becoming powerful realities. The level of interest and creativity we’ve seen from insurance customers has been off the charts. Working alongside our partners, we have been more than busy brainstorming with business leaders and technology teams, hacking solution concepts, and collaborating with customers to build differentiating capabilities.

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Use cases help to drive AI innovation in insurance

Central to our exploratory engagements with insurance companies is the challenge of finding effective use cases—real-world scenarios that identify specific business problems and define how capabilities or features can be implemented to deliver measurable results in solving them. A good use case can serve as a north star to help in the design, development, and measurement of a solution. And because a use case is tight and distinct, it can help a customer make fast, efficient, and insightful early investments in experimenting with generative AI. Out of our customer deep-dives, a set of distinctive use cases has emerged that we recognize as especially worthwhile for insurance companies as they take their first important steps on their AI journeys.

Context is important here. Above all, insurers are anxious to use generative AI to transform their businesses in virtually every aspect of operations, customer engagement, and product innovation. They see, for example, the potential of content generation to write automatic responses to customer inquiries, of summarization to assist in producing support conversion logs or financial reports, of semantic search to enable fast information discovery and knowledge mining, and code generation to convert natural language to structured query language (SQL) (or vice versa) for telemetry data. This list barely scratches the surface of what’s possible.

Insurance customers are choosing Microsoft Cloud for Financial Services because it provides enormous flexibility and control in creating solutions based on an organization’s unique needs. For companies that want to build their own generative AI solutions, Microsoft Azure OpenAI Service brings together advanced models from OpenAI with the enterprise capabilities and advanced security of Microsoft Azure. AI is also being integrated into the Microsoft Cloud and in the Microsoft products that customers already use and love, including the upcoming Microsoft 365 Copilot, which will create and edit documents, presentations, and emails.

Top generative AI use cases for insurance companies

In considering options to deploy generative AI, insurers and other risk-sensitive companies are starting with use cases that can help them learn without creating risk for customers and clients. Where generative AI is being used to generate content, humans need to be in the loop to review output and ensure compliance. Still, these early-horizon requirements leave plenty of room for innovation in early deployments.

 Three categories of use cases are gaining traction with customers today:

1. Helping deliver meaningful and engaging customer experiences

Generative AI can have a tremendous impact in transforming each phase of the insurance customer journey.

• In the discovering and exploring phase, company agents can receive automatically generated notes and recommendations following a customer call, or produce tailored, auto-generated emails to follow up on issues or opportunities.
• In the buying and using phase, agents can generate scripts to drive conversations based on customer profiles and conversation histories.
• In the asking phase, agents can automate follow-up activities or retrieve fast knowledge-based responses to customer queries, in simple terms.
• In the engaging phase, agents can be alerted to birthdays or other important customer moments and generate tailored emails and messages to nurture relationships.

2. Driving efficiencies in corporate functions

Generative AI will potentially change the way people work in insurance, impacting core function across the business.

• In contact centers, the ability of customer service representatives to respond faster and more effectively will be enhanced through capabilities that enable streamlined workflows such as automated follow-up on emails and the ability to search and retrieve knowledge-based information in contextualized natural language.
• In human resources, the ability to attract and retain high quality candidates will be enhanced with tools that more effectively screen resumes, engage candidates through the hiring process, and deliver the knowledge that new employees need to do their jobs from day one and beyond.
• In legal, the ability to help attorneys and support staff to work more efficiently will be enhanced with tools that generate legal and regulatory summaries and assist with compliance and other specific challenges.  
• In marketing, the ability to connect with key stakeholders and tell the brand story will be accelerated by AI-generated ideas for content across channels and personalized, targeted email campaigns to promote products or services to specific audiences.

3. Creating copilots for each phase of the insurance life cycle

For virtually every aspect of the insurance life cycle, there is an opportunity to enhance experience and add value through a copilot—an application that uses generative AI and large language models to assist with complex tasks and offer a suggested course of easily executable action. Insurers are exploring early generative AI use cases across the business. For example:

• Customer copilots can help customers find the information they need about policies and services across a variety of web and mobile interfaces.
• Underwriter copilots can help underwriters augment decision-making with automatic summaries of applications and policy documents.
• Claims examiner copilots can help claims managers evaluate filings, process settlements, extract data from documents, or facilitate data entry.
• Actuarial copilots can help actuaries expedite trend analysis and automate mundane tasks.

