For life and annuity insurance CFOs, leveraging data analytics can help address an array of business challenges such as empowered consumers, talent gaps and operational disruptions in what some consider a difficult environment for their sector. And in the process, they could gain data-driven insights for the business and potentially catapult the finance organization from its traditional decision-support role to one that helps shape and drive strategy.

“Yet, because finance, in some ways, is built to support transactions rather than analysis and decision-making, finance organizations could be missing opportunities to analyze operational data to bring insights to the business and therefore reshape how the business views finance,” says Neal Baumann, a principal at Deloitte Consulting LLP.

Finance and Data Analytics: A Natural Fit

In many ways, the finance organization and data analytics make a natural pair. For instance, as analytics continues to gain prominence, so does the demand for rigorous information security.

“The transition of data from its operational origins to analytical models requires new controls to manage a different set of risks. This dynamic inherently boosts finance executives’ strategic contributions,” says Kevin Sharps, a principal at Deloitte Consulting LLP. And in the strictly regulated insurance industry, finance brings a discrete perspective as the steward of organizational information and external disclosures. Further, finance chiefs are well positioned to champion strategic partnerships with various stakeholders across the organization.

Armed with analytics technology and acumen, a finance organization can acquire the ability to interpret business results and variances across many functional areas through earnings-based, trend-based and controls-based metrics. For instance, margin analytics and reporting could help finance deliver timely and insightful decision support, while more precise roll-forwards could help it provide better forecasts and plans. Further, leading finance organizations can move beyond traditional analytics to develop predictive capabilities that support forecasting, simulation and optimization in the following ways:

—Advanced forecasting and customer behavior modeling. Advanced forecasting techniques using analytics and predictive modeling are replacing historical forecasting techniques that leverage sales trending. These advances empower companies to potentially shift from using drivers correlated to sales to using drivers related to expected future behaviors. With a finer understanding of the market, products, customers and other performance drivers, an organization can assess the future more accurately. “Predictive modeling techniques can promote a more meaningful interpretation of forecasting financial results, peeling back the layers of performance drivers,” notes Mr. Baumann.

—Simulation and modeling, with predictive exposure analysis. These capabilities can provide finance professionals with a deeper and wider lens into business challenges, and help them evaluate risk and financial exposures across a range of macro- and micro-economic situations. Because this modeling method reflects real-world conditions, it can serve to illuminate the implications of marketplace shifts.

—Optimization algorithms for in-force management analytics. Similar to customer behavior modeling, this type of analysis allows finance to gain a single customer view in order to anticipate future behavior. It assesses profitability drivers, income behaviors for annuity contract holders, drivers and implications of attrition, and the risk profile of L&A customers. The ability to identify potential challenges could potentially enable the organization to counteract undesirable outcomes.

Market Value Creation

Further, CFOs can leverage integrated analytics—using information from both internal and external sources—to better understand how the market values their organization and to reinforce market value creation concepts. For instance, in order to prevent value gaps, a firm must square internal perspectives of company value with external stakeholder expectations. “Within the organization, CFOs can play a central role in bringing to light cause-effect relationships of business decisions often made in silos—as well as the overall impact to business value creation vs. destruction,” says Wendy Huang, principal, Deloitte Consulting LLP.

CFOs often play an even more critical role in creating a strategy to communicate business performance to external stakeholders. “Using analytical techniques—such as sentiment analytics from social media platforms—to leverage insights, an organization can act more quickly to mitigate negative viewpoints and propagate positive ones,” says Ms. Huang. “Efforts such as these could serve to close the value gap and increase market value creation.” she adds.

Other potential benefits include:

—Greater profitability

—Improved predictability of business results with a distinct link between business outcomes and key performance indicators

—Enhanced capital efficiency with respect to reserving, based on improved understanding of expected mortality and value drivers

—Expanded forecasting and planning capabilities

—Increased capacity to evaluate potentially disruptive scenarios and respond nimbly to market opportunities and competitor threats

Leading the Conversation

Many CFOs already leverage data as a strategic asset to bolster business decisions, but adopting an enterprise-wide analytics model requires CFOs to lead the conversation and possibly advocate for the modernization of the technology infrastructure to support the analytical model.

Signs that an enterprise-wide analytics model might be needed include:

—Inordinate amount of time devoted to collecting, compiling and questioning data rather than interpreting outcomes and implications

—A cumbersome and time-consuming forecasting process that produces inconsistent results

—Inability to link financial and operational data

—Lack of data granularity, disparate data architecture and inadequate data governance

—Unpredictable or inconsistent performance across one or more key business metrics, along with a blurred relationship between forecast and plans

—A view of finance as the aggregator and messenger of information, not the source of strategic insights or driver of strategy

For the finance organization, gaining the analytics tools to shift from hindsight to foresight can provide a competitive advantage. Smarter technology can enable innovation in products and services, expansion into diverse channels and an enriched customer experience. It can also enhance risk-rated product pricing and performance analysis. “An analytics-based approach can improve operations returns by balancing a desire for new business and growth with appropriate risk considerations,” says Mr. Sharps.