At gas stations, vehicle owners get the option to choose between top-of-the-line premium fuel and the regular variant. Naturally, if budget weren’t an issue, then every other individual would choose the former. After all, the fuel determines the performance, mileage, and health of the vehicle.
So why would anybody do otherwise when it comes to data? As cliche as it may sound, data is the fuel of digital operations.
Data is a core control and business asset for insurers. As such, they can no longer afford to compromise on its quality. Insurers of today leverage data for optimizing pricing strategies, managing growth and profitability, underwriting, detecting claims fraud, improving customer satisfaction, anticipating future demands, and more. In contrast, poor data quality can contribute to poor customer relations, bad underwriting decisions, flawed analysis, and missed opportunities and revenue. Consequently, the emphasis on robust data management and governance practices has intensified in the insurance industry.
In this blog, we will explore how bad data impacts insurance businesses and how modern insurance management systems can improve data quality.
The Impact of Poor Data Quality on Insurance Businesses
- Poor quality data can cost businesses up to $3.1 trillion annually.
- Bad data also leaves as much as one-fifth of business records of no use, with incomplete data, obsolete information, and duplicate entries being the top reasons behind it. While this information is rendered useless, it also consumes significant business resources!
- Inadequate data results in unduly optimistic or pessimistic projections, which can frustrate insurance teams. Also, poor prioritization of sales-ready leads can result in missed opportunities.
- When insurance management systems run on poor data, they create misleading and incorrect reports, which can lead to poor business decisions.
- As data stored in software solutions for insurance companies impacts customer service, bad data can harm policyholders experience. Also, the overall failure to deliver to customer expectations harms the brand image.
5 Ways Insurance Management Systems Improve Data Quality
Here is how modern insurance management systems, including insurance software as a service, play a pivotal role in enhancing data quality:
1. Data Centralization to Eliminate Silos and Redundancies
Insurance system software solutions are a centralized repository of all business data. Given how data-intensive the sector is, such a role is no common feat. The centralization of data eliminates data silos and allows data to flow seamlessly from one terminal to another. The resulting frictionless data exchanges paired with high availability and accessibility ensure that all stakeholders are data-empowered to make smarter and well-rounded decisions.
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2. Increased Data Accuracy From Core Operations
Insurance software solution providers, through their varied offerings, infuse accuracy across the insurance value chain. From underwriting to claims assessment, different operations require up-to-date customer data and real-time inputs to generate actionable insights. These findings contribute to making quicker and more accurate business decisions.
3. Updated Policyholder Data From Customer Relationship Management
Insurance administration software solutions lay the foundation for long-term and fulfilling customer relationships. It does so through a slew of tools that run on customer data to compose detailed customer profiles. Such profiles lend a flavor of personalization throughout interactions while also customizing the product and services. It also facilitates faster and more contextual customer support servicing for increased satisfaction rates.
4. Efficient Claims Processing for Accurate and Timely Settlements
Having access to real-time, accurate information enables insurers to accelerate claims processing and improve customer experience. As such, insurance management systems expedite and optimize the end-to-end claims process, starting from the First Notice of Loss (FNOL) to settlement.
5. Improved Data Governance and Regulatory Compliance
The insurance industry operates under strict regulatory frameworks. Insurance management systems are equipped with features that help insurers stay compliant with changing regulations by ensuring that data is managed in accordance with legal requirements.
This forward-thinking approach not only ensures compliance but also positions insurance companies to navigate the complexities of the regulatory environment with agility and foresight. Ultimately, these systems contribute to the overall stability and sustainability of the insurance industry.
6. Real-time Data Updates for Strategic Decision-Making
Insurance management systems not only serve as a centralized repository for all information, but they also process and update data in real-time. As a result, insurers have instant access to current data and can make better decisions. This functionality also reduces the risk of relying on outdated information.
Best Practices for Maintaining Data Quality Within Insurance Management Systems
- Perform Data Cleanse
Performing regular data cleanse can help insurers remove incorrect, duplicate, and erroneous data. Routine data cleansing helps in keeping the data quality consistent over time.
- Validate the Data
Performing data validation by checking it against predetermined rules and constraints offers accuracy, cleanliness, and completeness to datasets.
- Educate and Train Employees
To ensure data quality, all stakeholders must be on the same page. Hence, insurers must prioritize employee training and education so they can maintain data cleanliness.
In an era where data is considered a strategic asset, insurance management systems serve as a linchpin for insurers looking to enhance data quality. By leveraging these advanced insurance system software, insurance businesses can not only streamline their operations but also elevate their ability to make data-driven decisions. As the insurance industry continues to embrace digital transformation, investing in robust software solutions for insurance is a crucial step toward ensuring long-term success in a competitive landscape.
Case in Focus
A leading, full-service life insurance company was struggling to manage disparate systems and databases that contributed to poor data accessibility and poorer customer experiences. We used our suite of technology services – InsuranceNXT – to assess the insurer’s business processes, data quality, and It infrastructure. After understanding their technology landscape, we leveraged MuleSoft ESB and facilitated seamless integration of business data and legacy systems. The API-led data integration helped reduce TAT in claims administration, improved customer experience, and reduced data complexities, thereby ensuring sustained benefits for the life insurance company. For more information, refer to the complete case study.