Get engaged now on your generative AI journey

Now is the time for insurers to evaluate and experiment with AI, as it is revolutionizing how insurers assess risk, process claims, interact with policyholders, and empower employees.

We invite you to learn more by contacting your Microsoft representative or solutions partner. Or, for those who plan to attend InsureTech Connect (ITC) from October 31 to November 2, 2023, in Las Vegas, Nevada, we invite you to meet with us in person at Mandalay Bay’s South Convention Center, Lagoon L, where we will showcase the use cases and capabilities that we and our partners are bringing to market. In addition, Microsoft leaders will be presenting at the event in main program and partner sessions on key topics in the industry, including the following:

• Data-Smart Life & Annuities: Embracing ChatGPT and AI for Insurance Transformation—Jeffery Williams, Director, Insurance Digital Strategy, Worldwide Financial Services, on Tuesday, October 31, 2023, from 2:20 to 3:20 PM PST in Mandalay Bay Ballroom J.
• Microsoft: Embracing Open Insurance: Unlocking Opportunities within Distribution— Sasha Sanyal, Worldwide Financial Services, Americas Regional Leader, on Wednesday, November 1, 2023, from 2:40 to 3:00 PM PST in Mandalay Bay Ballroom F; and “Women’s Leadership Forum,” Wednesday, November 1, 2023, from 3:00 to 5:00 PM PST in the Foundation Room.
• How AI Is Changing the Way We Operate in Insurance—Jim DeMarco, Insurance Practice Lead, on Thursday, November 2, 2023, from 12:30 to 1:30 PM PST in Mandalay Bay Ballroom G.
• Automating the Submissions Intake Process with AI to Drive Better Decisions and Better Outcomes (Presented by Indico Data)—Tom Wilde, CEP, Indico Data, and Naveen Dhar, Director, Insurance Digital Strategy, Worldwide Financial Services, on Thursday, November 2, 2023, from 2:40 to 3:00 PM PST, Reef A-F.

Next steps

You can learn more about how Microsoft Cloud for Financial Services is helping our customers realize the future of insurance in the era of AI, unlocking business value, and deepening customer relationships.

The post Insurance in the era of generative AI: Use cases that transform the industry appeared first on Microsoft Industry Blogs.

The contact center agent who answered Matt’s call immediately authenticated him with voice biometrics, removing potential friction from this highly charged moment. Guided by AI-powered insights and suggestions, the agent then walked Matt through a quick yet complete intake process. Automatically, the contact center platform sent Matt an SMS link to upload photos of the damage, as well as follow-up communications with details of his claim. Afterwards, the platform generated a call summary, and extracted details and insights for future calls. And Matt, despite the fender bender, felt better about his insurer for making the process so easy.

This scenario, which until very recently would have seemed futuristic, is just one of many examples of how generative AI is redefining the very notion of a contact center for insurance companies, banks, and other capital markets firms. It is only one example of the kind of transformation we at Microsoft together with our global partners are helping customers realize with Microsoft Cloud for Financial Services.

The contact center cost conundrum

COVID-19 highlighted the critical importance of contact centers to financial services businesses, as housebound customers had only phone calls, emails, and digital access to connect with their financial service providers. It was suddenly left to contact center agents and customer-facing digital tools to handle the lion’s share of many key functions, such as responding to customer problems, providing important information, and assisting with transactions and account issues.

As COVID-19 pressures ease and new business requirements emerge, companies now face new challenges to keep their contact centers vital and efficient. Among them:

• Modern customers expect personalized experiences, and they get frustrated by disconnected interactions and incomplete information that can result from siloed systems and data.
• Customers demand simple and effective self-service experiences and are turned off by limited solutions.
• Contact center agents want to focus on solving problems for customers, but struggle to use cumbersome tools and difficult training requirements, which can result in high rates of attrition.

The leaders we’ve talked to in financial services firms recognize that contact centers represent a major opportunity to enhance the bottom line and drive new revenue. But contact centers have traditionally been cost centers. Now with generative AI, companies have quickly recognized that the new capabilities of large language models (LLMs) and data analytics can further unlock business value.

