Category: IT Services

Generative AI in Healthcare – A Game Changer or Another Fad? | Blog

Generative AI (GAI) has disrupted numerous industries, and the healthcare industry is eager to join in and explore the applications of GAI in healthcare research. However, the healthcare sector must be cautious due to the potential risks. Read on to learn more about Generative AI in healthcare, including adoption, usage, and risks.

Reach out to us directly for questions or further details.

Generative AI, an advanced technology that employs deep learning models, can create images, videos, text, codes, simulations, and other high-quality content by responding to given prompts within seconds.

While GAI has been shaking up almost every industry with its easy-to-use interface and instant responses, the healthcare sector is typically slower to adopt new technology, and the risks of inappropriately deploying the technology are huge.

Nevertheless, technology giants and healthcare startups are racing to test the potential for large language models (LLMs) and GAI tools in healthcare research. Understanding the adoption, usage, and potential risks of GAI in the healthcare setting is crucial.

With its vast applications, it is important to carefully select the use cases that can positively impact patients with minimal regulatory, compliance, cost, and health risks. Let’s explore this further.

By using the below framework, healthcare organizations can prioritize use cases for observation, exploration, and future investment:

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Based on our analysis, GAI offers the greatest immediate potential in the area of clinical documentation. The technology can be used to free scarce clinical resources from time-consuming administrative tasks, allowing them to instead focus on delivering quality care to patients. For example, simplifying clinical documents and creating easy-to-review clinical patient summaries are some areas where GAI can have the greatest short-term impact in healthcare.

Looking beyond these basic applications, healthcare stakeholders need to cautiously consider using GAI for diagnosing patients or directly providing medical care. The technology’s tendency to sometimes invent a response when it lacks sufficient information makes it too risky for care delivery. Significant long-term investments will be needed before GAI can be used for delivering patient care.

Will Generative AI in healthcare lead to job loss?

GAI is expected to considerably alleviate the administrative burden of healthcare professionals. The nature of jobs will shift and healthcare professionals will have to adapt as demand grows for GAI. Certain healthcare professions such as medical transcriptionists, medical record keepers, medical coders, call center executives, and home healthcare executives will need to upskill as GAI automates some manual processes.

The other big question in everyone’s mind is whether GAI will completely replace physicians. This is unlikely to happen anytime soon. GAI should be viewed as a tool to augment healthcare professionals’ capabilities and not replace them entirely. Physicians, surgeons, radiologists, and nutritionists will leverage GAI to enhance care delivery.

Challenges to future adoption

Generative AI in healthcare is a disruptive opportunity that both excites and concerns healthcare professionals. While it offers significant potential, the industry needs to overcome obstacles to commercial adoption.

Some of the risks include:

  • Ethical concerns and biases – Healthcare professionals must be wary of the ethical concerns and limitations related to using sensitive member/patient information. Moreover, limitations of datasets also can lead to biases in results or outcomes suggested by GAI
  • Training data limitations – Generative AI models require high-quality training data to improve the accuracy of output, which can be difficult to source. The model’s efficiency also depends on the breadth of training data, which can be both time-consuming and expensive to label
  • Integration issues – Integrating GAI into existing healthcare systems and workflows can be challenging, especially with legacy systems that are not designed to work with AI
  • High costs – The technology costs of building and deploying GAI models can be expensive

Adopting Generative AI in healthcare can be a game changer. While it offers many potential benefits, the industry needs to fully understand the associated risks of GAI before implementing use cases and adopting the technology at scale.

To discuss the future of Generative AI in healthcare, contact Kaushik Sundar, [email protected], or Priya Sahni, [email protected].

Continue learning about the healthcare industry in our webinar, How Technology Can Help Healthcare Overcome the $30 Billion RCM Spend.

Googling Growth: How the Google Cloud Specialization Strategy Enables Enterprises to Innovate and Differentiate | Blog

Google Cloud continues to differentiate itself from other cloud providers by emphasizing specialized services, tools, and a partner-oriented strategy that enables businesses to achieve better flexibility, scalability, and security. Learn how the Google Cloud specialization strategy can help enterprises large to small generate greater value from cloud implementation.

To learn more about this topic, reach out to us directly with questions and for more information.

How have enterprise cloud adoption trends evolved post-pandemic?

The pandemic years profoundly impacted enterprises worldwide, and hyperscalers are no exception. A shift began when cloud gained popularity as a go-to tool to transform the enterprise landscape. As more enterprises moved online, the demand for cloud services skyrocketed, and cloud adoption topped enterprises’ digital transformation agendas.

Fast forward to the present day, when enterprises are still exploring cloud services but with a different agenda. The enterprise cloud adoption strategy has transitioned from “leap and observe” to “assess and stride.” Thus, cloud technology has transitioned from being a support tool to an enabler for enterprises’ long-term business growth, with new trends emerging to meet the changing needs of businesses and consumers alike.

How does Google Cloud meet the current enterprise preferences?

Google Cloud has evolved its value proposition to respond to market disruption by catering to use cases that provide such benefits as improved customer experience, better cost optimization options, increased security, the industry cloud, and many others.

It is slowly developing niche expertise to position itself as a strong competitor in the cloud provider ecosystem. With multi-cloud and hybrid-cloud adoption rapidly accelerating among enterprises, Google Cloud is emerging as a preferred secondary cloud option because of its flexibility and compatibility with existing enterprise infrastructure, simplicity of data analytics and Artificial Intelligence (AI)/Machine Learning (ML) products, robust security features, and cost-effectiveness.

With a targeted focus, its expertise echoes customers’ key adoption preferences, such as:

  • Gaining innovative insights from data streams: Data is the “key” that opens pathways that can help any enterprise build a competitive advantage through innovation. However, the typical characteristics of data, such as volume, veracity, and variety, have always posed challenges for enterprises in effectively analyzing and utilizing the data. This becomes even more concerning for firms operating in a multi- and hybrid-cloud environment. Google Cloud’s targeted focus on “an open, unified, and intelligent data ecosystem” can provide improved insights while managing each data lifecycle stage.

