Beyond Legacy Systems- Data-Driven Strategies to Win Customers in Insurance

This blog dives into the challenges of customer retention in the insurance industry. It explores how outdated data infrastructure hinders personalization and engagement. You'll learn why data is crucial for customer satisfaction and how leveraging data analytics can transform the insurance business.

Abstract

The customer is at the center of all business decisions, more so for the mature insurance sector that is fraught with slow growth, consolidation, increasing competition, and rigid compliance mandates. While customer churn may be an integral, inevitable part of doing business in the insurance sector, the impact can be significantly reduced by recognizing and meeting the emotional requirements of customers. Insurers who take concrete steps to elevate customer confidence and alleviate their fears not only succeed in enhancing retention, but also in growing business. Data optimization can be your answer to improving customer experience with in-depth and real-time insights and creating more inclusive, personalized engagements.

Going the Extra Mile

Let’s accept it—losing a customer is bad for business! There is no dearth of options available for today’s informed and digitally equipped customer, which is making customer retention an even bigger challenge. To expand their customer base and create long-lasting relationships, it is imperative for insurance companies to go an extra mile and engage with the customer at an emotional level. Insurers need to focus on understanding the emotional needs of investing in insurance and addressing the “fear versus care” concerns of customers.Traditionally, the insurance sector has thrived on the notion of fear of the unknown—whether in the “value P&C” or the “premium specialty” market

In most cases, insurance is essentially purchased for a “just-in-case” situation, and customers worry that they or their loved ones will be inadvertently left liable for large sums of money. There is often the concern that they may not have invested in a product that is best suited to their requirements and situation or may not have paid the right price. Moreover, the not-quite-favorable perception—insurance professionals aggressively push products that ensure them hefty commissions rather than what really serves the customer’s best interests—must be altered to ensure higher customer satisfaction and retention.

Smart insurance companies today recognize the need to meet customer expectations and connect with them at an emotional, personal level. There is a growing need among insurers to instill confidence in customers and deliver products and services that make them feel cared for and part of the system. From ensuring access to easy online quotes and externally certified product comparisons to one-click processing of claims, insurance companies are leaving no stone unturned to deliver a premium experience while engaging with their customers. Industry experts assert that to gain business, customers, and market share, insurers must overhaul their customer-facing channels like websites and apps.

Additional customization and inclusive add-ons that insurers are offering to make the customer feel cared for include:

• Naming care associates along with client phone numbers, emails, chat, and social media accounts
• Enabling field insurance professionals to process payments on the spot
• Periodically reviewing a customer’s portfolio of insurance products for premium reductions and not just additional upsells
• Providing features such as “click for details” that let users drill down and see what factors have prompted an underwriting decision

Choosing the Right Model for Effective Customer Engagement

Given that customers are driving businesses today, insurance providers must look inwards at their distribution models. Actually, it is this element that will actively dictate how a company engages with customers and conducts business. Choices ranging from a traditional legacy that concentrates on in-field representatives, corporate agents, and an insurance broker-based model to drive growth, to on-demand models that encourage customers to self-serve, to an alternative hybrid model that adopts modern technology tools and the Internet blended with the traditional agent-driven approach, will have a direct impact on the bottom line of the company.

Legacy Model: Most insurance companies follow this conventional model that has local agents engaging with customers on a day-to-day basis under the umbrella of the corporate office. While this model offers a higher degree of localized service and ensures a more long-term connection with customers, it fails to provide customers with on-demand care capabilities they are looking for. The model does not incorporate modern tools like apps or online portals that allow customers greater control over their own experience. Moreover, a legacy-based model may create information silos about customers and reduce cross-sharing of best practices across the organization.

Direct-to-Customer Model: As opposed to the traditional legacy model, a direct-to-customer approach is exclusively committed to letting customers control their experiences. It lends customers the freedom to self-serve—to go directly online and determine the level of protection they would like, refine their price parameters, and dictate the entire process based on their needs. While this model allows customers to self-serve and regulate their experience, it takes away an opportunity to provide exceptional customer service through personal interaction and customized products and services. The customer may no longer have access to a dedicated customer care representative who can guide them to purchase the most suited product and help navigate the claims process.

Hybrid Model: As the name suggests, the hybrid distribution model is a combination of the legacy and direct-to-customer models. It offers greater flexibility to customers with access to insurance agents to help navigate the claims process or address any coverage related questions, and the freedom to dictate their own level of protection through a channel of their choice. While this is an ideal approach for customer engagement, it also significantly increases process complexity and requires new capabilities to be implemented. More specifically, insurers that operate through a direct-to-customer model will have to include dedicated representatives to manage the accounts. Insurers that function on legacy models will be required to integrate emerging technologies and digital offerings to deliver a more holistic experience to their customers.