The generative AI contact center

Generative AI is transforming contact centers with a set of powerful new capabilities such as:

• Content creation: authoring content that is similar in style and tone to what people are used to.
• Summarization: writing summaries from large volumes of data.
• Semantic search: using natural language to understand the intent behind queries.

These provide the basis of innovations such as intelligent chatbots, virtual assistants, and customized solutions that use natural language processing, interactive voice response (IVR), trend and sentiment analysis, and much more.

In practical terms, generative AI transforms the contact center into a highly efficient asset that understands abstract context, provides engagement at a near-human level, and empowers agents and employees to deliver service faster and more effectively.

The potential impacts of generative AI innovations are huge. Personalized interactions can dramatically boost service-to-sales conversions. Perceptive self-service tools can spike customer satisfaction through instant gratification. And tools that reduce data entry can improve agent productivity. On the expense side, AI can reduce labor costs by reducing training requirements for agents who, in turn, can deliver better customer experiences that increase customer loyalty.

We see generative AI providing near-term benefits for financial services firms in the following broad categories of use cases:

• Agent assistance: Empowering customer service and helpdesk agents with bots to provide insights and next-best-action guidance derived from disparate knowledge sources across the organization. Assistance can also incorporate multi-language transcription, management bots for forecasting simulations, and automated call scoring.
• Fraud detection: Continuously monitoring and analyzing incoming data streams for potential fraud. For example, advanced biometric detection not only enables immediate authentication based on a customer’s unique voiceprint, but it also recognizes an attempt to impersonate the customer.
• Interaction analytics: Identifying patterns in customer behavior to deliver increasingly personalized responses. Generative AI can look across every conversation (voice, text, email, and so on) to identify trends, inform product improvements, enhance agent coaching, and ensure compliance.
• Self-service: Automating routine tasks and repetitive queries with conversational chatbots and IVR capabilities that enable computers to have conversations with customers. Over time, generative AI can also create personalized responses in customer engagements based on experience and learning from across the organization.

Put generative AI to work in your contact center

Microsoft offers a broad suite of solutions and capabilities that addresses the contact center needs of financial services organizations. The generative AI use cases listed above, enabled by Microsoft technology, can be provided on any contact center platform including those from NICE CXone and Solgari, which run on Microsoft Azure. In addition, they can be provided through solutions in Azure from partners such as Verint and Callminer. Microsoft Azure data and AI services application programming interfaces (APIs) integrate easily with call center platforms to enable new use cases, which are enhanced greatly through the solutions and contributions of our global partner ecosystem and can be integrated into Microsoft Teams and Dynamics 365.

Contact center transformation at Money20/20 USA

We were excited to showcase Microsoft’s remarkable innovations in contact center transformation at the Money20/20 USA conference in Las Vegas, Nevada from October 22 to 25, 2023. We demonstrated innovative solutions and highlighted the progress our customers and partners are making with solutions built on Microsoft Azure OpenAI Service and the Microsoft Cloud. Among the highlights:

• At the Microsoft AI Lounge Powered by Nvidia, we hosted 30 presentations from more than 20 partners across a broad range of demos, case studies, and thought leadership topics. We were delighted to showcase how Microsoft is using generative AI in our own contact centers (with all 55,000 of our agents), which is delivering remarkable benefits.
• Microsoft partners presented an innovative set of solutions featuring generative AI scenarios in our lounge and in the Money 20/20 pavilion.
• Microsoft’s Daragh Morrissey, Director, Worldwide Financial Services, discussed Microsoft’s broader generative AI approach in a panel discussion on “AI, Quantum, and Crypto: Get Ready for the Impact on Payments.”

Get started on your journey today

Using generative AI to reinvent the contact center is an unparalleled opportunity not just to deepen customer relationships but to unlock new business value. With generative AI and the Microsoft Cloud, financial services businesses can optimize costs, reduce time to value, enhance collaboration, and use data to deliver more impactful business outcomes.

Learn more by visiting our website where you can discover how Microsoft and our partners are working together to help our customers transform financial services. If you want to accelerate your transformation journey, feel free to reach out to us or contact your Microsoft representative or technology partner.

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The post How Microsoft and generative AI are transforming financial service contact centers appeared first on Microsoft Industry Blogs.