Enterprises seeking to harness their existing data’s full potential for business growth and innovation are taking advantage of Google Cloud’s AI-enabled data offerings. From natural language processing and computer vision to predictive analytics and personalized recommendations, enterprises are opting for Google Cloud’s AI/ML solutions to drive innovation, unlock new insights, and, thereby, improve business outcomes. Enterprises are widely adopting BigQuery for scalable data analysis. Moreover, Google Cloud’s investments in expanding data center coverage and rising computing and storage capabilities are aligned with meeting rising enterprise demand for seamless data-driven innovation

  • Embracing open-source cloud for flexibility and control: A few years into their cloud journey, enterprises are experiencing visible cloud challenges, including inefficient scalability, limited agility, and rising cost pressures. To create a flexible, interoperable, and reliable cloud infrastructure, they are gradually transitioning to an open-source ecosystem. Enterprises are using Google Cloud’s latest products and services to create an open-source portable application architecture, which can provide ease and flexibility for developers to remain in a lock-in-free environment.

 As enterprises strive to maintain ownership and control over their data and applications, Google Cloud’s open-cloud approach provides them with the necessary transparency and control to address security and compliance concerns. With its key contribution to various open-source projects such as Kubernetes, Istio, and TensorFlow, Google Cloud has fortified its position as a cost-friendly cloud that offers enterprises the ability to maintain ownership and control over their data and applications

  • Creating secure cloud infrastructure: Security has become a top priority for enterprises as they deal with massive amounts of data and essential workloads on cloud platforms. They are more concerned than ever about keeping complete control over their IT infrastructure and guaranteeing the security of their cloud-based infrastructure, owing to the soaring need for resilience and reliability post-pandemic. Traditionally, Google’s security focus spanned its product suite, including encryption of data at rest and in transit, and AI-enabled threat detection. Its recent acquisitions, Mandiant and Chronicle, are steps towards creating an end-to-end secure cloud security suite focused on preventing threats and providing reliable and secure cloud services. Enterprises are choosing Google Cloud for secure cloud infrastructure due to its security features, private global network, and comprehensive compliance framework and certifications

How can enterprises continue to grow with Google Cloud?

Enterprises are increasingly appreciating Google Cloud’s specialized offerings, and their adoption journey remains centered around selected technology workloads. Twitter, Mayo Clinic, and Ford are some prominent examples of enterprises following this approach. Let’s take a further look at the Google Cloud specialization strategy.

Recognizing the paramount adoption shift, Google Cloud quickly organized its core specializations and processes into the following three strategic differentiators that enterprises could leverage for business growth:

  1. Industry-centric ecosystem as a differentiator: During cloud transformation engagements, enterprises face multiple vertical-specific constraints, including data sovereignty, regulations, and governance of mission-critical applications. These constraints have become significant concerns, requiring effort-intensive operations to effectively mitigate the associated challenges. Providers and vendors have recognized the importance of industry-centricity, and Google Cloud has been no different. However, its focus on industries is aligned with its data and next-generation expertise, with a higher preference flowing in from verticals where this expertise can transform the entire value chain. Prominent examples are retail, distribution, and consumer packaged goods (CPG) verticals, where Google Cloud’s AI/ML products and models can be used to reinvent the entire supply chain. Enterprises in the healthcare domain can leverage solutions such as Healthcare Data Engine and AlphaFold for health analytics and drug discovery, respectively. Google Cloud’s industry-specificity can help enterprises improve the customer experience by accelerating time to market, introducing customized innovative solutions, and optimizing enterprise operations
  2. Unified cloud ecosystem as a differentiator: Google Cloud’s approach of “open cloud, data cloud, and trusted cloud” is suited to provide enterprises with a well-defined unified ecosystem that can help them navigate the cloud, maintain required operational efficiencies, and enable business growth from Moreover, enterprises can benefit from this unified ecosystem by accessing the services and products that can help create a cost-efficient, agile, and resilient cloud transformation approach
  3. Partner ecosystem as a differentiator: Inefficient strategy roadmaps have emerged as one of the top reasons cloud adoption fails within enterprises. While Google Cloud has strategically engineered its products and services, it relies on channel partners to deliver them. These partners approach each cloud engagement with the objectives of enablement and growth. Enterprises can align with partners through a Google Cloud conduit that acts as a matchmaker. These partners bring the required talent, tools, and experience to act as an extension of the team while being long-term strategic enablers during enterprises’ cloud journey. Moreover, Google Cloud’s technology vendor landscape has evolved to create a collaborative ecosystem for enterprises, which can allow them to innovate their product offerings

How can enterprises best adopt Google Cloud?

Overall, adopting Google Cloud requires careful planning, coordination, and management. Enterprises can ensure their cloud adoption is executed smoothly and efficiently by asking the following questions:

  • Contracting:
    1. What measures can we take to establish accountability for meeting defined service commitments and objectives and key results? Have we considered contract termination scenarios?
    2. How easy are the contract update, renewal, and termination processes?
    3. How much flexibility do we have during contract change, renewal, and termination? Are we aware of the pricing and inclusion of products in enterprise discount plans such as Sustained Use Discounts (SUDs) and Committed Use Discounts (CUDs)?
  • Solutioning:
    1. How can we ensure our cloud adoption strategy roadmap aligns with organizational goals and objectives?
    2. Are we leveraging industry-centric products and services available in Google Cloud’s open ecosystem to enhance flexibility within the enterprise?
    3. How can we effectively collaborate with Google Cloud and third-party vendors to accelerate and optimize solution delivery?
  • Talent management:
    1. How ready is our talent pool to handle the operational and business complexities associated with the Google Cloud adoption?
    2. How will we ensure change management while transitioning to Google Cloud ecosystem?
    3. What measures should we take to guarantee ongoing training, support, and knowledge enhancement for all individuals involved in the Google Cloud adoption, while also considering the engagement of Google Cloud’s engineering and professional services teams?
  • Governance:
    1. What is our governance framework to effectively manage the adoption of Google Cloud within our enterprise?
    2. How can we ensure a controlled and accountable approach to Google Cloud adoption?
    3. How will we actively monitor and address risks associated with Google Cloud adoption, and what are our mitigation strategies to minimize the potential impact?

