Beyond Functional Transformation in Insurance Refocusing on Market Agility by Improving Cross-Functional Effectiveness

Transcription

1 Beyond Functional Transformation in Insurance Refocusing on Market Agility by Improving Cross-Functional Effectiveness

2 Introduction Many property and casualty (P&C) insurers are functionally siloed. From an enterprise perspective, this has resulted in a lack of crossfunctional market focus driven by ineffectiveness between underwriting, claims, actuarial, and finance. In the past, efficient functions operating at low cost compensated for this ineffectiveness. Functionally-focused carriers are finding themselves at a disadvantage as crossfunctional information sharing becomes more important than cost efficiency to overall organizational effectiveness. They are experiencing failure in the information feedback loop, where claims and market data should be used to quickly update and manage the product structures and underwriting rules that support market positioning and risk selection. The wealth of information that has become available necessitates managing the dynamics of insurance products using an end-to-end information advantage. In the pages that follow, we explore this dynamic, illustrate it by way of example, and end with practical recommendations. Current state Many P&C insurers are in the process of transforming, or have transformed, their policy administration, claims, billing, and financial systems, as well as related data environments and operational processes. While there are macroeconomic and technological reasons for these transformations (e.g., record levels of policyholders surplus across the industry, historically low interest rates, new and more robust technologies, etc.), the primary driver appears to be strategic. Many P&C insurers realize that more insightful approaches to deploying capital in what is a highly cyclical marketplace will help them more effectively achieve their profit and growth goals while mitigating cyclical adverse selection risk. Enablers of this effectiveness include: Optimizing the use of advanced analytics for product development, pricing and claims management, More targeted risk selection through focused underwriting appetites, More focused distribution management, Leveraging claims information in a more-timely manner, Preparing managerial and financial reports more efficiently, and Implementing new compliance imperatives faster. It is somewhat surprising that it has taken so long for the current level of transformations to occur. It is equally surprising that the holistic integration of cross-functional information for the purpose of focused risk selection has taken so long to gain widespread recognition. In many ways, insurers are information factories that absorb and analyze data to develop products in order to manage risks at given levels of premium. PwC 1

3 Industry analysts believe direct distribution personal lines insurers, such as GEICO and Progressive, use the information advantage of their data in market positioning and risk selection. This is in contrast to the broader P&C industry, where many carriers are just beginning to fully explore how to develop an integrated market strategy and risk selection capability founded on an end-to-end information advantage. One possible reason that many carriers are not maximizing this information advantage may be their organizational structure. Functional silos have developed across actuarial, claims, finance, IT, operations, and legal driven by functionally focused initiatives such as: Claims leakage analysis to improve claims effectiveness and efficiency, Finance transformation projects, Functional IT re-architecture, reengineering and/or outsourcing, Predictive modeling to improve pricing and distribution management, and Legal, auto property and medical billing review for reasonableness (legal research has also been offshored). Focused functional projects like these have resulted in improved functional efficiency and effectiveness, but such focused, specialized expertise also has resulted in a certain level of enterprise cross-functional ineffectiveness due to a breakdown of cross-functional data flows and processes. In other words, enterprise-wide effectiveness has suffered due to process, systems and organizational gaps/misalignments resulting from a functional organization structure. This dynamic is becoming more problematic given how quickly market opportunities change and rates soften. For example, consider product development. While the process of creating insurance products is relatively well understood, the analysis that goes into identifying a market opportunity and tracking customers, risks, exposures and profitability over time are much more complex. To understand why, first think of all the data required to create a new product (including policy forms, underwriting guidelines, SIC or D&B codes, class codes, line of business structures, coverage codes, and cause of loss codes across actuarial, finance, underwriting, and claims, as well as loss and expense data), and then think of all the cross-functional communication and analysis that is required to: Rationalize, maintain and align multiple code structures across all of the various functions (underwriting, claims, finance, and actuarial), Integrate new codes and related data into all of the various systems of a modern P&C insurer as product features change, and Analyze all of the production data across various functions, operations and systems to update underwriting criteria, rates, riders and policy language. These failures in the product management lifecycle can severely impact carrier profitability and potentially longevity. Adverse selection and winners curse have affected the profitability of many carriers, some fatally. The following diagram illustrates the business impact of informational leakages that can occur due to a lack of cross-functional interactions between product management, underwriting and claims. PwC 2

