Life and Annuity Insurance:Step up or be sidelinedHow CFOs generate value using analytical insights

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Table of contents

The marketplace 1

Analytical insight and value creation 2

Call to action 4

The life insurance and annuity carrier (“L&A”) industry is amidst a barrage of pressures on multiple fronts. Since the 2008 financial crisis, scrutiny of the financial industry is at a historical high. Stricter regulations surrounding financial disclosure and reporting, risk assessment, and capital management threaten substantial compliance risks. Insurance companies, specifically, face an uncertain regulatory environment. Three-quarters of CFOs polled cite industry-specific regulation as a chief impediment to growth.i

Life insurance ownership is at a 50-year low. Yet 50 million American households report a complete lack of life insurance or need for more coverage. Underpenetrated segments such as Generation X, 70 million strong, express a desire to purchase life insurance, worth $3.6 trillion over a single 12-month period.ii However, buyer expectations have evolved, particularly amongst Gen X, Gen Y, and Millennials.

The L&A industry has fallen short of US GDP for the past several decades due to prolonged low interest rates, capitally intensive annuities, and health care reform’s rising costs. While these obstacles are considered relatively short-term hazards, significant long-term industry threats loom. For consumers in need of insurance, including life, disability, and long-term care, current delivery models prove restrictive. Accustomed to social networks and mobile devices, users demand more flexibility and connectivity from distribution models and customer interactions. Buyers seem quite at ease with conducting complex transactions online. Nearly three-quarters of customers would consider buying insurance products from non-insurer companies, including 23% who would purchase from online providers, such as Google and Amazon.iii As power shifts to the consumer, L&A insurance companies struggle to remain relevant.

Further internal issues plague the industry. Severe talent gaps abound. Existing, traditional skills alone are no longer enough. These capabilities differ fundamentally from in-demand skills such as business partnering, outsourcing, shared services models, centers of excellence, actuarial, and analytics. Further, the interaction lifecycle is riddled with costly operational disruptions from anemic efficiency and productivity plays and poor talent recruitment and development. A pattern of underinvestment in legacy platforms compounds the problem by impeding data management. Legacy systems lack the agility to accommodate fast-paced distribution, underwriting, and advanced analytics needs.

Foreword

i Top regulatory trends for 2014 in insurance, Deloitte Center for Regulatory Strategiesii Life insurers cast the net wider for growth: Enter Gen X, Deloitte Center for Financial Services; Trillion Dollar Baby – Growing Up, The Sales

Potential of the U.S. Underinsured Life Insurance Market. LIMRA, 2011. Note: As of 2013, Gen X is generally defined as the population born between 1965 and 1981, Gen Y between 1982 and 1993, and Baby Boomers between 1946 and 1964

iii The Digital Insurer, Accenture 2013 Consumer-Driven Innovation Survey

Life and Annuity Insurance: Step up or be sidelined 1 How CFOs generate value using analytical insights

The marketplace

Fault for stagnant growth of the life insurance and annuity carrier industry belongs to myriad events; among them, intense scrutiny of the financial industry in historic proportions, substantial compliance risks due to stricter regulations, and an uncertain regulatory environment. Customers, keen on mobile devices and social networks, expect delivery models with more flexibility and connectivity. As power shifts to the consumer, L&A insurance companies battle for relevancy. Internal obstacles further exacerbate the struggle. Operational disruptions and talent gaps permeate. Organizations are short on in-demand skills such as business partnering, outsourcing, and analytics. The industry is under attack on multiple fronts, and business as usual is, in this day and age, a dire prospect.

Challenges are opportunities. To win the war, Finance leaders can assess eight critical areas: • Growth and capital allocation• Distribution model transformation• Regulatory and compliance obligations• Analytical insight and value creation• Business change portfolio• Finance operating model• Business partnering• Finance talent

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Analytical insight and value creation

Measure, monitor, and predict business outcomes and drive decisions using data analyticsTo survive and thrive, Finance chiefs must address business challenges by championing and leveraging the unique lens analytics provides. As an enterprise’s analytical sophistication increases, its perspective evolves methodically from hindsight to insight to foresight. Along with prolific web, mobile, and social platforms come opportunities to uncover insight about customer behavior, reveal trends, and optimize the decision-making process. Data interrogation and visualization tools help pinpoint present and historical key drivers, as well as identify potential improvement opportunities. Effective use of data analytics also enhances in-force business performance.

Finance is distinctly positioned to deliver performance management insight as the conventional consumer and collector of data. Yet, since Finance is traditionally architected for the transaction state, not the analytical one, opportunities exist to further leverage proven and emerging methods to streamline data management and analytical use of operational data. Each evolutionary step must be sound before progressing onward (e.g., historical reporting must be reliable in order for insights to be trusted). It is Finance’s responsibility to play a leadership role in enabling a strategic enterprise information platform. Data-driven insight catapults Finance from traditional decision support to explaining, shaping, and driving strategy with accuracy.

The Insurance Value Chain – Finance Business Partnering Scope

• Which new markets and corresponding products should we target and how should we price?

• How will decisions affect us in the longer term?

• What are the customer preferences for distribution and corresponding effects on profitability?

Strategy

Finance

IT, Risk Management

Other (e.g., Legal, HR)

ProductDevelopment Marketing Distribution Underwriting Customer Service

PolicyAdministration

ClaimsAdministration

• How do we best provide insightful customer reporting?

• Which customers are most profitable?

