IT Solutions for Insurance Industry

Insurance Analytics

Insurance companies operating in their status quo business model will be at a competitive disadvantage in the coming years. Increasingly, insurers must provide unique products and services tailored to meet the diverse needs of their producer and consumer communities. To do so, they need a deep understanding of complex customer behaviors, market segments and product life cycles. The ability to capitalize on these new market opportunities will depend on an insurer’s adeptness at identifying new customers and producers and retaining profitable ones, providing the right products at the right time, and giving customers top-level service through multiple delivery channels. Analytics represents the next frontier for this industry, and even with the challenges posed in shifting from a sales culture to an analytic culture, the industry is well positioned to start down this path.


Data Analytics to optimize claim processing and operational expenses

Operational analytics covers a broad spectrum of initiatives within the diversified life insurance industry, and can cover areas such as workforce and workload optimization and call center analytics. Claims management is a critical process in the Insurance life cycle. Quick and efficient claims processing increases customer satisfaction, optimizes settlements, and minimizes expenses. Analyzing and proactively managing the end-­-to-­-end process across regions, loss types, product lines, and business units helps Insurance companies better understand their most critical components in operational effectiveness and customer retention. Analytics solutions from xtLytics can help executives visualize and drill into key metrics on claims performance such as Cycle Time, Average Settlement Amount, and Claims Expense at an enterprise or transaction level. Complex information can be presented in graphical interfaces that encourage user interaction and discovery of insights.

Compensation & Future Sales

Predictive modeling to forecast how changes in producer compensation may impact future sales of groups of insurance policies based on producer’s past sales performance

Carriers have incredible amounts of information on producer’s compensation from their sales transactions that produce terabytes of data annually. However, most companies are unable to do much with that big sales data – although it can be the key to recognizing and responding to emerging developments in compensation structure and sales cycle, they have no way of analyzing it quickly and efficiently. xtLytics newest solution combines big data technology with innovative analytics and visualizations to enable real-­-time exploration of granular sales data to find how changes in producer’s compensation may impact future sales. Access to big sales data, and the ability to analyze it will revolutionize sales and channel decision-­- making.


Data Analytics to identify fraudulent and unethical selling practices

Big data and analytics can play a critical role in addressing the increasing prevalence of fraudulent or unethical selling practices to quickly gain additional insights. At the underwriting stage, insurance companies can employ big data and analytics solutions that scrutinize applicant identities by searching and analyzing large volumes of information rapidly. Companies can determine whether applicants—and people associated with those applicants have been linked to fraud in the past, and whether selling practices may be fraudulent or unethical.


Predictive modeling tool for Senior Agents to plan growth and productivity improvements for their network/agency by territory

Senior Agents effectiveness solutions focus on two elements: more effective support models for existing producers and more effective analytics to attract retain and optimize the producer workforce. Leveraging big data analytics, Agencies can now estimate the potential of a market and then evaluate a producer’s contribution of that share of the business. This analysis can also be used for target setting and training to improve overall market penetration. Whether a producer is a captive or an independent agent, a financial advisor or an intermediary, the use of big data analytics can help drive top-­-line and bottom-­-line growth. Senior Agents can leverage analytics across a broad range of producer information, including interaction history with the carrier and customers; social media capabilities, claims, payments and agent histories to understand which characteristics predict successful behaviors. The findings can be used to search and screen for new producers and to help existing producers increase their performance. Big data and analytics can also help make producers smarter about their customers, so they can anticipate customer needs more effectively and help retain business. Sharing cross-­-sell offers and sentiment analysis with the producer community can add to the producer’s business and drive incremental revenues to the Agency and the carrier company. Analytics allow for the matching of producers and customers to drive cross-­-sell and up-­-sell opportunities, help carriers maintain wallet share and reduce policy exchanges or cancellations.

Lapse and Persistency Rates

Predictive modeling to forecast lapse/persistency rates for groups of insurance policies.

Lapse experience on individual life products for various policy and product factors provides carriers with bench-marking and background information for product development, planning processes and marketing strategies. Lapse Analytics data will aid insurers in identifying factors that impact individual life insurance persistency, helping them in saving and retaining formerly “at-­‐risk” insurance policies and customers.


Predictive Analytics to help identify which customers are most likely to buy -­- developing hot leads for producers by zip code

xtLytics predictive analytics for captive distribution models can provide leads to the producers. Insurers with this capability are combining their internal data with third-­- party database marketing solutions to mine their own books of business for opportunities. One of the biggest challenges in the field is having thousands of clients and achieving a level of data segmentation that allows insurers to better understand their customers. Producers will gain the ability to analyze the decisions consumers in various demographics are making and the trends that exist. For insurers, the implications of social media analytics are enormous. The entire industry is driven by customers trust in their advisors or agents and social media increasingly determine whom customers trust. Social media are where customers express the feelings of security that are so important to an insurer’s customer relationships. In addition, social media help insurers maintain a presence in their customers’ minds during those long periods of time when their customers prefer to think about other things. For example, most insurance customers think about their insurance only when they experience a significant life event, change their address, or renew their policy. Social media provide a place where customers hear stories that remind them of the protection and the value that insurers give them every day.