With maturing digital adoption, enterprises are changing their outlook towards utilizing the cloud as a key value generator. A successful strategy and a well-established roadmap are needed to realize cloud’s expected value. Choosing the right system integrator to partner with is also critical to get the most out of Google Cloud adoption.

Reach out to [email protected] and [email protected] to understand how to best leverage Google Cloud’s solution, industry, and partner ecosystem, the right metrics to effectively select a cloud transformation partner, and other cloud adoption trends.

Future Insurance Technology Trends: A Closer Look at the Need for Building Humanized Insurance Experience, Data-driven Intelligent Operations, and SaaS Integration | Blog

From the many thought-provoking conversations that Everest Group analysts engaged in at Formation ’23, three main themes emerged about the future of insurance technology. These priorities are: integrating a humanized and people-centric approach, leveraging data to make intelligent decisions, and strongly emphasizing the Software-as-a-Service (SaaS) ecosystem. In this blog, we will take a closer look at these growing trends and explore their potential impact on the insurance industry.

Contact us directly for more insights.

Formation ’23 on May 8-10, hosted by Duck Creek Technologies (DCT), provided an excellent opportunity for Everest Group analysts to engage in exciting conversations with the community of insurance enterprise leaders, technology providers (from DCT and its solution partners), system integrators, consulting firms, and other analysts, about what will drive the next era in insurance.

Based on the dialogue we heard, the following three themes stood out to our team:

  • Building humanized and consistent experience will be the key to success

Delivering high-quality personalized customer experience is taking center stage in the insurance industry’s current transformation as carriers move from their traditional role as loss payors to becoming empathetic insurers and guardians for customers.

Digital experience platforms, distribution management systems, and smart communication platforms are becoming increasingly relevant to streamline operations, provide seamless and consistent digital experiences, and engage customers more effectively.

Data will play an important role here by equipping insurers with the right information that they can use to personalize and humanize the experience for individual customers. Interestingly, DCT also gave us a preview teaser of its new product – Elea, an AI-powered and empathy-driven chatbot slated for release later this year.

  • Infusing data and intelligence into insurance operations is the industry’s top priority

Data-driven intelligent decisions are a key priority for the industry. As the insurance industry moves toward AI-powered workflows, infusing data and having standard data models at a value chain and workflow level will be a major demand.

We found it interesting to see various point solutions offered by technology providers, such as CogniSure’s AI platform, which helps automate the underwriting process by converting structured and unstructured data to improve efficiency and effectiveness.

We also heard many discussions about early use cases of Generative AI (GAI) for operational tasks (emails, presentations, etc.), GAI-powered chatbots, and writing codes. But concerns remain about using this fast-growing technology in core operations.

  • SaaS sprawl requires attention

 SaaS sprawl was another theme that dominated conversations. While the point solutions across the value chain come with the benefit of speed to market and bridge the capability gap on the top of core systems, integration across these remains a concern as these solutions often don’t talk with each other.

Enterprises leveraging a wide number of these point solutions now see the need for digital rationalization. Most of these software platforms have evolved and added new functionalities. But enterprises are not taking advantage of the latest features because they are either unaware of these benefits or because they are paying for other software with the same purpose. This leads to duplicate costs and less value.

These conversation themes and focus areas resonate well with what we expect from the industry in this environment, but we felt some upcoming trends did not get enough attention from the community – low code/no code technology being the most prominent one.

As always, Formation ’23 was a great experience for Everest Group to interact, learn and exchange thoughts and points of view with industry leaders about the future. The fun atmosphere in Orlando, Florida, complete with country music, delicious food, and drinks, added to the interesting conversations, resulting in lasting memories.

To discuss these insurance technology trends in more depth, please contact Ronak Doshi and Roma Juneja, who attended this insightful event.

Continue learning about insurance technology trends in this blog, Uncovering a Massive Insurance Industry Cloud Opportunity.

Generative AI – Redefining the Experience Design and Development Process | Blog

Generative Artificial Intelligence (GAI) holds the potential to revolutionize the experience design and development process by creating unique personalized marketing content. Read on to learn about the opportunities, challenges, and implications of GAI for enterprises and service providers.

You can also hear about the use cases, the limitations and risks, and the industry’s predicted response in our webinar, Welcoming the AI summer: How Generative AI is Transforming Experiences.

From rule-based systems merely capable of automating set functions to deep learning algorithms that can accurately comprehend natural human language nuances, Artificial Intelligence (AI) undoubtedly has come a long way.

Today, AI is at a juncture where its capabilities are no longer restricted to automating repetitive tasks. Generative AI – the latest version of this technology – has taken the industry by storm this year by entering the arena of human creativity.

While GAI is flooding the market with a plethora of unique use cases, it particularly has the potential to disrupt the experience design and development process by optimizing the content supply chain and streamlining the UX/UI design process. Let’s explore this further.

What is Generative AI?

Everest Group defines Generative AI as a variant of AI technology based on deep learning Generative Adversarial Networks (GANs) and Transformer models, having the ability to provide convincingly unique content in the form of text, imagery, video, audio, and synthetic data.

Although the technology has been around for the last five decades, it has recently gained momentum due to advancements in hardware computation power, maturity of AI models, and availability of high-quality contextualized training data sets.

