Data warehouse for the insurance industry: How it works

Business success across modern verticals relies heavily on informed decision-making and ad hoc analysis of real-time and historical data companies operate in their pipeline routine. To live up to such tasks, organizations should ensure 24/7 availability of their business and customer data that can be sliced and diced on demand via leveraging cutting-edge digital tools. The best example of such tools is data warehouses (DWH) that act as data hubs containing vast amounts of relevant information from diverse sources and enabling business intelligence and advanced analytics of the data stored in them.  

Insurance companies are among DWH solutions’ most frequent business users, considering them key elements of their IT ecosystems. By pooling information from various sources and centralizing data under one virtual roof, they can improve regular workflows, revolutionize data analysis tasks, and adopt data-driven decisions concerning multiple shop floor activities. 

What boons does a data warehouse for insurance bring? 

Zooming in on data warehousing benefits for the insurance business

Having delivered high-end solutions for insurance agencies for over 15 years, we at DICEUS are well aware of the many benefits building a data warehouse ushers in.  

Centralized repository of data 

Modern insurance companies are ramified ventures with numerous branches and subsidiaries that generate and receive tons of data (customer information, policies and claims, market conditions, and more) from diverse data sources and different systems within the organization in disparate formats. By integrating data and storing it in one location, they obtain a single source of truth for all departments and avoid data silos.  

Boosted operational efficiency 

Since every personnel member can access the unified database containing up-to-date, consistent, and accurate information at any time, they can perform claims management and underwriting processes (as well as other shop floor operations) faster and more efficiently, which spells reduced costs, greater productivity, and minimal number of errors.  

Enhanced reporting and analytics 

Top-notch data warehouses are equipped with robust analysis and reporting tools that enable the staff to analyze trends in the niche, gain a comprehensive overview of the company functioning, identify patterns in customer behavior, tap new business opportunities, and present all the findings in the form of easy-to-read and accurate reports leveraging the best-in-class data visualization techniques.  

Better risk assessment 

DWH mechanisms are honed to sift through client-related data in search of risk factors and red-flag suspicious activities that pose a threat to the organization. As a result, employees can make informed decisions about their steps, introduce proactive risk-hedging measures, and step up their fraud detection efforts.  

Improved decision-making 

Information stored in the data warehouse allows both managers and rank-and-file personnel to gain insights into internal processes within the organization and market trends that dominate the sector. Armed with these actionable insights and using predictive models as guidelines, they can perform better decision-making and more knowledgeable long-term planning. 

Augmented customer awareness 

Maximum client satisfaction is the name of the game in the insurance industry. It can be achieved by the utmost personalization of services tailored to suit each particular person. Client data a DWH contains with all customer preferences, needs, and pain points creates a 360-degree view of the clientele and becomes a point of departure for devising individualized customer service strategies and targeted marketing campaigns. 

Sounds impressive, doesn’t it? Well, it does. But poised for creating a highly efficient data warehouse that relies on disruptive data handling technologies, insurance organizations should understand what bottlenecks and pitfalls await them on the way to its development and implementation.  

Addressing major challenges when implementing DWH in insurance

While consulting companies on the nuts and bolts of DWH implementation, vetted experts of DICEUS draw their attention to the following roadblocks.  

Performance 

For data warehouse end users, the speed of getting responses to their queries is vital. However, with the growth of information volume and the number of personnel involved in data handling, DWH performance may decrease.  

You can accelerate the operation of the data warehouse by properly indexing files within it, denormalizing data (when necessary), and widely utilizing in-memory databases and OLAP cubes.  

Data integration 

As a rule, organizations have their dossiers stored in CRM, ERP, and other disparate systems where data resides in various formats and multiple structures. Besides, they draw upon data from external sources (for instance, social media platforms, medical records, police protocols, IoT devices, etc.). Bringing it to a common standard and synchronizing it within one database is a tall order for users.  

The most effective technology for tackling such complex processes is the ETL (extract, transform, load) mechanism. Thanks to it, information from various sources is transformed into a single format and stored in a DWH based on a standardized model. Besides, by utilizing a network of APIs, insurance organizations can streamline and facilitate data exchange between applications, providing seamless data sharing across the ecosystem where the data warehouse is a nexus.  

