Data, when processed and analyzed effectively, can provide a competitive advantage. The insurance analytics market is projected to reach $20 billion by 2026, according to MarketsandMarkets. This highlights the growing reliance on data for shaping strategies and improving efficiencies. This article outlines a strategy for startups and SMEs to use data for innovation, service differentiation, and informed decisions.
Based on our experience working with insurance companies, we have listed down a method that can be used to deal with the challenges the industry faces. Each challenge is broken down into manageable projects and every project is given a wrapper solution to obtain quick results.
The wrapper strategy lets you maximize outcomes with your current systems, thoroughly understand the available data and apply insights within your existing tech stack. This approach enables you to progressively modernize platform components without needing a complete overhaul.
Big Data vs. Fast Data – Do I need both?
Big data includes vast amounts of historical structured and unstructured data from sources like customer interactions, IoT devices, and social media. This data, which can be days to months old, is analyzed to gain insights into customer behavior, driving informed business decisions. It identifies market trends, determines value propositions, and influences product design, aiding strategic decisions.
Aviva uses big data to refine customer segmentation and tailor products by analyzing purchasing behavior and claim history. This helps Aviva create targeted marketing campaigns and develop products that meet specific customer needs, such as eco-friendly.
Fast data processes real-time data, enabling Insurtech companies to quickly assess risk, offer instant quotes, issue policies, and detect fraud. Real-time data allows insurers to adapt to changing customer contexts and provide personalized solutions.
Trov uses fast data from connected devices to offer on-demand insurance for specific items. While big data drives strategic decisions, fast data enables immediate operational efficiency and responsiveness, impacting the bottom line.
Harness Existing Data with RPA solutions During Platform Modernization
Robotic Process Automation (RPA) is a cost-effective way to extract data from legacy systems for analytics without addressing their inherent limitations. Companies like Prudential Financial, New York Life, and Aetna use RPA to consolidate data from multiple systems, streamlining underwriting processes and allowing agents to focus on higher-value tasks.
RPA solutions serves as an interim solution, enabling insurers to work with data from existing systems while planning a phased modernization. It acts as a wrapper, insulating new data layers from legacy constraints, and facilitating a transition to cloud-based applications for agility and personalized coverage.
A report by Deloitte highlights that 78% of insurers using RPA reported significant improvements in operational efficiency within the first year, validating RPA’s role as a transformative tool in the insurance sector.
Build a Secure API Layer – An Investment with Long-Term Value
Secure API Layer – Long-Term Investment
APIs isolate backend services, standardize data formats, and facilitate data exchange between application silos. They enhance decision criteria in workflows for improved risk assessment and customized policies. While RPA extracts data, API’s push analytics back into the platform, contingent on legacy system modernization for optimal utilization.
In InsurTech 2.0, API’s foster collaboration among insurers, InsurTechs, MGAs, brokers, and others, enabling secure data sharing and real-time interactions. Honcho uses APIs to connect with insurers, offering accurate insurance comparisons via real-time data exchange.
PwC’s analysis indicates that insurers investing in robust API infrastructures achieve 20-30% faster integration times with third-party services, leading to enhanced customer experiences and operational agility.
Assess Data Value: Streamline with Managed Data Services
Different data types vary in relevance and quality. For instance, purchase history is more insightful than social media activity for understanding customer behavior. As data volumes increase, so do storage needs, data cleansing efforts, compute requirements, and analysis time.
Prioritizing data analysis is crucial for effective big data insights. Managed Data Services partners specialize in data operations, ensuring data quality and relevance. For example, Bright Box analyzes real-time driving data to assess customer risk profiles, while Slice Labs uses specific data subsets to tailor insurance for gig economy workers.
Transparency is key to user trust
Accurate data is crucial for valuable analytics. Customers share data for tangible benefits but restrict it if businesses use opaque methods. Insurance companies can build trust with clear data practices, robust security, and compliance with GDPR and HIPAA. They should communicate data collection and usage clearly and anonymize shared data.
A responsible data culture and employee training are essential. Share data only for relevant services, and be transparent about access and purpose. For example, Hitch Insurance uses advanced security, while Oscar Health provides clear data usage explanations and easy health data access.
Master Data with Trigent AXLR8 Labs
SMEs in insurance can overcome budget constraints by adopting the ‘Wrapper’ strategy and an incremental approach, starting with critical data and gradually adding capabilities. Partnering with specialist vendors for managed data services provides a cost-effective way to leverage the benefits of big data and fast data analytics.
You can get more by leveraging Trigent AXLR8 Labs that offers tech resources including domain consultants, Ninja developers, pre-built code libraries, and customizable solution frameworks. Our tech accelerator enables you to leverage AI and generative AI services to analyze complex and diverse datasets for effective risk assessment and underwriting, and for generating personalized policies and pricing.
Talk to Us To Deliver Instant Insurance Experiences with the Right Data
