The future of insurance

 The future of insurance inance A strategic new partnership role is poised to be the future of insurance finance Today’s insurers are enduring a perfect storm of converging challenges amid the global pandemic’s sudden disruption and the ongoing impact of game-changing digital technologies and automation capabilities. The industry is facing significant changes, including delivering competitive new business models, meeting evolving customer and employee expectations, recruiting new skills and managing changing regulatory demands. 

 Welcome to the new reality — and with it a significant new role for the insurance finance function. Finance is poised for a shift from its traditional reporting, monitoring and planning duties to a significant new role as a strategic partner to the business — driving informed, data-based decision making and helping to execute strategy, maximize growth and enhance profitability. We believe the new reality means finance is no longer about ‘the speed of the close.’ Insurers are now looking for a finance function featuring scalability and integrated capabilities that can deliver crucial new business insights and enhanced performance. 

 Doing ‘more with less’ — the way forward The journey forward is expected to include a new capacity to ‘do more with less’ and underpinning this transition will be modern workforces and new skills that can help drive innovation, agility, growth and future profitability. Accomplishing more with less on the road ahead will require: — A strong data foundation that will be key to enhanced efficiency and new automation capabilities; — An integrated design across all metrics, between actuals reporting, planning and forecasting, ideally delivering consistency, clarity and the benefits of automation; — Leveraging emerging technologies such as cloud capabilities for seamless integration across data and systems architectures. Unlocking capacity to develop new capabilities Create capacity to do more for less 1. Strong data foundation 

 With these foundational elements in place, insurers can look to develop new capabilities that include: — Driver-based insights — Helping to ensure that underlying drivers of business results are fully transparent, both to financial and actuarial teams, and the broader business team. This is considered a critical enabler for enhanced value creation. — Predictive and prescriptive analytics — Once a driver based approach has been embedded, it will evolve and enter a new frontier in helping to predict drivers and modelling to identify optimal results. — New ways of working — A shift from historical reporting and traditional approaches to a new focus on data analysis and informed decision making. Develop new capabilities 4. Driver-based insights Focus on driving an integrated data architecture — which is a key foundation to automation and delivering efficiency and can help make integration of new subsidiaries more efficient. 2. Integrated design An integrated design across all metrics, between actuals reporting, planning and forecasting — this can facilitate automation and analytical capability. 3. Leverage emerging technology Automation cannot be achieved with RPA and AI technology alone — an integrated design and seamless integration with the data and systems architecture is a key enabler. Modern workforce Finance can make the drivers transparent to the business, helping to drive a stronger partnership to achieve results.

 It is a critical enabler for adding more value. 5. Predictive and Prescriptive analytics Once a driver-based approach has been embedded, it can evolve and enter a new frontier in helping to predict drivers and modelling to identify optimal results. Core skills like accounting and actuarial are still required, but the business needs finance to have a deeper business understanding, commercial acumen and an ability to communicate and drive change. 1 | The future of insurance finance 6. New ways of working To realize the value of data and systems solutions, finance teams should also change how they think about data and work with it. © 2021 Copyright owned by one or more of the KPMG International entities. KPMG International entities provide no services to clients. All rights reserved. Thinking through the ‘art of the possible’ What could the finance and actuarial function of the future look like? Consider these revealing cases that demonstrate aspects of the ‘art of the possible’ and finance’s future value proposition. Business decision support 