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Exhibit 1: Definition and evolution of GAI technologyPropelled by investments from giants such as Microsoft, Google, and Amazon, the market is witnessing a huge influx of start-ups focused on consistently identifying and operationalizing new Generative AI use cases.

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Exhibit 2: Start-ups pioneering unique use cases in the GAI space

How can GAI help marketers?

As personalization becomes the centerpiece of every marketing strategy, the never-ending demand for real-time contextualized content puts a lot of pressure on creative teams. This is where GAI comes in. Be it content creation or user interface/user experience (UI/UX) design, the technology can create a scalable creative engine for personalized marketing.

The industry is acting fast to streamline the marketing creative process by adopting GAI. Experience leader Adobe has launched the Firefly family of proprietary GAI models that enable image, audio, video, and 3D model creation through mere text prompts. On the other hand, AI leader NVIDIA has introduced the GauGAN tool that can generate realistic images from sketch drawings by artists.

GAI – The brainstorming partner for idea generation across industries

While content remains key, enterprises also are investing in GAI models in vertical markets to power industry-specific use cases to brainstorm and generate creative ideas.

 The following industries are rampantly adopting GAI technology:

  • Manufacturing: General Motors partnered with Autodesk to use GAI to design a new seatbelt bracket that was 40% lighter and 20% stronger than the original design
  • Healthcare: GAI also is being applied in drug design with companies such as Insilico Medicine using its Chemistry42 GAI platform to generate novel chemical compounds for new medicines
  • Architecture: Architecture firm Skidmore, Owings & Merrill (SOM) has created a GAI tool called SOM Computational Design for generating design options for buildings
  • Retail: Levi Strauss has partnered with to design hyper-realistic AI-generated model avatars for promoting diversity in terms of body type, age, and skin color

While AI has leaped in maturity from automating unproductive repetitive tasks to generating unique content via human-led prompts, it still lacks the finesse of a human touch. Therefore, the technology can act as a co-pilot for the creatives, but it’s not yet at a stage where it can provide customer-ready outputs through prompts. Instead of instilling fears about the technology replacing humans, enterprises must embrace the magnitude of the impact it can have on workforce productivity.

Mitigating GAI technology risks

The technology is a game changer, but it comes with substantial challenges related to output accountability, model bias, privacy compliance, talent shortage, system integration, and the cost associated with deploying large AI models.

 While Italy has banned ChatGPT and other European nations have expressed concerns about the technology, pioneers such as Adobe and Salesforce are relentlessly trying to mitigate these risks by developing plagiarism checkers, establishing compensation structures for creative professionals, upskilling talent, and adopting fair representation learning models to counter model biases.

Implications for service providers

With announcements of Accenture’s GAI Center of Excellence, Deloitte Digital’s dedicated GAI practice, Infosys embedding GAI into software development tools, and TCS developing an in-house enterprise-grade solutioning platform using GAI, service providers need to take a cue and move fast to cement a strong understanding of Generative AI functioning and the ecosystem.

Providers also have to bring top leadership up to speed on the Generative AI landscape, flesh out a detailed narrative discovering enterprise priorities, embed GAI in solution and service delivery for efficiencies and productivity, and harness GAI technology’s true potential by integrating it with business applications.

For more insights on Generative AI, contact Vaani Sharma.

HIMSS23 Highlights: Focus on Integration, Generative AI, and Increased Emphasis on Risk Mitigation | Blog

Artificial Intelligence (AI), technology integration, and consumerization are among the key trends driving the future of healthcare, a glimpse into the horizon at HIMSS23 showed. Read on to learn takeaways from Everest Group analysts who attended the recent global healthcare conference.

More than 35,000 healthcare leaders converged in Chicago last week to share ideas, highlight investments, showcase demos, and shape the future at HIMSS23. Technology integration, value realization, and risk avoidance dominated conversations at this year’s more strategic and connected conference focused on finding solutions to urgent issues.

Here are the three main themes we saw at HIMSS23:

  • Integration is the key to realizing value

Integration was a major topic, as many organizations struggle to stitch together various composable platforms. While microservices have enabled precision and faster outcomes for specific use cases, these independent solutions often do not communicate with each other, which can hinder value realization. Many stakeholders we interacted with highlighted the desire to explore ways to better integrate these platforms.

  • Generative AI is attracting attention

Generative AI, like ChatGPT, and its potential applications is creating a lot of excitement. Major technology companies such as Microsoft and Google are leading the way in developing innovative uses for AI in healthcare, including creating new health applications. While some early examples of AI in healthcare show promise, such as voice dictation that help doctors document patient information more efficiently, how AI will address broader healthcare challenges such as staffing shortages, physician burnout, and rising costs remain to be seen.

  • Consumerization of healthcare will continue to grow

Putting the patient at the center of healthcare was another recurring theme, with a focus on designing healthcare systems and technologies that are intuitive and seamless for users. The increased emphasis on user experience has been influenced by the consumer world, where these types of technologies are the norm. The coming years are likely to bring a greater focus on patient portals, wearable health solutions, and virtual care delivery technologies to improve patient/member experience.

How was HIMSS different this year?

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The annual HIMSS conference returned to Chicago, with attendees noting a greater sense of urgency and action in meetings versus prior events in Orlando and Las Vegas. A large number of healthcare information and technology companies attending were focused on emerging enterprise priorities around value-based care (VBC) and interoperability.

Leaders engaged in meatier discussions focused on integration, value realization, and risk avoidance. The conversations showed that healthcare enterprises are looking for solutions to get more out of their technology, budgets, and resources in today’s challenging environment.

The large post-pandemic turnout demonstrated the appetite for in-person interaction. Event organizers focused on creating more focused opportunities for attendees to gather and have relaxed and candid conversations with friends, colleagues, and clients, which have been difficult to replicate virtually.

Overall, interacting with industry leaders influencing the next stage in healthcare technology at HIMSS23 was an illuminating experience for Everest Group analysts Abhishek Singh and Manu Aggarwal, who are available to share their insights.