4 1) Claims Detects Losses Out of Line with Initial Product Model Infrequent product model exceptions, low severity. Infrequent product model exceptions, higher severity. Frequent product model exceptions, lower severity. Frequent product model exceptions, high severity. 2) Product Management Reactions (Actuarial/Underwriting) Not Systematic /May Not Persist Tactical Response Change marketing, producer focus and underwriting guidelines. Reinforce underwriting guidelines, change limits or add product exclusions. Systematic /Appears Persistent Strategic Response High selectivity in writing business and adjust rates to compensate for high loss and expense. Potentially add riders. Stop writing business and raise rates significantly to compensate for high loss and expense. Redesign product coverages entirely. 3) Claims Cause of Loss Impacts if Addressed Reduced frequency of exceptions. 4) Carrier Impact if Not Addressed Lower severity of exceptions. Initial reduction in frequency of exceptions. Longer term increased in premium and return to higher frequency Initial reduction in frequency and severity of exceptions. Longer term change product strategy, coverages and loss model Slow erosion of profitability. Gradual drop in underwriting competitiveness. Cost drift in claims. Higher IBNR, variable profitability and increased capital usage. Claims cost rise to mitigate large losses. Quick erosion of profitability and erosion of capital. Reactive underwriting. Claims expenses rise due to frequency Severe erosion of capital. Product or line of business enters run off. Operational stress on claims PwC 3

5 Defining the problem Now consider some key questions that apply to environments where data structures differ across functions, operations and systems and are not effectively set-up for new products or processes: Who will own and govern common definitions across functions? Who will develop consistent practices for data gathering and entry in each function and across functions? How will data quality be tracked from one function and system to another? Who will detect and correct manual data entry errors (from the submission phase to claims resolution and ceded reinsurance)? Who will oversee the consistent gathering of data from vendors and other outside parties? In many functionally-focused insurers, the owner of these questions is everyone and no one. Current solutions to this issue typically reside with chief data or analytics officers, actuaries or finance personnel. Regardless of the ultimate corporate owner, to diminish the effects of heavily siloed business functional designs, insurers need to take into account the following information-generating activities: Strategic planning including market, line of business and product expansion/contraction, Price modeling and monitoring processes, Distribution modeling and broker/agent performance management, Incurred But Not Reported (IBNR) and case reserving analyses, Reinsurance experience, Managerial, financial and statutory reporting, Customer and agent satisfaction management, and Legal defense and regulatory risk management purposes in the event of bad faith litigation (or other forms of legal/regulatory actions). Rarely is the information from all of these activities effectively coordinated. The diagram below illustrates typical cross-functional informational breakdown. PwC 4

6 Underwriting Claims Actuarial, Finance, etc. PAS 1 PAS 2 PAS 3 Lookup Policy ID ID Duplicate Claims Claims assignments Assignment based on location, policy limits, etc., not cause of loss or LOB Data Mart Data Mart Data Mart Data Mart Data Prepping / Scrubbing PAS 4 PAS 5 PAS 6 PAS 7 PAS N+ Review Special Handling Codes Deductible Erosion impacts Claims Claims Multiple Stat Coding Resources Internal and External Coverage Counsel Assigns resources to stat. code Stat. coding Ask for coverage counsel Coverage Reviews Claims adjusters looking up and verifying coverage Functional Disconnects and Impacts Coverage or exposure codes different (or non-existent) for each Policy Admin System Product bundling complicates code identification and processing Policy Admin Systems not integrated with claims platforms may require adjusters to review policies, look up coverages and limits, manually requiring multiple touch points (as illustrated above) Causes of Loss are not mapped to specific exposures ly and inconsistently inferring cause of loss to Line of Business loss information Actuarial data prepping is required, which at times can be significant Many companies have inconsistencies in the mapping of premium to exposure to claims to cause of loss and to expense. PwC 5

7 Significantly, this dynamic is not just an IT problem. Some examples of how cross-functional ineffectiveness can negatively impact underwriting include: Relatively effective insurers are able to update a product in three-to-six months and roll-out a new one in nine-to-twelve months. These activities can exceed two years at cross-functionally ineffective insurers. Advanced analytics are currently receiving a great deal of attention; however, end-to-end breakdowns can impact the value of a wide variety of analytical innovations. Consider, for instance, fraud analytics. The value of such analytics comes not just from how claims and special investigative units make use of the modeled output, but also how the company leverages this output in risk selection, pricing, distribution, ceded re, medical, and litigation management. The organizational feedback loops that enable this kind of enterprise-wide analyses are substantial, and not currently in evidence at many P&C insurers PwC 6

