How a finance data strategy can transform the insurance CFO’s role

By adopting a unified approach to finance data management, insurance CFOs can build a robust financial ecosystem and drive long-term value.

The following individuals made valuable contributions to this article:

• Chris Cooper, Partner, Insurance Finance Transformation, Ernst & Young LLP
• Rosemarie Sansone, Managing Director, Strategy, Transformation, and Advanced Technologies, Ernst & Young LLP
• Riayn Lavoie, Senior Manager, Insurance Finance Transformation, Ernst & Young LLP

In brief

• Insurance CFOs are grappling with uncertifiable financial data, fragmented operational-financial linkages and inefficient reporting and analytics.
• By harnessing data as a strategic asset, insurance CFOs can transform their role in the enterprise.

Faced with new entrants, the advent of artificial intelligence (AI) and mounting economic pressures, the insurance industry is experiencing unprecedented challenges that significantly impact the finance function. To address this evolving landscape, today’s CFO should embrace a new approach, transitioning from the traditional roles of curator, guardian and steward to that of a strategic partner who serves as the arbiter of certified data.

Data lies at the heart of the complex problems faced by CFOs

• Insurers are increasingly investing in data architecture in the front and middle office. However, finance departments are struggling to articulate their requirements for data capture and data services, which can limit the effectiveness of these investments. As a result, finance teams often find themselves engaged in data quality checks, reclassifying entries and linking affiliate data to support profitability segments, which underscores the need for a well-structured finance data strategy.

• Products are becoming increasingly divergent, with a growing personalization of certain offerings, which places substantial pressure on finance teams when discussing profitability. Creating effective planning and profitability analysis requires more and more data to support these efforts.

• As AI is gaining traction within the finance function today, it is set to become a critical driver of efficiency, insight and strategic value over the next three to five years. This shift requires a robust foundation of well-structured, certifiable and connected data, including financial data, operational data, planning and forecasting data, clean master data, and potentially external unstructured data that can be easily integrated. Moreover, having granular levels of financial transaction data is essential for optimal use, as training AI with more atomic-level data allows for easier diagnosis of differentiation in flows and various characteristics in reference or affiliate data.

To navigate these challenges, a robust finance data strategy and partnership between the CFO and chief data officer (CDO) are essential. With a unified approach to finance data management, the future CFO can add value and create a robust finance data ecosystem. This includes insisting on the rationalization of general ledger structures, which determine how segments should be defined in relation to the account treatment of products. Additionally, the CFO should approve the use of operational books of record for risk, regulatory and finance purposes, further enhancing the integrity and utility of financial data.

Together, these zones create a comprehensive framework that enhance financial operations and support informed decision-making.

Standardizing data for consistency and clarity

To successfully implement the F-CIM, CFOs should champion the standardization of data formats across finance areas, including actuarial, treasury, investments, and financial planning and analysis (FP&A). Standardized data formats ensure that everyone in the organization is using the same definitions and structures, which reduces confusion and errors in financial reporting.

CFOs should also push for better control over data services to maintain data quality and improve reporting processes. Assigning specific teams or individuals to manage data services creates accountability and helps maintain high standards of data quality.

Integrating emerging technologies, including AI and machine learning, is another critical step. By automating data analysis, CFOs can gain insights more quickly. These technologies can help refine underwriting processes, execute predictive analytics and tailor products to meet customer needs.

With the F-CIM framework in place, CFOs can gain much-needed agility. This includes the ability to formulate requirements for other investments across finance, integrate data for mergers and acquisitions (M&A), and capture data requirements for Know Your Customer (KYC) and business event-related products.

The F-CIM framework is more than a tool; it’s the backbone to a sustainable finance data ecosystem. By embracing a unified finance data management approach, CFOs can redefine their role in the enterprise and deliver value through real-time insights, proactive decision-making and strategic risk management.