Continue reading about the healthcare industry and the trends influencing decision-making by healthcare payers in our blog, The Recessionary Conundrum: What Lies Ahead for Healthcare Payers?

Pension Risk Transfer: The Next Greenfield Opportunity in Retirement and Insurance | Blog

With pension risk transfer (PRT) activity hitting post-pandemic record highs of $53 billion in North America market volume last year, this growing market represents a massive untapped opportunity for technology and services providers to leverage their retirement and pension expertise to deliver new solutions. Read on to learn about the possibilities this option opens. 

Even with the general shift towards defined contribution (DC) plans, defined benefits (DB) assets still contribute to the majority of retirement Assets Under Management (AUM) in the US. However, defined benefit plan providers often struggle to guarantee the security of retirement benefits because of the following risk factors:

  • Unpredictable investment returns due to variable interest rates, market volatility, and the geopolitical environment
  • Volatile interest rates
  • Increasing life expectancy and longer service tenure of plan participants
  • Underfunded pension liabilities

To shield against this unpredictability, plan sponsors are adopting pension risk transfer strategies to guarantee retirement and pension benefits for DB plan members. Under this approach, DB plan providers transfer their entire/partial pension liabilities to other firms, usually a life insurance firm, to remove their obligation to pay plan participants guaranteed retirement income or post-retirement benefits.

In the past four years, PRT transactions have increased as DB plan providers seek to de-risk huge pension liabilities. Many large and mid-sized plan sponsors are hedging these risks through PRT transactions with the intent of transferring or terminating existing DB plans.

The pension risk transfer market peaked in 2022 as retirement plan sponsors urgently felt the need to secure pension benefits in an increasingly uncertain world following the pandemic.

The growth momentum is expected to continue due to favorable transaction terms for sponsors and insurers’ continued desire to de-risk pension assets. North America accounted for approximately two-thirds of global PRT sales (US$60 billion) in 2021 and grew by 40% in 2022. In both these years, almost half of the PRT transactions were near US$1 billion or more, according to the LIMRA Secure Retirement Institute.

Pension risk transfer types

The following two PRT transactions are most prevalent in the market:

  1. Buy-in – The insurance firm takes the liability of benefit payments for plan participants to the plan trust. The sponsor retains fiduciary and administration obligations and holds the pension plan contract as an asset on its balance sheet
  2. Buy-out – The insurance firm takes the liability of benefit payments for plan participants entirely and all of the administrative responsibilities. This is the most common transaction type, as the entirety of pension obligations are transferred


Implications of pension risk transfer for services and technology providers

Transferring pension liabilities to an insurer comes with many challenges. Providers have several opportunities to support insurance enterprises, recordkeepers, plan sponsors, and third parties involved in such transactions in the following key areas:

  • Technology systems: Insurers need support to transform their technology landscape to meet the increasingly complex market requirements, including data migration, fund transfer, benefits administration, contracts and provisions management, and pension administration for the full participant lifecycle.

Varying technology maturity levels among recordkeepers, insurers, and plan sponsors presents a big challenge. A service provider or platform provider’s solution can help with the entire process of transferring liabilities (sometimes along with plan termination) and all the relevant data, provisions, rules, funds, and critical participant details. This presents an opportunity for system integrators (SI) and platform providers to work together to efficiently manage the process lifecycle

  • Strategic partnerships: As this business achieves scale, insurers will strategically view this as an alternate revenue stream. Insurance firms can partner with technology and service providers to enable user-friendly onboarding, payment/annuity processing, automated query resolution, and analytics-based PRT transaction pricing, as well as building newer underwriting and actuarial capabilities for deciding PRT transactions’ premiums
  • Regulatory compliance: Technology and service providers need to assist insurers and sponsors in complying with the changing regulatory environment, varying state and regional taxation laws, and accounting nuances of different transaction types such as buy-ins and buy-outs
  • Cyber security: The significant amount of sensitive participant data being exchanged between recordkeepers, insurers, and sponsors’ systems poses substantial security risks. With the varying complexities and formats for different plan sponsors and record keepers, traditional file formats of participants’ data are difficult to maintain. Technology and service providers can securely manage the migration of pension data from on-premise systems to cloud, on-prem systems to other on-prem systems, and between different cloud environments


With the transaction volume increase in the PRT market expected to continue, technology and service providers have many opportunities to seize this underserved industry segment by leveraging their existing business expertise in the retirement and pension domain to build new solutions catering to this market.

To discuss pension risk transfer further, please reach out to [email protected] and [email protected].

Learn about the evolving digital requirements for the insurance industry in the blog, Reinventing the P&C Insurance Claims Value-Chain: Moving to the Claims of the Future Vision.

Demystifying Common Low Code Pricing Models and How to Choose the Right Platform | Blog

Selecting the right low code/no code pricing model is essential for enterprises to realize the many cost savings benefits these popular citizen-led development platforms offer to enterprises. Read on to learn about the various factors to consider to make the best choice for your organization. 

The case for no code/low code

The last few years have been rough for most enterprises, to put it mildly. The COVID-19 pandemic disrupted supply chains and forced many businesses to close their doors. The subsequent war in Ukraine and its ramifications, such as energy crises, supply chain disruptions, etc., left many business leaders struggling to make difficult decisions and pushed enterprises to quickly adapt to new ways of working.

With market uncertainty and macroeconomic impacts looming, enterprises are seeking innovative, cost-effective tech solutions to adapt to changing demands. Low code/no code platforms aim to bridge this gap of unrelenting business needs and the restricted bandwidth of IT teams through the rise of the citizen developer.

Plethora of low code pricing models – boon or bane?

The increasing popularity of low code/no code platforms can be partially attributed to the diverse pricing options that cater to various customer needs. The extensive options offer customers greater flexibility to select the most suitable pricing to meet their requirements, enabling them to leverage low code/no code platforms and remain within budget constraints.