8 Illustrative Future State Context A holistic view of the operating model and how data flows across the value chain provide critical insights for pricing, underwriting and product development. Illustrative Future State High-level Architecture Closed Loop Underwriting Claims Actuarial, Finance, etc. UW Desktop Underwriters consider emerging costs in risk selection FNOL information entered accurately and completely Claims Reporting resources are given specific fields to document claims Stat Coding done automatically Claim and loss data integrated cleanly to reporting /analytics DBs Products Policy Admin Platform Claims Mgmt. Platform Actuarial Analytical DBs Claims are automatically assigned to adjustors based on their expertise Limits and Deductibles are codified in the Policy Admin Platform, limiting potential leakage Coverage information provided to adjustors Coverage Counsel volume is reduced with clear coverage data and better claim assignment Reporting DBs Systematized use of data across the enterprise to reduce expense and improve profitability and growth PwC 7

9 Issues to consider when implementing an integrated business and technology platform to achieve closed loop product management include: Clearly expressing end-to-end goals and strategies with a balance between function-specific and cross-functional requirements to drive more effective underwriting, Explicitly develop end-to-end processes and information feedback loops within the operating model to more timely inform risk selection, and Develop end-to-end information, organizational and operations strategies based on the needs, uses, data transformations, functional processes, and organizational dependencies across the entire underwriting function. The following case study illustrates the utility of this approach. Fancy Nails Hair salons began offering beauty services to their clients, including manicure/pedicure services. Many salon policies covered these offerings as beauty services and charged a premium that reflected historical losses associated with haircuts, hair coloring, nail filing, polish, and associated services. Some salons began adding prosthetic or decorative nails and nail ornaments (diamantes, designs, etc.) to their services. Over time, these applications have become more complicated and hold a higher risk of medical complications than traditional hair and beauty salon services. For example, medical complications involving application problems caused by glues, solvents, and the products themselves have become much more common. As a result, there have been claims for cosmetic/plastic damage, infections, nail fungus, damage to skin around the nail, and even finger amputations due to faulty applications or product defects. Despite the above frequency and severity developments, many insurers continued to underwrite policies for beauty salons under historical product structures. For example, the claims were being coded to original class codes and as a result actuarial teams generally continued to rate based on historical experience that did not adequately reflect recent loss developments. As a result, some insurers were entering this market just as other, more informed insurers, were exiting it or significantly revising their product terms or rates. Better informed insurers were able to more timely identify the frequency and severity spikes via linked code structures and integrated external information sources, and thus they were able to either firm-up their terms and conditions or exit the market before the issue eroded profit and capital thereby allocating capital to more promising classes. Meanwhile, insurers without these capabilities were entering the market and being adversely selected, which resulted in significant capital losses. PwC 8

10 How to proceed Considerations when using a cross-functional transformation program to improve overall carrier profitability and product agility include: Quantify the problem Quantify the market, customer, product, operation, and financial impacts of any breakdowns or areas of concern across functions, systems and processes. Include opportunity costs/benefits from early identification of positive and negative trends. Take a cross-functional view The product and underwriting operating model should undergo a thorough review to remove enterprise-wide effectiveness barriers and to enable cross-functional information flows. Uncompetitive products, customer segments and lines of business should be reviewed and examined for end-to-end breakdowns (such as knowledge gaps, operational inefficiencies, data inefficiencies, etc.). Take a risk selection-focused approach to developing a roadmap Start by asking questions such as How do we enable effective risk selection by enhancing end-to-end capabilities across all functions in the insurance value chain? What information enhancements are available if we improve data extraction and preparation efficiencies? Take a comprehensive approach to solving end-to-end issues Develop end-to-end requirements to comprehensively address product, market, segment, and line of business inefficiency issues. PwC 9

11 For more information To discuss this subject in more detail, please contact: Richard Pankhurst Director, Advisory Services Francois Ramette Director, Advisory Services Joseph Calandro, Jr. Managing Director, Advisory Services [email protected] Richard Hayes Senior Associate, Advisory Services [email protected] Emily Pallotta Manager, Advisory Services [email protected] PwC 10

12 2014 PricewaterhouseCoopers LLP. All rights reserved. PwC refers to the United States member firm, and may sometimes refer to the PwC network. Each member firm is a separate legal entity. Please see for further details.