Every insurer is keenly attuned to addressing the challenges the industry has faced in recent years—economic uncertainty and industry-specific concerns around climate change and geopolitical upheaval, to name but a few. Another challenge is technology, which holds the promise of either competitive differentiation (winning) when done well, or the threat of market loss or disintermediation (losing) when done poorly. There’s no middle ground.  

All this was true before 2023. Then, the world shifted. With the arrival of ChatGPT and generative AI, the power of AI became more accessible to everyone. For Microsoft, this will drive an evolution of our vision for intelligent insurance. For insurance companies—with their data-centric product focus, to their vast ecosystems of digital-savvy agents and customers—it is simply a red-hot opportunity.  

Microsoft and generative AI: Creating new possibilities 

We are seeing an unprecedented level of interest in AI technology that we’re seeing now around generative AI, which I generally define as a system for generating text, images, or code in response to user input or prompts, drawing on vast sets of data. Our customers are asking: What can it do for us now? What are the best use cases? How do we get started? 

The first thing we tell them is that generative AI is close at hand. For companies that want to build their own generative AI solutions, Microsoft Azure OpenAI Service brings together advanced models from OpenAI, including ChatGPT and GPT-4, with the enterprise capabilities of Azure. Critically for insurers, all data uploaded—including training data and content—is isolated within your Azure subscription so it stays within the bounds of your organizations. By being fully integrated into Azure, insurers also get all the advantages of enterprise-grade security and role-based access included. 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 large language model, enabling you to drive insights with greater accuracy than previous large language models developed by OpenAI. 

This is in addition to the fact that AI is already being integrated into the Microsoft Cloud and in the Microsoft products that customers already use and love. We recently announced Microsoft 365 Copilot, which integrates amazing new generative AI capabilities across the Microsoft productivity suite, and this is complemented by copilots for Bing Search, Microsoft Dynamics 365, Viva Sales, and GitHub. 

That’s a ton of innovation—so much that it may seem overwhelming. Let me offer some insights into what we see as the most important capabilities for insurers and how those will play out in use cases.  

Here are the top three generative AI capabilities that we expect will quickly take hold among insurance companies and deliver differentiating benefits:  

1. Content creation and summarization. Generative AI will be widely used within organizations to generate things like proposals, reports, presentations, and summarizing internal meetings and customer conversations.
2. Semantic search. Using natural language and context, searching will become smarter and faster, and will be continuously trained as you interact with your customers.
3. Code generation. With copilot capabilities for generating sophisticated code, developers will spend less time writing lines of code and more time designing new statistical models and mathematical tools for actuarial challenges.

Generative AI use cases insurers will love 

With these capabilities, we can enable some compelling scenarios. The following use cases can empower and drive productivity across the organization: 

• Empowered contact center agents. With the ability to transcribe, summarize, and get insights on every customer engagement, agents can instantly measure sentiment from the start to the end of a conversation. Contact center staff can get coaching in real time. And new intelligence can be fed into a contact center knowledge base to give agents better and faster responses to future questions. Insurers can benefit from aggregated insights for tracking key performance indicators for customer satisfaction, engagement, and Net Promoter Score impact, continuously improving the experience for customers.
• Empowered underwriters. In complex lines of business—as in commercial, specialty, and reinsurance—underwriting involves the processing of large amounts of unstructured data. Generative AI, in conjunction with other AI capabilities like optical character recognition (OCR), can play the role of an “underwriting assistant” by extracting and organizing the various forms of data, summarizing the content, and then suggesting areas of opportunity for underwriters to consider based on appropriate logic. Documentation can then be generated to bind the policy. This should free underwriters from non-core tasks and administrative tasks that typically take up to 40 percent of their time.
• Empowered claims managers. Generative AI will impact almost every step in the claims lifecycle. Customer service representatives can use it to summarize policy documents during the first notice of loss and more quickly respond to customer inquiries along the claims journey. Claim adjusters and handlers will use it to quickly ensure that high-priority claims are handled promptly and that lower-priority claims don’t cause delays or backlogs. Insurance recovery specialists will use it to help in the coding of subrogation and reinsurance claims to expedite the recovery of capital due from third parties or reinsurers.
• Empowered insurance brokers and agents. Generative AI enables you to deploy powerful knowledge base systems. As customers seek to buy new insurance products or renew their existing coverage, product knowledge bases enabled through a chat-like experience could empower brokers to answer customer questions about coverage levels and other benefits.
• Bigger and better virtual assistants. A new customer journey often begins online, where digital agents play a large role in helping them explore insurance. Generative AI reimagines the whole notion of a chatbot and enables new types of engagements. Customers and prospects will be able to ask all kinds of questions in natural language and quickly get contextualized answers. Employees and agency partners will also have better experiences by getting answers fast to the questions needed to do their jobs. 