Data quality 

Raw data retrieved from multiple sources contains inaccuracies, redundancies, inconsistencies, and other inadequacies. If used in this state, it will lead to misleading analysis, unreliable outcomes, poor insights, and incorrect decisions.  

The main recipe for safeguarding the quality of DWH data is an out-and-out cleansing procedure during which you should pinpoint and remove all flaws, validate data against pre-established rules, ensure information is up-to-date, and create data governance frameworks, thus maintaining its integrity. 

Data security 

Business and personal data is one of the most valuable assets today. Astute hackers are never tired of inventing ever new ways to penetrate enterprise and private systems and get hold of sensitive information they will utilize for criminal purposes, causing great financial and reputational damage to organizations and individuals.  

You can prevent files your data warehouse contains from being stolen by implementing stringent access control, establishing zero-trust architecture, employing data encryption techniques, utilizing robust intrusion detection mechanisms, regularly updating DWH’s security perimeter, conducting systematic audits, and staying proactive in forestalling breach attempts and data leakage instances. 

Regulatory compliance 

Organizations across numerous sectors (and the insurance realm is no exception) that handle customer data in their pipeline processes are required to adhere to legal norms concerning information protection at rest or in transit. Yet, the sheer amount of such laws and their constant updating and expansion make this task a challenging endeavor.  

The only way you can conduct constant monitoring of the legal framework and remain compliant is to leverage specialized tools (largely AI-powered ones) that will watch for regulation changes and compare your existing standards against them, alerting personnel to take corrective steps.  

Scalability 

Sometimes, companies opt for the data warehouse that fits their current needs to a tee, taking no thought for the future advancement of their business, technological progress, client base growth, expansion into new markets, and respective surge in the volume of data. That is why, in a couple of years, they face performance issues and the DWH’s inability to play well with disruptive know-how.  

To keep up with the dynamic business demands and fluctuations in data amount, organizations should design the data warehouse architecture with an eye to the increase of processing capabilities and its possible escalation (for instance, employ partitioning strategies) and deploy their solutions on cloud-based platforms allowing for the system’s quick upscaling. 

Change management 

It refers both to onboarding the new technology by the personnel and introducing modifications to the already functioning data warehouse. Very often, both processes encounter obstacles, chiefly due to inadequate implementation strategies. 

Tweaking the existing system seems easier to tackle by adopting the Agile approach for iterative development and step-by-step upgrading of the DWH without disrupting regular workflows.  

Embracing data warehousing is a trickier business since employees often struggle with learning the ropes of state-of-the-art solutions and mastering their functionalities. The learning curve can be made less steep by introducing comprehensive training programs for the workforce and showcasing the efficiency perks leveraging a DWH promises.  

To successfully overcome all these barriers and maximize the value of data warehousing for your insurance organization, you should delegate its development and implementation to seasoned experts in the field.   

How DICEUS can help you

DICEUS is a product-led company specializing in innovative tech solutions for the insurance industry. We also provide services as a system integrator and develop custom software solutions. 

By partnering with us, you get two options for data warehouse implementation.  

The first is the ready-made DWH and data analytics product that comes as a part of our Vitaminise suite and can be easily integrated with your company’s digital infrastructure. Its OLAP mechanisms are honed to analyze insurance data by dimensions (such as policy types, claims frequency, and more), while its data marts contain files related to certain workflows (for instance, underwriting, claims management, customer management, you name it). Using robust ETL processes to standardize and load real-time and historical information, the Vitaminise solution pools data from various systems, ensuring consistent trend analysis, fraud detection, reporting, and decision-making across the organization.  

If you find that Vitaminise software can’t satisfy your technical and business requirements completely, we can develop a custom DWH system from scratch, filling it with unique functionalities and envisaging its scalability potential that will dovetail with all your current needs and future expectations.  

Contact us for a high-end data warehouse that will propel your insurance company to reach big-time goals.  

To draw a bottom line

Efficient data handling is the bedrock of business success across contemporary industries (the insurance domain included). It can be achieved by setting up a data warehouse – a centralized data depot that contains relevant information derived from all available sources. 

If an insurance company makes a DWH a part of its IT ecosystem, it enhances operational efficiency, boosts its reporting and analytical capabilities, improves risk management, augments decision-making, and elevates customer awareness to a new level.  

Insurers can maximize the value of data warehousing by successfully addressing challenges they face in the process of its implementation and delegating this task to high-profile professionals in the field. 

Frequently asked questions