Producer Analytics

Data modeling of Producer Analytics based on hierarchy and demographics

Companies need to manage successful producers and get them to sell their products over those of their competitors, as well as align their selling with corporate goals. Insurers are looking for Analytics tool that allows them to generate and analyze compensation reports as they choose. Companies need the ability to model producer’s compensation based on hierarchy and demographics. By having immediate insight into compensation, carriers can increases producer’s loyalty to the company by designing marketing campaigns and changing compensation structure to incent and stimulate growth.

Producer’s Book of Business

Data modeling to quantify the quality and sustainability of producer’s book of business

A Producer’s book of business is his most valuable professional asset. Yet, the ongoing opportunities that lie within it often go undisturbed, as producers tend to focus on prospecting for new clients and paying extra attention to their biggest clients. After all without assistance of analytics, it would require a great deal of time and effort by the producer or his staff to keep track of what’s going on with every client in a book of business. xtLytics provides insurers and producers with the tools to quantify the quality and sustainability of their book of business -­- to identify opportunities that benefit the client and often the producer. This Analytic tool, by mining producer’s in-­-force business generates a flow of opportunities that lowers costs for clients, scraps inefficient policies and improves producer commissions. The software can scrutinize each individual policy and compare it to every available alternative, generating a proprietary report the producer can present to the client, who will usually act on the recommendation because it either saves him money or enhances his coverage. Insurers, using predictive modeling can group producers into simple classifications based on the quality and sustainability of their book of business and align sales activities and marketing campaigns with “higher-­-value” segments and the at-­-risk group of producers.

Renewing Agent’s Appointments

Data modeling to optimize insurers investment in renewing Agent’s appointments

Many diversified insurers rely on negotiated selling agreements with broker-­-dealer firms and banks to sell their product lineups. In fact, roughly 92 percent of life and protection products are sold through third-­-party distribution arrangements. How are the insurers making sure that they’re aligning their wholesaling field organizations to the right opportunities? Many insurers still see the business of wholesaling as an art, not a science, but xtLytics is introducing quantitative methods into qualitative sales practices. Insurers can apply these analytic initiatives at all levels of the distribution chain, from the external and internal wholesaling organizations to the producers. This Analytic tool enables carriers to bring more profitable producers to the filed organization and ensures that wholesalers were spending time with the producers that would bring the most value to the insurer.

Sales Analytics

Predictive modeling to forecast how easy/difficult is for producers to sell groups of insurance policies considering demographics and prevailing economic conditions by territory

Most insurers sell more than one product line, and as the producers increase the breadth of products they sell from a provider, they become “stickier”. They sell more, they have higher account values, and they have a longer tenure with the provider. Understanding the prevailing economic conditions by territory lets insurers tailor specific cross-­-sell offers. Producers can script different contact scenarios based on their value, their propensity to buy, their propensity to pay and their propensity to lapse. Analytics helps reducing wholesaler turnover by providing wholesalers with more qualified leads, improves productivity ensuring the optimization of marketing dollars. Growth Analytics reduces product suitability risk by positioning the right product with the right consumer. xtLytics predictive models developed for customer retention efforts can identify customer transactions as a predictive triggering event and used the event to automatically generate a follow-­-up interaction with the client when the event was triggered.

Sentiment Impact on Sales and Lapse Rates

Predictive modeling to forecast, how company positive/negative sentiment in social media impacts sales and lapse rates

Social media plays significant role in today’s business strategy. Insurers need to study and monitor their standing in social media to develop successful go-­-to-­-market programs. Monitoring how sentiment in social media impacts sales and lapse rate in local markets provides valuable inputs into brand management, marketing campaign management and targeting new prospects. Insurers by monitoring sentiment to their company and products in social media can retain formerly “at-­- risk” customers, find market opportunity through identifying new target audiences and provide inputs into product development, pricing and communication strategies.

Territory Demographics and Sales

Predictive modeling to forecast which products will sell most in given territory by zip code based on demographics

The field organization needs to be in the right place to take advantage of opportunity. Throwing a representative into a territory based purely on population is ineffective. Using demographic data and identifying target markets enables the organization to profile the population, develop products to meet specific markets, and ensure that the sales force aligns with those markets. Analytics improves producers’ loyalty and productivity by proactively helping them understand the demographics and opportunities in their potential and existing customer base.

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