The Critical Importance of Decision Intelligence for Insurers

Historically, the insurance industry has struggled to match the pace of change within digital transformation. However, more recently, insurers have shifted rapidly – and competed intensively – to become more digitally enabled, customer–focused and data-driven enterprises.  

Becoming More Data-Driven 

Within the insurance sector, most companies have traditionally operated their different lines of business as silos, with each operating unit maintaining its own data, processes, and operations separately. This arguably has been one of the greatest challenges for the sector for a move to a faster, more consistent and digitally enabled customer journey.  

Among this, other market drivers exist: 

• Intense financial pressure – improve topline growth and bottom-line profitability, driven by challenging market conditions 
• An expectation to become more customer-centric – ensure a more tailored, streamlined experience for customers, as well as delivering fairer value 
• Automation and efficiency initiatives – replace legacy, manual processes with more automated processes to increase productivity and reduce costs  
• A highly competitive environment – forcing insurers to offer more customized products and dynamic pricing 
• Increased governance requirements – actions by regulators regarding consumer privacy, data protection, equitable and transparent pricing, among other issues.  

Now, through the application of innovative technology, AI and advanced analytics – and by leveraging the full potential of data – insurance companies are racing to create a seamless, integrated and holistic experience of customers, claimants and suppliers that they do business with. Achieving this, while navigating the challenges of disconnected data, organizational silos and external factors may seem impossible.

The key is being more data-driven through dynamic entity resolution. 

Accelerating Digital Transformation to Overcome Data Challenges

To overcome insurance data challenges, a highly scalable yet transparent solution is needed.

Dynamic Entity Resolution enables insurers to analyze, interpret and understand multiple parts of the customer journey in an entirely holistic way. It can integrate with disparate operational processes, leverage regularly siloed internal data and enrich with external insights to enable you to gain a trusted entity (e.g. customer, claimant, supplier) view.  

Let’s consider…

Take two commercial customers, “Allcon Labs Ltd” on a worker’s compensation (employers’ liability) policy and “All Labs Inc.” on a warehouse property and stock protection policy. Are the companies linked? 

Take a new quote from applicant “Sheila Edwards” and existing long-standing policy holder “Sheila Foster”. Are they the same person and would you treat the quote differently knowing that?  

Take two claimants. “Joseph Anthony” from City A and “J. P. Anthony” from City B. Are they the in fact same person and is it required to assess both claims holistically? 

By using an advanced capability like ER you can delve deeper to quickly assess questions of the data like does “Allcon Labs Ltd” and “All Labs Inc.” have a group of overlapping directors? Or do they share warehouse locations? 

Do both “Mr. Anthonys” share any overlapping details (e.g. aliases, vehicles, contact details, addresses, security/national identifiers from other portfolio data sources, credit bureaus, other public records)? Do they actually share connections to other claimants and/or policy holders? Have they used the same medical providers and if so, how large or geographically dispersed is that medical provider? 

This is how humans think – deriving context to make more informed decisions – and it’s exactly how ER works, too. It provides more contextual insight and allows insurers to determine “who is who” and “what is what” with unparalleled accuracy, at huge scale and at lightning speed.  

This creates that transparent, single analytical view of the truth that has often been missing and means insurance companies can deliver a truly trusted, accurate and streamlined business process to their customers (and third parties). 

Find out more about Quantexa’s Dynamic Entity Resolution solution.

Unlocking a Roadmap Toward Digital Resilience for Insurers 

As far as an insurance firms’ journey goes, ER is the foundation of a roadmap to digital resilience. The open architectures ensure they can be integrated easily into any existing IT and operational system landscape (cloud-based or on premise). 

With that trusted holistic view, you can enable powerful knowledge-based network graph analytics, predictive modelling, decision intelligence and data visualization. This reduces complexity and enables more automated decision accuracy as well as increases operational efficiency. 

CASE STUDY 

When one of the world’s largest insurance companies wanted to enhance their own in-house-built, global claims analytics and adjudication system, it compared a range of market solutions. The organization chose  Quantexa’s Dynamic Entity Resolution as the capability to incorporate into their global ecosystem to reduce decision-making time and increase efficiency by 10-30x.

Quantexa’s Dynamic Entity Resolution can resolve data related issues 60x times faster and with over 99% accuracy. Only with this level of speed and precision can you empower more automation and digitization while maintaining a consistent and transparent customer experience.  

Other benefits of Dynamic Entity Resolution include: 

• Achieving a trusted 360-degree operational view of all customers, prospects, claimants, suppliers (and other organizations) and more easily enriching decisions with external data to deliver better insights,  

• Enabling timely customer verification and on-boarding including pre-population, 
• Delivering faster and more accurately priced quotes on new policy applications, 
• Fast tracking valid claims whilst protecting your book from hidden risks such as fraud, 
• Reducing the time spent by data scientists and analysts wrangling data and addressing data quality issues. 

Accelerating Your Digital Transformation Journey with ER

Through increased competition, tougher regulation of fair treatment of customers and the battle to remain profitable, the stakes for having accurate digital processes and customer journeys are becoming even higher for insurance companies.  

The promise of becoming a genuinely data-driven company is a powerful one for most insurers. It is encouraging to see that many are now advancing towards that goal – with the succeeding the fastest, are applying advanced decision intelligence technologies to their digital transformation journeys.