— Providing data-driven insights and analysis in an agile ecosystem enables informed decision-making by business units and product teams. A modern workforce can enable small multi disciplinary ‘virtual’ teams to be formed around specific business problems or initiatives, such as new product delivery. Business resources lead the work, but members of the finance team provide insights, analysis and discipline to support all decision making. A consistent and unified data and systems foundation can provide rapid access to the financial data needed for data-driven analysis. Visualization tools and embedded machine learning can enhance the ability to quickly perform investigations, respond to queries and perform ‘what-if’ analysis. Who is doing this well today? Finance joining agile virtual teams to support decision making has already been adopted successfully by some insurers as well as major global organizations in the consumer goods sector. It has fostered a ‘fail-fast’ mindset, allowing new ideas to be evaluated and successful strategies to be quickly developed amid changing environments and marketplace challenges. Driver-based early warning detection — Integration of metrics, data and systems can provide timely new insights across the business. An integrated data architecture, combined with automated predictive analytics, can allow f inance to provide both early warning on emerging issues and proactive financial management. Data is automatically collected, and automation can allow for forward-looking analysis and immediate forecasting. Automated early warning triggers and anomaly detection can raise a red f lag for the business to respond. Ongoing updates are automatically pushed out to the business and finance can support analysis and appropriate responses. Who is doing this well today? A major global brewer has successfully implemented an organization-wide dashboard of live operational KPIs from its facilities worldwide. The integrated real-time KPI reporting allows for adverse trends to be detected early and for preventative action to be taken quickly. Wide dashboard access has also encouraged gamification as manufacturing sites compete on efficiency metrics. Prioritization and funding — Providing data-driven insights and analysis can position leadership to make informed business decisions when deploying limited capital to drive growth and profitability. Shifting from a ‘project-centric’ mindset to a customer-led ‘product-centric’ mindset can also position leadership to deploy limited resources toward priority objectives and help reduce costly duplication of efforts. Data-based insights will help foster synergies and harmonize delivery efforts, thus helping to reduce capital investment. Who is doing this well today? Some financial services companies are already applying agile funding principles 2 | The future of insurance finance that enable them to go to market more rapidly with new products and enhanced customer experiences. This has created less redundancy and costly duplication of efforts across multiple business units and product lines. Embarking on the ‘journey’ The journey for insurers in today’s new finance reality will require a significant shift from a ‘task-based’ to a ‘capabilities based’ orientation. Businesses are typically working on spot solutions to evolve siloed financial processes and integrate strategic planning, budgeting, forecasting, teams and capabilities. Unfortunately, significant duplication of efforts can result during processes such as data extraction, manipulation and analysis, while limited time is dedicated to deriving informed data-based insights and generating the advantages of predictive capabilities. What we see in the majority of finance and actuarial functions today is that a lot of effort is associated with the production of financial reporting and planning. It involves manual tasks associated with the production of numbers and exists in a series of silos within the finance function. This often creates additional manual efforts around reconciliation and duplicated checking of results. As finance and actuarial functions move into the future, we expect to see an increasing focus on the automation of much of this manual production activity, which will help create the capacity to deliver on the capabilities surrounding the distribution of insights into the business. Additionally, more integration of data and alignment of metrics between the various areas of the finance and actuarial functions (valuation, planning, forecasting, capital) can help eliminate significant effort around reconciliations and provide a stronger foundation for the analytical capabilities that would allow finance to support business decision making. Getting it right begins with a consistent data and systems architecture. Building an integrated finance and actuarial data and systems architecture is a core capability in helping to deliver agile financial reporting that’s fast and cost efficient. As finance and actuarial functions move into the future, we expect to see an increasing focus on the automation of manual activity to help create the capacity to deliver on the capabilities surrounding the distribution of insights into the business. © 2021 Copyright owned by one or more of the KPMG International entities. KPMG International entities provide no services to clients. All rights reserved. Modern data and systems architecture can allow rapid expansion and efficient incremental change. Businesses adopting a modular architecture and cloud-based infrastructure can experience easier future expansion. By reimagining how to deliver data and systems, businesses can adopt an agile, prototyping-based delivery model. This can allow you to implement with smaller teams, improve quality of delivery and reduce delivery risk. However, it does require the adoption of a philosophy of accepting failures during prototyping and learning from them. Success will require a seamless ‘data backbone’ to provide one source of data that helps drive speed, standardization and consistency. Ultimately, the right data and systems architecture and ‘data backbone’ should integrate all business data sources and domains beyond the finance and actuarial functions, including: —Product development and pricing —Underwriting, marketing and sales —Operations and policy management —Claims management —External