Responsible AI by design 

Generative AI can sometimes generate inaccurate output, so for all use cases, human oversight and supervision are key. As next-generation AI innovation gains momentum, we are optimistic about what it can do for people, commerce, and society. Microsoft 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. Read “What is Microsoft’s Approach to AI?” for more information.

What’s next for intelligent insurance

Our mission is centered around empowering insurers, and we are thrilled to introduce them to our generative AI advancements through our Azure OpenAI Service and Microsoft 365 Copilot offerings. Moreover, we will collaborate with our industry partners to facilitate the integration of these powerful capabilities into their own solutions. I am eager to witness the innovative creations that our insurers and partners will develop with generative AI. Our collective efforts will allow us to use the most advanced AI models available to meet business objectives with responsibility, security, and the assurance that comes with the Microsoft Cloud. 

Find out more about our vision for intelligent insurance and how the Microsoft Cloud and our global partner ecosystem can help you address evolving customer needs, hybrid workplace requirements, complex regulations, new competitors, solution integration, and the increased frequency and severity of claims.

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 banking
• The era of generative AI: Driving transformation in capital markets

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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.

Compliance Program for Microsoft Cloud

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It’s easy to wonder if the challenges the insurance industry faces in 2023 outweigh the opportunities.  

Economic headwinds, new competitors, regulatory demands, and the lingering effects of COVID-19—it all adds up to one of the most difficult environments in recent memory. Nonetheless, I encourage insurers to see this as a time for optimism. Companies that have invested in strong digital foundations are weathering the storm and are in a good position to capitalize on new opportunities.  

In my conversations with customers, the number one theme I hear for 2023 is that insurers need to do more with less: more innovation with less time, more agility with less money, and faster processes with less risk.  

These goals (and more) are attainable, but the right digital strategy is critical. Looking forward, I see five priorities that every insurer should keep in mind: 

1. Leverage the cloud to digitize the business. Customers expect seamless omnichannel experiences as they engage with you on the web, via their smartphones, or with agents. Partners (agents, brokers, and affinity) want stronger integrations with you to create comprehensive views of their customers (who are ultimately yours) and to align your business strategy with theirs. The best way to meet these types of new demands is to tap into the benefits of the cloud. The good news is that most companies are well into their digital transformation journeys. Insurers like AIA invested in large-scale infrastructure modernization and are now not only reaping major benefits in cost savings, sustainability, and customer experiences but are positioned to do more with less as they create new digital capabilities and harness the power of AI. 

2. Deliver efficiency with AI. Competition in the insurance sector has intensified as industry leaders keep raising the bar on the customer experience with innovative digital solutions. And, of course, insurtechs are upending traditional industry practices with a digital-first mindset to deliver entirely new products and services that customers often love. To not just survive but thrive, insurers need to differentiate their products and services, without breaking the bank. This is where AI can help. AI and data analytics can improve efficiency and customer satisfaction by automating and streamlining processes such as underwriting and claims. And it can help create differentiated solutions that speed service delivery and impact. To cite just one example, Progressive is using AI-powered chatbots to save USD10 million every year as their bots answer up to 200,000 queries each month with personalized, intelligent, text-based responses. The potential of AI is astonishing, and Microsoft is committed to delivering on its promise in ways that are both impactful and responsible. 