For illustrative purposes only

Life and Annuity Insurance: Step up or be sidelined 3 How CFOs generate value using analytical insights

As analytics gains prominence amid the data revolution, so too does the demand for preemptive, rigorous, next-generation information security. Data’s transition from its operational origins to innovative analytical models requires new controls able to manage a different set of risks. This dynamic inherently boosts the strategic contributions of Finance executives. The steward of enterprise information and external disclosures in the strictly regulated insurance industry, Finance brings a distinct perspective. Further, Finance chiefs are well positioned to champion strategic partnerships with various stakeholder groups.

How can Finance leverage analytics to provide value? Value-added capabilities. Armed with analytics acumen and current analytics technology, an organization gains the ability to interpret business results and variances across many functional areas through earnings-based, trend-based, and controls-based metrics. Margin analytics and drill-down reporting help deliver timely and insightful decision support. More precise and granular roll-forwards help provide better forecasts and plans. Pacesetter organizations evolve beyond traditional analytics to develop predictive capabilities that support forecasting, simulation, and optimization.

Advanced forecasting—customer behavior modeling. Advanced forecasting techniques leveraging analytics and predictive modeling are replacing historical forecasting techniques using sales trending. These advancements empower companies to potentially shift from using drivers correlated to sales to using drivers related to expected future behaviors. With a more acute, granular understanding of the market, products, customers, and other performance drivers, an organization can assess future results more accurately. Predictive modeling techniques promote a more meaningful interpretation of forecasting financial results, peeling back the layers of performance drivers. Similar logic can be applied to gain a better handle on in-force or newly acquired blocks.

Simulation and modeling—predictive exposure analysis. This capability offers a deeper and wider lens, evaluating risk and financial exposures across a range of macro- and micro-economic situations. Because this modeling method reflects real-world conditions, it enhances accuracy and provides meaningful insight surrounding the implications of marketplace shifts.

Optimization algorithms—in-force management analytics. Fundamentally similar to customer behavior modeling, this type of analysis is marked by the capacity to drill down to a single customer view in order to anticipate future behavior. It assesses profitability drivers, income-taking behaviors for annuity contract holders, drivers and implications of attrition, and risk profile of L&A in-force customers. The ability to identify potential challenges enables an organization to anticipate and nimbly counteract undesirable outcomes.

Further, today’s leading CFOs leverage integrated analytics—using information from both internal and external sources—to reinforce Market Value Creation concepts. A firm must align internal perspectives of company value with external stakeholder expectations in order to prevent undervaluation and value gaps. Within the organization, Finance chiefs play a central role in driving integrated analytics across the enterprise value chain to enhance understanding of cause-effect relationships of business decisions often made in silo, as well as the overall impact to business value creation vs. destruction. External to the organization, Finance chiefs often play an even more critical role in architecting an effective business performance communication strategy with external stakeholders. When an enterprise uses leading technology and analytical techniques, such as sentiment analytics from social media platforms, to effectively leverage insights gained from mining externally available information, the organization gains the ability to mitigate negative viewpoints and propagate positive ones. Such efforts serve to close the value gap and increase Market Value Creation.

Potential benefits • Increased profitability• Improved predictability of business results with a distinct

link between business outcomes and KPIs• Ability to more closely value and plan for mortality and

other financial impacts of acquired blocks• Enhanced capital efficiency with respect to reserving,

based on improved understanding of expected mortality/value drivers

• Expanded forecasting and planning capabilities• Boosted capacity to respond nimbly to market

opportunities and competitor threats

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Triggers that indicate action may be necessary• Inordinate amount of time devoted to collecting,

compiling, and questioning data rather than interpreting outcomes and implications

• Forecasting process (e.g., DAC roll-forward) considered cumbersome and time-consuming with inconsistent results

• Inability to link financial and operational data• Lack of data granularity, disparate data architecture,

and inadequate data governance• Performance is unpredictable and/or inconsistent

across one or more key business metrics with blurred relationship to forecast/plans

• Finance deemed as the aggregator and messenger of information, not as the source of strategic insights or driver of strategy

Call to action

Far-sighted Finance leaders leverage data as a strategic asset to galvanize the enterprise and bolster business decisions. Adopting an approach steeped in analytics requires CFOs to lead the conversation. These Finance chiefs drive understanding of predictive analytics’ pervasive benefits and rally buy-in of top executives. They champion the implementation of a strong top-down mandate, coordinating across lines of business, functions, and IT groups. At the same time, they design an integrated enterprise-wide analytics model to evaluate the impact of potentially disruptive scenarios. Collaboration is essential in order to develop a structured data governance organization able to sustain data management rigor and promote stewardship of data and information. CFOs also advocate for modernization of the current technology infrastructure, equipping it to support the defined analytical model.

The ensuing shift from hindsight to foresight can be a transformative competitive advantage. Smarter technology enables product and service innovation, efficient expansion into diverse channels, and enrichment of the customer experience. It enhances risk-rated product pricing and performance analysis. An analytics-based approach can improve operations returns by balancing a desire for new business and in-force growth with appropriate risk considerations.

Life and Annuity Insurance: Step up or be sidelined 5 How CFOs generate value using analytical insights

For more information, please contact:

Neal BaumannPrincipalDeloitte Consulting LLPnealbaumann@deloitte.com

Kevin SharpsPrincipalDeloitte Consulting LLPksharps@deloitte.com

Wendy HuangPrincipalDeloitte Consulting LLPwendyhuang@deloitte.com

David JachymSenior ManagerDeloitte Consulting LLPdjachym@deloitte.com

Rich RoremPrincipalDeloitte Consulting LLPrrorem@deloitte.com

Larry MannoPrincipalDeloitte Consulting LLPlmanno@deloitte.com

Quinby SquireSenior ManagerDeloitte Consulting LLPqsquire@deloitte.com

Jason MortonPrincipalDeloitte Consulting LLPjamorton@deloitte.com

Contributors

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