data sources Linking diverse data sources can unlock better driver based analysis, timely insights and proactive responses. How to integrate? Keep in mind that data does not need to be compiled within a single monolithic database. The key is to ensure that data can be linked through a common interface. Finance can certainly act as a catalyst to kickstart the development of an integrated data backbone and will ideally take a leading role in controlling sensitive financial information. In other aspects, finance can be an equal ‘data citizen’ — drawing on diverse data sources and enabling other business functions and processes to do the same. Going forward, we believe automation and artificial intelligence will play a key role in enabling this improved environment. KPMG professionals estimate that through automation it is possible to have 60 to 70 percent of internal controls automated. This will play a critical role in pricing and underwriting, reserving, reporting and decision making. Natural language process Artificial intelligence Advanced search Data ingestion and integration Understanding reinsurance/industrial line contracts — Check if the contract is in line with UW guidelines and money laundering requirements — Check if the system encoding is complete e.g. all risks and involved parties are included — Self-correction: Enter data fields identified and not already encoded Enhancing control over reserving quality Checking the ability to reconcile between different reporting bases Enhancing governance over decision making with additional scenarios — Capital, IFRS/US GAAP and local GAAP — KPIs — Qualitative explications versus KPIs and quantitative figures Artificial intelligence Natural language processing Learning algorithms Artificial intelligence Pricing/Underwriting Reserving Decision making Reporting — Data quality and consistency checks and triangle creation — Quality of assumptions and inclusion of latest incidents — Logical checks input data to results — provide suggestions for detailed reviews — Enhanced scenarios with more variables and their interactions — Show complex interactions, e.g. taking more risk and profit/capital impact Learning algorithms Automation & AI — Can enable an improved control environment It’s estimated that 60–70 percent of internal controls will be automated in 5–10 years Source: The Future of Finance, 2019 KPMG LLP. 3 | The future of insurance finance © 2021 Copyright owned by one or more of the KPMG International entities. KPMG International entities provide no services to clients. All rights reserved. Taking a ‘hypothesis-driven’ approach Realizing the value of a data and systems solutions will also require insurers to adopt a hypothesis-based and data-driven approach to analysis and insight development. This approach can ultimately support finance’s important transition from value analysis to value enabling in the eyes of the business and external stakeholders. When designing and implementing the future solution, we recommend following four key steps: Form a hypothesis: Start by developing a hypothesis on your future-state reporting and analysis, and work back to form a view on the data and data structures needed. Focus energy on data that adds the most value. Test: Develop prototypes of the elements of the solution through an iterative process using past data and incorporate ongoing feedback into the subsequent iterations. Implement: Bring the solution into production with live data. Observe and refine: Ensure ongoing improvement and refinement of tools to adapt to changing needs. When using the solution to develop insights, we recommend following these key steps: Form a hypothesis: Envision potential future scenarios; for example a small number of sales agents are reducing profitability through excessive churn of clients. Test: Identify the data domains needed to test the hypothesis, including sales agent data, policy and policyholder data, and policy profitability metrics. Develop a model to provide early warning indicators for excessive churn and define actions to be taken. Implement: Create the model and visualization, monitor KPIs and take the appropriate action as needed. Observe and refine: Implement a feedback loop, observe the effect of your actions and refine your model, KPIs, actions or initial hypothesis. A modern workforce for new ways of working As noted, we believe doing more with less is the way forward, so do not underestimate the critical importance of how the traditional finance workforce should change. We believe the future state requires a fundamental redesign of the finance organization in order to establish and foster close collaboration among teams across the business. We expect that the finance function of the future will require a revaluation of teams and their current roles. Managing how people perform and interact with technology such as automation and AI will also be crucial. Ultimately, we believe the future state requires a fundamental redesign of the finance organization in order to establish and foster close collaboration among teams across the business, with a clear focus on capability delivery. Collaboration teams will be needed as finance organizations become more agile, allowing resources to move between teams to deliver enhanced value. Along the way, phased deployment will likely be necessary, moving to the future state in phases as new capabilities emerge. As technology modernization occurs, teams should be reorganized as needed to meet evolving requirements or challenges. Core skills like accounting and actuarial will still be required — but the finance function of the future will possess a deeper business understanding, greater commercial acumen and the ability to communicate and drive change. In conclusion, we believe the new reality has arrived for today’s insurers and future-focused organizations are already moving forward to reshape the finance and actuarial functions. The future is positioned to be data driven and automation enhanced — and there is little time to delay for businesses that want to remain relevant, competitive and profitable in a fast-changing environment. Going on this journey will enable finance functions to remain relevant and responsive to the demands of the front office. Finance can become a true business partner and help deliver profitable growth for your organization.