3. Innovate with a cloud developer platform. One of the most important requirements of digitally transforming core insurance systems is to bring new solutions and services to market in better and faster ways. This is another area where AI is delivering amazing benefits. AI is redefining the very idea of an application and changing the way people build software. For example, with GitHub Copilot, AI is employed to turn natural language into coding suggestions and entire functions—in real-time, directly from the editor. Copilot draws context from the code a developer writes to offer recommendations for completing lines and even suggesting entire functions. Just as with the rise of compilers and interpreters, AI-assisted coding is poised to fundamentally change the nature of software development, giving developers a new tool to write better code, more easily. Developers using GitHub Copilot see a 55 percent productivity boost when working on real-world projects and tasks.¹ And, as Gjensidige, Norway’s largest insurance company has seen, a modern “DevSecOps” environment also puts security front-and-center, without impeding developer velocity. 

4. Reenergize your workforce. It’s not only customers and partners who want digital experiences. Your employees expect them too. After all, when they’re not at work they’re customers themselves, and they know what a great digital experience is when they see it. For employees to thrive and build commitment to the business, they must be empowered and energized to do meaningful work. That’s what Microsoft 365, Microsoft Teams, and Microsoft Viva are all about, as Nationwide experienced when they built a hybrid work environment for their global workforce of 25,000 associates, and saw improvements in collaboration, flexibility, and employee wellness. Microsoft 365 delivers a cloud-first experience that makes work better for the new normal of today’s digitally connected, broadly-distributed workforce. Microsoft Teams provides an enterprise-scale platform for meetings, calls, chats, collaboration tools, and more. And Microsoft Viva connects the company from the frontline worker to the CEO with a complete system for delivering actionable insights and feedback, aligning organizational goals, and enabling the learning of new skills so that everyone can work together to achieve great business outcomes.  

5. Protect everything, everyone, everywhere. Last, but not least, is security. This is a top priority for every insurer, as both the pace and sophistication of cyberattacks continue to accelerate. Many chief information officers (CIOs) and chief information security officers (CISOs) can attest to the cost and complexity of effective protection, especially as the company digitally modernizes. The more connected your business gets, the faster a bad actor can move laterally through the enterprise and wreak havoc. The more agile operations become, the more your security teams struggle to manage risk. Your objective should be to ensure that new solutions are built with security at the core, not as an add-on. For example, when Zurich Insurance implemented a new suite of bookings and productivity solutions built on Microsoft technology, they also realized enhanced security and better compliance with regard to General Data Protection Regulation (GDPR) requirements. Security is baked into Microsoft offerings. And our enterprise solutions for identity and access, endpoint management, blocking incidents, and delivering security analytics and threat intelligence are all key to helping you protect your business. 

New technology will drive innovation across your value chain

As you move through 2023, don’t moderate your digital strategy due to uncertainty. Instead, view the unprecedented array of new technology options as a stabilizing force that can help you create product and service differentiation. In a competitive marketplace, you can drive new efficiencies across your value chain, especially in areas like automated underwriting and touchless claims. And sentiment analysis and data insight technology can help your employees win with customers and help you manage talent amid shortages. Finally, the right technology will help you create value for your customers by simplifying and digitizing their experiences with you, in ways that become progressively better.  

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Learn more about how Microsoft can help you differentiate your business today and build the digital insurer of tomorrow.

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¹GitHub, Research: quantifying GitHub Copilot’s impact on developer productivity and happiness, The GitHub Blog, September 7, 2022.

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Here are 10 strategies that insurance professionals should consider when building their strategy:

Technology strategy 1: Leverage advances in Artificial Intelligence (AI) to drive operational improvement and new opportunities

There are three main areas of benefit from AI: detecting insurance fraud, reducing claim costs, and mining voice data to enhance customer service.

Natural Language Processing (NLP) allows unstructured documents, such as claim adjuster notes, to add even more value, serving as a mechanism to detect fraudulent claims and patterns of fraud. NLP can also be used to read and process handwritten insurance-related forms and mine information to save the insurer money on claim costs. Voice recordings from agents and customers can also be used to enhance the overall customer experience and improve service.

Technology strategy 2: Smart and intelligent automation

Smart and intelligent automation focuses on the application of advances in predictive analytics and Machine Learning, applied beyond automating data collection processes through the use of robotic process automation (RPA) tools. Insurers should explore automating processes like property assessment, personalized customer interactions, fraud detection, and claims processing and verification. There is a huge opportunity to redefine operational improvements in call centers with voice translation, automated call monitoring for sentiment analysis leading to early escalations. Insurers can also benefit from a virtual call center that does not have all agents in one location and some agents are remote.