While offering a wide range of choices provides flexibility to procurement teams, it also can make it confusing and difficult to choose the option that works best in each context. Let’s simplify the different scenarios.

How to choose the right low code pricing model for your organization

First, pricing options can be divided into these two categories:

Perpetual licensing – Customers pay a one-time fee to use an application indefinitely.

Subscription-based licensing – Customers pay a per user/application fee. This pay-as-you-go model has gained greater acceptance among enterprises, with over 80% of clients preferring it

Now, let’s compare the two most frequently used subscription-based licensing models below:

  • Application-based pricing, as the name suggests, is based on how many end applications the enterprise builds using the low code/no code platform. Typically, platform providers offer either per-application-based pricing or a bundled price for a predefined number of applications. Bundled plans are billed for the entire contracted bundle regardless of the actual number of applications the client deploys. For example, if a client opts for a 100-application bundle, the provider will charge for the entire bundle whether the client deploys one application or 99 applications.

When does application-based pricing make sense? Application-based pricing models usually are starting points for organizations to explore low code/no code platforms. It allows them to dabble with the trend without breaking the bank because it is easier to control the number of applications. For example, an organization might use application-based pricing when replacing an HR Management System with a group of three applications (for core HR, learning and development, and payroll) built on low code/no code platforms

  • User-based pricing is more focused on how frequently the application is used versus the number of applications built. Platform providers usually classify users into the following two categories:
    • Internal users – Individuals within the organization who use the platform to access or build and deploy applications. Usually, platform providers provide a lower band on minimum commitment for the number of internal users (For example, enterprises can’t contract for five internal users)
    • External users – These are named individuals or entities outside of the organization who interact with the applications developed using the low code platform

When does user-based pricing make sense? More mature enterprises that have had successful proof of concepts and are looking to scale this organizational capability will probably find user-based pricing more convenient. At this point, their objective typically will be to democratize low-code capabilities across the organization rather than to target specific use cases.

Keeping the number of internal and external users of low-code applications as one of the primary metrics for measuring success makes sense in scale-up mode. This model also allows enterprises to pay for actual usage rather than committing to a bundle of applications they may not deploy to production

Choose a pricing model that works for your organization

Low code/no code platforms are the superheroes that enterprises need in the current uncertain and rapidly changing business environment. However, to achieve the elusive return on investment (ROI) that all enterprises look for, selecting the correct platform from the plethora of available offerings is equally essential to choosing the right pricing model.

Selecting an appropriate pricing model hinges on multiple factors, including an organization’s goals, development level, and intended use cases. Failing to properly align these requirements to the available models and pricing options can lead to either overpaying (by double or triple) for the requirement or result in dissatisfaction due to feature or usage restrictions at the chosen price point.

If your organization needs help in determining the right low code pricing model and the market price benchmarks for your low code/no code platform, email [email protected] or contact [email protected] or [email protected].

Watch the Software and Cloud Pricing and Contract Negotiations: Keep Spend in Check webinar to hear Everest Group’s software pricing experts discuss recent pricing trends, key tactics enterprises use to keep their software spend in check, and the outlook for software and cloud pricing in 2023.

Reinventing the P&C Insurance Claims Value-Chain: Moving to the Claims of the Future Vision | Blog

Heightened momentum for technology-first and automated operations is elevating customers’ need for greater convenience, instant gratification, faster turnaround time, and more self-service options. Today’s digitally-immersed consumers have grown accustomed to doing business anywhere, at any time, and with any device, and this is shaping up the new normal of the insurance industry; transforming the insurance claims journey becomes a pivotal priority for Property and Casualty (P&C) carriers to meet demands for a customer-centric hyper-personalized experience driven by digital technologies. Read on to learn more about the zero-touch claims of the future vision and how to achieve it.

Leading InsurTechs with pure-play digital models are heating up the competitive landscape, making it imperative for traditional insurers to optimize their claims functions. An insurer can achieve future goals by accelerating the adoption of next-generation capabilities.

Amid the digital shake-up and rising demand for delivering an “Amazon-like” experience, insurance operations are plagued with workflow complexities caused by multiple intermediaries and legacy systems. Digital and emerging technology solutions can help insurers reshape the customer claims journey and improve turnaround time while reducing information leakages and fraud and delivering a superior customer experience.

Foundational pillars of a digital-claims future

To embark on a transformational claims journey, insurers need to go beyond traditional after-the-fact claims management, tap into the plethora of available data to unlock immense value, and focus on offering omnichannel experiences powered by intuitive digital technologies. P&C carriers will need to excel at the 3Es: experience, efficiency, and effectiveness.

Winning P&C digital claims offer a compelling digital experience and strengthen customer loyalty. Insurers can differentiate themselves by supporting each touchpoint in the claims journey – starting even before an incident occurs – with data, artificial intelligence (AI), analytics, and other emerging technologies—all while retaining the human touch.

By offering seamless omnichannel customer experiences across claims registration, disputes, timely process updates, final settlements, insurers can improve customer satisfaction and retention rates. This is crucial given that Everest Group’s research shows ~35% of P&C insurers’ priorities across claims management are focused on enhancing customer experience (based on an analysis of 60+ case studies involving claims modernization/transformation).

Insurers also need to drive superior efficiency by enabling data-driven and analytics-driven claims processing. This ensures focus on effective service delivery to reduce claims expenses, while improving claims handling accuracy and ensuring greater customer satisfaction.

Bridging the gap between current and future digital claims-processing

With innovation growing throughout the P&C insurance industry value chain, AI/Machine Learning (ML)-enabled tools eventually will help insurers redefine their roles from claim handlers to claims preventers. P&C carriers flourish when they embrace this mindset shift from a risk transfer to a risk mitigation model.

Insurers can unlock value in the claims industry by employing the internet of things (IoT) and telematics capabilities combined with the connected devices ecosystem and third-party data to identify red flags and alert customers of risks before any loss occurs.

