Today, data is an asset that can be used both internally and externally. Companies can collect more information than ever before in a variety of ways. Digital interactions with customers on mobile devices and stationery allow us to track interactions and requests.
The Internet of Things (IoT) has provided billions of connected devices and objects equipped with tools to measure, record and communicate information about purchases, customer responses to advertising campaigns and marketing messages that can be captured and analyzed.
Accurate information requires data analysis programs that can easily collect, store, analyze, display, and report on information from a variety of sources. These insights provide business leaders with the information they need in real-time to make better decisions.
The Data-Backed Change
With converting client expectancies and the sheer expanse of data being collected, insurance businesses are already converting their models and processes.
Among the high-quality modifications are the following:
- Investment in tools to better understand their customers, their expectancies and their needs
- Development of recent insurance alternatives to provide guidelines which are shielding extra items
- Responding to an ageing populace whose insurance needs are converting in massive numbers and quickly
- Realtime processing and mobile apps that respond to the expectancies of younger customers, who anticipate a digital-first approach (this pace and responsiveness are often contrary to the traditional approaches insurers had in the past)
- Using new technology inclusive of blockchain, artificial intelligence, machine learning, and the IoT to create better operational efficiencies and create more connections with objects and customers
Challenges faced by insurers in leveraging data to drive digital transformation
Digital transformation provides a fantastic possibility for insurance companies. However, the same companies may also face limitations that delay the utilization and leveraging of data.
Among those problems are:
Lack of Policies and Procedures:
Many insurance companies have grown because of acquisitions, which means that the integration of systems and policies is challenging.
The data-driven insurance company needs:
- Data governance structures and policies
- Consistent data definitions
- Clarity of data ownership
- Standards for the collection, storage and use of data
- Data security guidelines
Cultural and Organizational Roadblocks:
An insurance company that desires to achieve success in the use of data in new approaches needs to address these concerns promptly:
- Internal cultural variations in how data is seen, valued and used
- Data stored in silos without standardization and a single source of information
- Complex data structures
- Inconsistent data formatting
- Reluctance to share data internally
- Data quality and more than one kind and sources for data (structured, unstructured, collected, purchased)
Technological Barriers:
Technology is a common barrier or leveraging data. Challenges include:
- Data stored both in the cloud and on-premises
- Legacy systems, often highly customized
- Lack of certified internal IT resources
Leverage data with Futran
Here are some recommendations for optimizing the opportunity for digital transformation for Insurance companies.
- Invest in Data Analytics – Big data analysis tools enable insurers to collect and use data from multiple sources at the same time, identify patterns, better detect fraud, and resolve cases faster.
- Using advanced OCR software – The insurance process still relies on paper, either that it generates or that comes from other sources. Sound OCR software reduces manual entry and re-entry, promotes better storage, retrieval and analysis of unstructured data while accelerating processes.
- Improves two-way communication – Insurers need to better engage with their customers — apps, content, and messaging tools. Tools should be primarily mobile and include features to capture interactions and outcomes.
- Use AI to improve engagement – Artificial intelligence tools like virtual assistants can provide customers with the information or live assistance they need, saving resources and fixing routing issues.
- Partners for Transformation – Insurers need strategic partners to help them collect, analyze and use data for digital transformation.
Conclusion
Emerging Leaders in the insurance industry are using insurance data analytics to manage risk selection and pricing strategy decisions. New-gen technology is working progressively to implement regulatory approaches to understand big data in a variety of insurance transactions such as underwriting, claims management, customer satisfaction and policy management to provide better predictive analytics. This allows insurance companies to describe the analytical decision-making process in all of their internal processes and business operations.
Futran helps insurance companies with their digital transformations by providing the best Data Analytics solutions such as Cloud-Based Data Warehouse & Data-Lake, Data Management, Managed Services & Analytics Model Development.