Technology strategy 3: Self-service drives “improved experience” while lowering costs

The food and retail industry are large proponents of the use of self-service for improved customer experience. However, this can also greatly benefit insurance companies for similar reasons. Implementing self-service both in claim settlement (touchless claims with automated claims payouts) and customer care through bots and virtual agents can cut costs, increase customer satisfaction, and lead to more personalized customer experiences.

Technology strategy 4: Employee experience matters (without compromising security)

Most companies regularly invest in their brand and customer experiences, but many forget to invest in a crucial component of a successful company: the experiences of their employees. To attract, retain, and boost the productivity of employees, insurance companies should increasingly look for ways to improve employee experience—whether virtually or in person—without compromising on security. With COVID-19, we have all learned the value of social distancing and insurers are redesigning workspaces to better address employee health. With an increasing number of remote employees, the employee experience and need for productivity from any place and location will be even more important.

Technology strategy 5: Competitive edge through data

Insurance has always leveraged data and thrived on data analytics. However, the need for data is more important now more than ever. Pairing big data with machine learning and predictive analytics, companies can leverage data to bring about new products, save costs, and stay competitive. Insurers are reinventing underwriting by leveraging new sources of data for competitive advantage and offering new products.

Technology strategy 6: Rise of new insurance products

The increasing shift towards autonomous cars and the use of sensors and IoT creates a disruption for insurance companies. Companies need to shift focus and tackle new opportunities appearing alongside these new technologies. New insurance products will emerge, insuring new types of risk. Technology teams will need to be prepared to support these new products.

Technology strategy 7: More insurance companies will have strategic alliances with tech companies

The advances in big data, AI, and data analytics are causing insurance companies to become more technology and data-driven than ever. As technology adoption increases, insurers will need to improve their technical capability. To strengthen their technical capability, insurers will seek access to big tech partners and influence features in their technology to stay competitive. Already, a handful of leading insurers have formed strategic alliances.

Technology strategy 8: Use of drones, sensors, satellite imagery, and Augmented Reality (AR) and Virtual Reality (VR)

Many of the processes that are typically done in person, such as user and employee education, coverage decisions, and damage prevention are being simplified with technology, creating a more immersive, accurate, and cost-effective experience for insurance companies. The use of augmented and virtual reality applies to the claims handling process, accident recreation, and many more processes. Uses of other technology, such as smart sensors or satellites to prevent and assess damage or reduce costs, will continue to increase.

Technology strategy 9: Legacy system modernization

Many insurers are still running old technology that is due for an upgrade. The benefits range from a reduction in costs, business agility, and improved productivity and user experience. Being able to leverage the advancements in new technology and the various new FinTech offerings is also a key benefit of system modernization.

Technology strategy 10: Trust and transparency in multiparty scenarios

Leveraging technologies that lead to increased trust and transparency in the transaction will lead to cost savings. Some scenarios include digital subrogation (where the insurance company collects money from the party at fault or their insurance company), workers’ compensation with worker presence verification, and digital identity services. Some insurance companies are also exploring ways to make the premium breakup more transparent to the customer as a way to ensure loyalty.

To learn more about building strong business strategies and read how carriers have modernized operations and strengthened customers’ experiences, visit our customer stories portal.

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What is digital stewardship in the insurance sector? To answer this, let’s begin with the background on data usage in the insurance industry. This industry is a unique combination of two things: (1) massive amounts of data and (2) a highly regulated and controlled process to use and store data. So a simple answer is this: digital stewardship is the process of managing, controlling and securing data, as it is used and generated through the insurance value-chain, in a way that meets all security and regulatory requirements. In this series of three blogs, we’ll explore digital stewardship as it relates to both data and data regulations.

Data and regulations in the insurance industry

Data is the lifeblood of the insurance industry. Data is used to assign and monitor risk, which drives pricing and renewal policies that culminate in overall profitability. Data is used by the core systems to track all customer interactions, helping to deliver differentiated policy holder experiences.

Regulations are the other side of the coin. Regulations define insurance products, and how and where such products can be sold. The regulations on data, data flows and data usage are the driving force for data stewardship.