Insurers need to look beyond mere cost-savings, accurately utilize the wealth of data they possess, and transform claims from a necessary back-office function into a source of competitive advantage and market differentiation. Below is a look at the key steps to reach a seamless claims settlement:

Exhibit 1:

Future Enables Carriers
Source: Everest Group

Rigid legacy systems for claims processing can present challenges for insurers and prohibit them from adapting to the evolving customer requirements and optimizing their operations. Legacy IT processes slow progress and innovation, eventually affecting the end-user experience that holds the potential to make or break insurers’ reputations. Taking a one-size-fits-all solution approach for different business lines, failing to adopt modular design principles, and having limited advanced systems skills add to the overall complexity and further weaken the ability of insurers to thrive in today’s competitive environment.

To attain a competitive edge, insurers require instant resolutions and digital experiences on the go. Leading insurers are harnessing the power of unified and custom low-code/no-code platforms with advanced AI and analytics tools to streamline claims processes, modernize systems, and build modern layers on top of existing legacy systems or other core platforms without involving time-intensive and expensive upgrades. This allows insurers to build reusable codes and design “plug and play” environments to deliver enterprise-grade solutions at speed and scale. Low code makes it easy for carriers to simultaneously focus on profitability, enhance customer experience, and fulfill the vision of balancing quick wins with strategic initiatives.

The need for digitalization of workflows and customer interfaces, convenient user journeys, reusability of components and faster configurations, cost optimization, and skill management are the top drivers fueling the demand for low-code/no-code technology for insurers in modernizing the claims process.

For instance, a leading global insurer used a low-code platform to create an intuitive and dynamic first notice of loss (FNOL) prototype application in just 90 minutes and transformed it into a fully functional mobile application for 2,000-plus users in four weeks, delighting customers.

Where do the opportunities lie?

A combination of agile insurance claims process/operating model transformation, adoption of advanced technologies and telematics, a skilled workforce with technical and domain expertise, and a connected partner ecosystem are the fundamental facilitators for the probable future of zero-touch claims.

In the future of claims processing, P&C insurers will be able to facilitate touchless claims decisions, accelerate payment settlements, assess indemnity obligations accurately, prevent fraud, and mitigate claims litigation losses.

Exhibit 2:

Industry Frontrunners
Source: Everest Group

Below are the key elements needed to move from the current state to claims of the future:

  • Acting quickly and flexibly: The rapidly changing environment is compelling insurers to keep up with the pace. Incumbents need to act fast, develop and launch new products, accelerate FNOL processing, and streamline claims management quickly to stay relevant. The need for agility is greater than ever. Adopting the latest technologies and processes will propel P&C carriers to move faster and separate leaders from laggards
  • Adopting advanced analytics and AI: Real-time sensor and IoT data coupled with AI and ML-backed algorithms will enable insurers to process claims efficiently and manage fraud without any human intervention. For instance, leading insurers are using an AI model embedded within the claims workflow to assign a complexity score to each claim based on multiple parameters and process all low-risk claims under a certain threshold. Low-complexity claims are routed for straight-through processing while high-complexity claims are sent to the right team depending on the claims adjuster’s specialization and availability, thus ensuring speed and accuracy
  • Transforming talent management strategy: Modernizing the claims journey requires relying on advanced technologies and a skilled workforce to manage emerging risks. Insurers need to enhance their long-term value proposition to attract skilled workers with technical and domain expertise
  • Partnering with digital claims solution providers: Building partnerships with solution providers can support carriers in extracting maximum value by utilizing the provider’s end-to-end digital claims solutions portfolio. Advanced capabilities across core functions include claims notification, adjudication, and settlement to fulfill P&C carriers’ needs across the claims value chain

To achieve the zero-touch claims of the future vision and keep up with leading competitors, insurers will need to invest in advanced technologies and drive value creation by taking a more proactive and customer-centric approach.

Successful insurers who can deliver a hyper-personalized experience will generate superior efficiency and leverage data and ecosystem insights to proactively detect fraud. Above all, this transformation improves the claims ratio by building predictive and preventive capabilities. Insurers who take these steps will emerge as industry frontrunners.

To discuss transforming digital claims, please reach out to [email protected], [email protected], and [email protected].

To learn more about technology-first, automated customer experiences, watch our webinar, Strategies for Customer Experience (CX) Success in an Uncertain World, for trends and recommendations on what to prioritize to deliver exceptional customer experience.

How the Recent Seize of First Republic Bank and the UBS Takeover of Credit Suisse Will Impact the BFS IT Services Market | Blog

The recent seize of First Republic Bank and UBS’ takeover of longtime rival Credit Suisse in a rushed, deeply discounted deal has reverberations across the banking and financial services (BFS) IT services market and on service providers. Read on to learn the looming risks and what to pay attention to in this blog.

The aftershocks of the collapse of SVB and Signature Bank, followed by the UBS-CS deal, are still being felt by the banking industry. The recent seize of First Republic Bank by JPMorgan with warning bells around PacWest has brought back memories from the 2008 financial crisis of whether this will be a one-off event or end up spreading like a contagion to the banking sector, especially the mid-market banking sector in the US. The stock of First Republic Bank had been steadily losing value in the last few weeks, and the massive deposit outflows put the bank at risk of failure. In a hurried weekend bidding, JP Morgan was the winner, while others like PNC and Citizens were unsuccessful. Right after the rescue by JP Morgan, shares in other mid-market banks started to see a slide. Commercial real estate loans have emerged as one of the main culprits pulling down loans value.

One thing that is becoming abundantly clear from these events is that customer confidence in their bank’s ability to protect their uninsured deposits is waning. It is when quarterly earnings are reported that the full picture is coming up on deposit outflows. While technology advancements have helped the banking industry, digital banking has only shown how fast deposits can be moved, which, coupled with social media panic, can accelerate a bank run. The implications for the overall banking sector, along with the technology and services industry, are multi-fold.