Changing customer lifestyles and buying preferences coupled with technological advancements are set to guide the future models of distribution. Though customers may increasingly prefer Internet-based buying, the need for the traditional, personal engagement that an agent offers cannot be undermined.

Regardless of the distribution model an insurance company opts for, it is critical for them to acknowledge that today’s customers want to interact with providers who can adapt to meet their dynamic needs. Without these offerings, companies risk losing customers and agents to competitors that understand these demands.

Why Data is Critical to Customer Satisfaction and Business Growth

At the core of any business activity lies data. Any effort to upgrade the processes and distribution models for insurance providers have to be appropriately backed with a sound, robust, and updated data infrastructure. Unfortunately, the database and the infrastructure across the insurance sector has failed to evolve over time to meet changing customer needs and expectations. Most insurance providers continue to deliver services and track clients based on legacy systems dating as far back as the 1980s when policy systems were first implemented to automate the insurance industry.

At the onset, legacy data infrastructure was easy to maintain and offered business continuity by streamlining the information capture process. However, the fact that the systems have not been upgraded to meet current technology standards has brought in copious amounts of complacence and inefficiencies such as:

• No access to customer’s latest data like their Twitter handles and social media pages
• Increased inaccuracies in data due to lack of verification and cross-checking
• Lack of 360-degree customer insight giving misleading customer information
• Inability to deploy and leverage new technologies like data mining and analytics

Knowing When to Upgrade the Data Warehouse

While data warehouse revamp and upgradation may seem to be an unnecessary expense, it is important to recognize that it offers actionable insights and intelligence critical to taking accurate business decisions. That said, it is not easy to undertake the monumental task of upgrading the entire data system. Here is how companies can determine if they should update the entire data warehouse before committing funds for an overhaul.

Review the fields being tracked: The goal of any data warehouse is to track information about the company and its clients to make sure it can be analyzed. However, if a company has not reassessed which fields are deemed critical, it may not be capturing essential information that can help provide a customer with superior service.

Scrub the list for errors and duplicates: Have you ever looked through the contact list and found multiple entries for the same customer? If so, your database should be cleansed, meaning that all information must be verified and duplicates removed. Without this step, data analytics will not give the desired results.

Use business intelligence software to analyze patterns: For some data, analysis software cannot be used, possibly because the fields are not uniform, there is no structured data, or because the data file is not accessible. Regardless, this means that the data warehouse needs a thorough review to ensure it is as effective as possible.

Harnessing Data Rightly to Reboot Insurance Space

The insurance sector has access to mega volumes of data, unlike any other industry. Multiple data streams and the insights gained from analyzing them have the ability to boost the insurance business to new levels. The key data sources are:

• Unstructured data: Considered very difficult to analyze, this includes adjuster notes, police and medical reports, and underwriter information.
• Internal data: This is the primary information available with the insurance company and includes data created and stored in transactional systems such as policy administration, claims management, billing, and agency management.
• External data: : This is being used aggressively to supplement internal data and includes third-party data like credit scoring, government demographic data, and even geospatial data such as weather information and Google maps
• New data: As the name suggests, this is the data emerging from digital and new technologies like social media data, telematics, and Internet of Things.

While other industries have been quick to adopt emerging technologies in the data analytics space, insurance providers have been sluggish in making the shift. As a result, insurance players are missing opportunities to better service customers and improve business.

This trend is set to change with insurance players now expressing a desire to leverage technology and data. Customized products and services are gaining traction, fueling business growth. For instance, simply by entering the postal code and home address, a potential customer seeking home insurance can receive an instant quote online about the cost of the insurance. This is possible as now insurers are analyzing internal and external data about weather risk, claims, construction, zoning, crime, accidents, and other related information and offering the best product at the best price points.

Insurers are using patterns and integrating it with business intelligence to help customers get the right coverage while also protecting the insurance company from underwriting risk and fraud. With analytics drawing upon new data sources, insurers can also explore entirely new opportunities for new products and services.

Additionally, data analytics can also help reduce customer churn by identifying customers that are likely to defect. It is a widely accepted fact that acquiring a new customer costs more than retaining an existing one. By applying analytics and algorithms around human behavior, insurers can start predicting which customers might leave. This makes it easier to specifically target them with tailored information designed to retain them.

Conclusion

The insurance industry is undergoing a data revolution. By embracing data analytics and modernizing data infrastructure, insurers can gain a competitive edge. They can personalize products, improve customer service, and ultimately win customer loyalty in a crowded marketplace.

Call to Action:

Is your insurance company struggling to keep up with changing customer demands? Contact Coforge today to learn how our data management solutions can help you transform your business.