Data categories

Data has many costs. For starters, there is the pure cost of maintaining data in some system—tape, hard drives, or solid-state drives. Then there is the cost of moving data, also known as bandwidth cost. For older data formats, it may be necessary to migrate to a new format. So, given the various costs that can accrue, it’s worth breaking down the sea of data into categories that can be understood.

Data use by insurance companies fall into three major categories:

1. Historic policy level data
2. Current, monthly transaction level data and current output from reserving calculations
3. External data sources used to assign risk. In this category there are multiple levels of data used to determine the risk of what is being insured

Historic policy level data

Historic data has special problems and benefits. This kind of data comes from legacy systems—mostly from on-premises datacenters. These datasets are a great source of longitudinal data (data gathered over long stretches) once it is normalized between the various system formats. The data also persists—often for many years—with some life insurance policies being issued at birth of the policy holder and only ending at that person’s death. The problem with historical data is the cost of normalization. Unless the data is transformed into a modern, shareable format, it remains in silos. If you have enough data in an old format, then you can pay the cost of transforming it to a modern format. The cost-benefit ratio depends on the value of the data.

Current monthly transaction-level data and current output from reserving calculations

To satisfy regulators, the insurer must always keep an actuarial reserve—money that must be available in case of a claim. As time goes by, money is worth less, due to inflation—so insurers must invest to build the reserve—or risk being unable to pay. At the same time, the insured must make payments to keep their accounts in good standing, which is the transaction-level data. The current transactional data has some of the same issues as the historical data as it feeds the same administrative systems. Additional data elements are generated by customers for many reasons. For example, new data comes as policy features change and by on-going policy level processing; more data arises from additional controls, meta data, and intermediate data from the policy valuation system and results. The difficulty here is regulator control or keeping up with new processing requirements as they are announced.

External data

The data that is used to assign risk at time of policy issue and throughout the life of the policy is now coming from varied sources, including wearable devices. A few examples: Fitbits, IoT sensors in the home, and government data sources for geographical based risk scores. Such data arrives at different frequencies and different levels of efficacy. The amount of the data that is now available, about the insured item or person, is overwhelming for most insurance companies. The general approach is to have a third party score the risk of the place, activity or person; the insurer then only tracks the scores and change in scores.

Regulations: controls imposed on products

Regulations are tied to the types of products that the insurance company is selling and the location where the policy is sold. For US-based insurance companies, the regulations start at the state level and can vary significantly between states. The US federal government has additional requirements based on the size of the insurance companies. International regulations are becoming increasingly important as more companies try to reach a global client base. Examples include: reserving and policy definition at the state level, Sarbanes-Oxley Act (SOX) at the federal level, and the General Data Protection Regulation (GDPR) and IFRS-17 at the international level.

For SOX there’s the process control cost, as every stage has a control. Signoffs must occur between each stage. Here’s an example of a process control: when Microsoft releases a new version of Excel, calculations must be run with the new version and the results must then be compared with the older version. It’s a simple check to make sure the calculation engine is not introducing errors, but it’s still a control nonetheless. The same kind of testing/checking occurs if an operating system is changed. In this instance, only policy changes are allowed, not changes from software. The list of controls and signoffs can be huge and complicated. And so, it is expensive to maintain compliance with existing controls and to continually add new ones.

In brief, the result of compliance is the ability to repeat any calculation—on demand. The actuary must be able to duplicate the calculations for regulators and auditors. It’s the ultimate version of “show your work.”

Easing the burden with Microsoft

The complexity and scale of these problems mean automation and the constant evolution of software solutions. Microsoft constantly invents new tools and services, and partners innovate with the same devotion to solve problems. My next three blogs will explore a variety of use cases to illustrate how the insurance industry can use Microsoft technologies for enhanced digital stewardship. I’ll cover these topics:

1. Data security, how to comply with all internal and external requirements (access and authorization automation, audit the personnel coming and going)
2. Keeping your company GDPR-compliant
3. Archiving solutions (for data)

Microsoft is driven to deliver solutions to enhance digital stewardship for the insurance industry across all platforms, from on-premises solutions, to hybrid, to full Azure cloud deployment and beyond. We continue to innovate with our partners to incorporate the latest technologies to meet the needs of our customers.

Next steps

Explore other ways Microsoft is helping insurers innovate and transform. Download the whitepaper “Inside the data science virtual maching” or visit the Microsoft insurance website.

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