Implications for the BFS IT services market:

  • The market will see the return of large deals as bank consolidation will see the larger acquiring entity consolidate the supplier portfolios
  • Higher regulatory scrutiny, especially on mid-market banks, coupled with plummeting stock value, will put a dent in banks’ IT spend in the near-term
  • Cost-saving measures will be put in place, leading to job cuts and even branch rationalizations in the short term; job openings have already slumped to 6-month lows in the US

Interestingly, it raises the question of whether large banks are becoming too big to fail, leading to an even higher concentration risk for the banking sector. While the takeover of First Republic Bank is expected to bring gains to JP Morgan in the wealth management business, will banking get consolidated in the hands of a few? This will have repercussions on technology spend and the competitive nature of the industry. Already, the US was behind the curve on open banking adoption. The added risk of bank failures may halt these initiatives for some time.

The rescue by UBS of Credit Suisse marks the latest explosion across global financial markets in the ongoing banking troubles sparked by the collapse of Silicon Valley Bank and Signature Bank in the US, as we covered in our last blog.

Let’s take a look at the factors leading up to the Swiss brokered last-minute emergency takeover of Credit Suisse at a 60% discount.

Impact of the UBS-CS transaction

Credit Suisse was already battling concerns when its biggest annual loss since 2008 exacerbated the situation. Falling investor confidence eroded its share price to an all-time low, and top investors refused to give the bank more money citing liquidity concerns and regulatory hurdles.

Because Credit Suisse is considered one of the global systemically important financial institutions (SIFI), concerns about its future existence were particularly troubling. While the deal was made to prevent further meltdowns and stabilize the banking industry, risks of further blight spreading exist.

The merger of the two giants will have ripple effects on the BFS market, including:

  • Slowed growth in Europe: If the crisis trickles down to other banks and lasts long, revenue growth in the banking, financial service, and insurance (BFSI) segments will be impacted in the near to mid-term. Other related sectors (such as retail and telecom) also can be affected as seen during the Great Financial Crisis of 2008
  • Hits to other business segments: Areas such as asset and wealth management will be impacted by UBS’ decision to exit its wealth management business in some markets. Also, the move to wipe out the holdings of Credit Suisse bondholders has damaged Switzerland’s global reputation as a stable, predictable international asset manager
  • IT consolidation: With duplicating technology platforms and applications, the new entity will have to rationalize vendor portfolios and IT estates to realize significant cost synergies. Merging the two banks will require increased short-term spending on integration activities and consulting. Partners that can create modernization roadmaps for the combined entity also will be needed to drive long-term value
  • Job loss: UBS’s rescue plan for Credit Suisse may result in the loss of thousands of jobs at a time when the Swiss financial sector is already under tremendous stress due to the sudden takeover. The bank has slashed 4,000 positions so far this year
  • Robust risk controls: Credit Suisse’s risk management practices will need a major revamp given its troubled history of scandals and management controversies (Archegos and Greensill scandals in 2021) that led the Swiss Financial Market Supervisory Authority (FINMA) to order remedial action. The required measures include periodic executive board-level reviews of the most important business relationships for counterparty risks

Additionally, suppliers in UBS and Credit Suisse’s IT portfolio should brace for an impact when these mammoths consolidate.

UBS-CS impact on service providers

Traditionally, UBS and Credit Suisse have been huge outsourcing shops, with two or three major service providers controlling most of the work. Both banks have actively been reducing their outsourcing headcount and shifting their focus to insourcing and building capabilities in-house over recent years. This direction, coupled with the dynamics of the takeover, will lead to a rebalancing in the overall service provider portfolio across both banks. Here’s a look at the current landscape:

Picture1 9

Typically in mergers, providers that have big contracts with both entities stand to lose revenue because the spending by the merged entity will not be as large as it was under the separate relationships, unless they gain wallet share from competitors.

Suppliers that only provide services to Credit Suisse are at risk of having their portfolio consolidated and moved to UBS. However, providers who bring intellectual property or a niche capability to the table may be able to maintain the business through the consolidation.

We are closely watching how the events will unfold in the next few weeks. UBS has a stronger balance sheet and is insured against any losses by the Swiss Treasury, which should lead to stability but settling cultural, and IT alignment will take time.

How Credit Suisse’s wealth management business shapes up is another element to consider. Already clients and asset outflows have begun, with competitors trying to take a piece of this pie.

BFS market outlook

The road ahead will be marred by the following challenges:

  • Banking industry consolidation: While the sudden implosion of SVB delivered a deep blow to a mid-market sector, the Credit Suisse collapse may have further repercussions across continental Europe and lead to further industry consolidation and mergers. This also will impact the technology sector, which is already reeling from layoffs, falling stock prices, and diminishing funding for startups
  • Business segments and markets reprioritization: Providers will need to reprioritize their efforts and pivot their go-to-market focus on high-growth segments. A critical need exists to align with growth segments across lines of business, marquee clients, and the partner ecosystem
  • Margin resilience: Our initial hypothesis indicates that service provider contract pricing should remain stable. However, revenue realizations could come under pressure with a lag due to portfolio shifts and the heightened competitive intensity. The US dollar has strengthened in past cycles in relation to the Indian Rupee so the cross-currency impact should be positive for margins

For more insights on the BFS technology and IT services market or to discuss the UBS-CS deal, please reach out to Ronak Doshi, Kriti Gupta, or Pranati Dave.

Changing Dynamics In The IT And Engineering Services Market | Blog

Looking at the market for IT and engineering services right now reveals that companies are in a spending dilemma. They face high demand for these services, yet they look to cut back on spending because they are concerned about a possible recession. The strategies large companies are already putting in place to address this dilemma are changing the marketplace dynamics. Here is an overview of what your company needs to understand about these strategies.

Read more in my blog on Forbes

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