Transformation target:
a future-fit finance operating model

^{Transformation target: a future-fit finance operating model}

These six paradoxes frame the significant challenges CFOs face as they try to modernize their systems and enhance their capabilities for the future. That’s why finance transformation plans should address them directly and holistically. The following multi-dimensional target operating model for finance in the insurance industry provides a roadmap for navigating these challenges.

Drawn from our work with all types of insurers around the world, the operating model reflects the interconnected nature of insurance operations. Better service delivery needs better processes, which require powerful systems and rich data, with talented people and well-designed controls ensuring effective, efficient and compliant performance.

While the elements of the target operating model can be viewed individually, finance transformation strategies should address them holistically, with the goal of establishing highly integrated and intelligent operations closely aligned to the most urgent needs of the business.

Service delivery model

How finance services are delivered

People

How people are organized, managed and developed

Process

How processes work and connect

Technology and systems

How tech enables processes and functions

Data and reporting

How data is used and leveraged from source to report

Governance and controls

How oversight and risks are managed

^{Service delivery model}

Successful finance transformation programs typically aim for agile, adaptable and scalable service delivery models that are responsive to business needs and able to deliver forward-looking and high-value services (e.g., scenario planning, predictive analytics). High-performing finance functions typically combine sourcing options, balancing localized support and centralization through shared service centers and centers of excellence. Similarly, insurers embrace offshoring and outsourcing to varying degrees.

Effective sourcing relationships with external partners can assume many different forms. They may feature high-efficiency transaction processing and administrative services, focus on discrete functional activities (e.g., reporting, actuarial modeling) or provide access to specialized expertise and advanced technology. The key is to understand the benefits and drawbacks of each approach relative to specific processes, weighing efficiency gains and cost reductions against potential loss of institutional knowledge.

Imperatives to move forward

Define and communicate a vision of finance’s unique responsibilities and critical services and how it’s integrated with other business activities.
Understand and apply lessons learned from transformation in other functions (e.g., claims).
Identify those processes and outputs where it’s worth striving for excellence and where efficiency and cost reductions are the most important objectives.
Determine which services are best suited to centralized delivery and third-party support and which must be delivered close to the business.

^People

Maximizing human capabilities is necessary to move finance from a role focused on reporting and stewardship to one centred on strategic partnership and value creation. The most effective finance teams of the future will be notable for a mix of skills and talent — core accounting and actuarial expertise, data science, strategy, technology, data analytics and market intelligence. Diverse groups will work together more collaboratively and creatively, engaging directly with business leaders to provide insights and tailored guidance, all in pursuit of growth, innovation and higher performance.

Recruiting and hiring are not the only variables in the talent equation. Managing people and teams for greater engagement, increased collaboration and long-term development are other priorities, and may necessitate closer collaboration between finance and HR leaders.

Imperatives to move forward

Map how finance staff will use technology and data to advise the business, influence decision-making and contribute value.
Define re-skilling needs for specific roles, empower workers with tools and training, and motivate them to evolve from process expertise to strategic skills.
Redesign the employee experience and work environment to foster collaboration, creative experimentation and fresh thinking.
Link training and development programs to career progression.
Create new compensation and incentive models aligned to new behaviors and ways of working.
Adjust leadership styles to reflect AI’s growing role in finance positions.

^Process

To transform service delivery and create more strategic links to the business, finance processes must be made leaner, faster and more integrated. Automating repetitive activities and eliminating manual work will enable teams to focus on high-value services and analytical tasks. The good news is that these steps can amplify returns on investments in technology and data.

Operational models can be designed to maintain reliable and efficient service delivery, leveraging the features and functionality of advanced systems. External benchmarking can help set targets for speed, accuracy and productivity of standard processes. Further, centralized processes should be linked with local ones and those overseen by external partners. Business users and other stakeholders can contribute to initial process design, as well as ongoing modifications, so finance services meet their needs and timelines.

Imperatives to move forward

Use a wider ecosystem, including third-party service providers, to provide continuity while developing new processes.
Streamline, centralize and automate end-to-end processes to meet industry standards for efficiency, scalability and agility.
Design processes based on systems thinking, best practices research, benchmarking data and external insights to support the full range of business needs.
Establish clear ownership of shared and local processes.

^{Technology and systems}

Technology underpins service delivery models and core processes, providing the foundation for operational excellence and freeing people to focus on high-value tasks. Modernized systems provide many advantages – automating low-value tasks, user-friendly features that accelerate adoption, rapid integration of AI tools, instant support for complex finance tasks and flexibility for evolving market demands and regulatory requirements. They also shorten the path to integrating acquisitions and launching new products.

The IT environment must allow for standardization, secure connectivity and modular adaptation. Merging duplicative systems on core platforms can add stability and strengthen protections for customer data and other valuable assets. Such platforms facilitate safe, seamless connectivity to third-party systems and external data sources. Legacy systems that are costly to support (e.g., policy administration) can be retired or wrappered with new capabilities to retain access to business-critical data and functionalities.

Imperatives to move forward

Chart a roadmap to a rationalized and renewed IT environment, based on cost, user experience and enterprise integration considerations.
Build momentum by integrating AI tools with existing systems, and modeling how AI can transform core processes.
Prioritize centralization and standardization for finance systems, maintaining connectivity with core ERP/EPM systems.
Explore the full range of sourcing options, including managed services, to access advanced technology and manage IT budgets.

^{Data and reporting}

Data – ranging from raw information to structured reports and analytical insights — remains the finance function’s stock in trade. Without it, financial reporting, regulatory compliance and actuarial projections are impossible.

Data-centric finance functions are best positioned to generate value through analysis and foresight. The more granular and actionable the insights, the better; while it’s useful to know if a product is profitable, it’s even more valuable to understand why it is more profitable in some markets and how to make it attractive to certain types of customers.

Finance can deliver such insights, provided strong data management practices are in place. These capabilities provide a foundation for a culture of analytical thinking and data-driven decision-making in the service of innovation, growth and improved performance.

Imperatives to move forward

Implement future-fit data platforms that support the use of AI and predictive analytics.
Harmonize and unify data across systems, regions and business units.
Map which data (including external and alternative data) feeds into capital, risk and pricing models — and assess its reliability, quality and accuracy.
Prioritize ease of data segmentation for analysis and reporting by business unit, geography and product line.
Identify each “golden source” of data and ensure owners are sufficiently equipped and resourced to manage and secure it.

^{Governance and controls}

CFOs know that effective governance and controls are vital to protecting the business from all sorts of risk (e.g., data loss, reputational harm, non-compliance). Reporting errors can lead to lower confidence among investors, as well as regulatory fines.

However, the need to embrace new technology, adopt new ways of working and accelerate innovation can be difficult to reconcile with rigid frameworks and controls. The ideal state is a clear, simple governance framework that’s well understood and embraced by the entire business, including all product lines, regions and jurisdictions. That vision is becoming a baseline necessity for insurers and will only become more important in the future as insurers:

Face intensifying competition from non-traditional and more nimble rivals.
Adopt AI more deeply and extensively across the business.
Build a broader finance ecosystem, with more strategic partners, managed services providers and other third parties.

Imperatives to move forward

Harness system-automated controls and testing, including AI-powered analytics tools, to provide a control baseline.
Subject AI development to appropriate governance, especially around performance evaluation and the use of training data.
Apply the governance techniques of disruptors and start-ups (e.g., establishing ring-fenced environments with innovation-friendly governance and controls).
Establish clearly documented ownership and responsibility for static data, mobile data and reporting processes.