The role of emerging technology in creating business value for insurers is vital. By helping insurers sell more, manage risk better, and achieve operational efficiency, advanced tech is triggering agile and profitable business models.
Today’s fast-paced innovations are enabling companies to tap into the full potential of data-driven prediction modeling and machine learning. Insurers are actively utilizing emerging technologies — chatbots, IoTs, robotic process automation, telematics, and code platforms to improve loss ratios, risk selection and pricing, and operational efficiency.
But, the inclusion of emerging technologies to improve processes requires a steep learning curve, raising three major concerns — How easily the technology is understood? How effectively can the technology be deployed and integrated with existing processes? And how can the value created be measured and communicated?
A well-strategized transformation of the insurance sector through technology-driven business models, and automation, is enhancing business value and improving operational synchronicity. Automation enables insurers to process claims faster, eliminate high-risk customer scenarios, reduce physical inspection costs, better fraud detection rate, and save on underwriting expenses.
The disruption of institutional insurance that relies upon legacy systems and traditional mindset is being steered by new behavioral trends. Generational insights are helping insurers focus on customer experience, efficiency, and effectiveness. The competitive advantage rests with insurers who are recognizing early signs of emerging risks, customers’ behavioral insights, and achieving operational synchronicity.
Advanced Analytics is Steering the Change
Insurance is a data-driven business, and harnessing the power of data to mitigate challenges is the biggest challenge for P&C insurers today. This is where advanced analytics comes in for insurance, which comprises data science, extensive risk knowledge, and industry expertise. It generates actionable business insights, optimizes existing portfolios, and combines actuarial methods with computational methods. By actualizing known problems with unknown solutions, advanced analytics ultimately reduces the time lag between underwriting and claims. Advanced analytics help insurers:
01 Improve efficiency
Claims prevention tools such as telematics and IoT sensors have become integral to auto insurance. They are eliminating the need for physical inspection and helping make critical decisions.
02 Optimize Portfolio
Identifying the principal reason for portfolio underperformance is a priority, and advanced analytics can help insurers identify inadequate or out-of-date customer segments. It can reveal accounts with considerable losses for prompt remedial actions.
03 Enhance customer engagement
Analysis of existing customer data offers prescriptive insights which improves customer engagement and satisfaction rates. Behavioral insights help nudge, target, bid, and engage with the right customer base. This improves policy persistence and sales performance. Analytics-driven profile identification reduces front-line sales attrition.
Buy vs build
The amount of data that will be created over the next three years will be more than the data created over the past 30 years. Further, the world is poised to create more than 3 times the data over the next five years than it did in the previous five. This tsunami of data has set the stage for massive investments into big data, and advanced analytics initiatives. Hence, the choice between building internally or buying external technology solutions arises.
Today’s fast-paced industry requires scalability and cost productivity. Building offers flexibility and ownership while buying offers ease and reliability. Quick deployment time along with necessary updates and new features are essential for maintaining a competitive edge. And advanced tech partners like Roadzen provide the necessary expertise for data collection, analysis, and curation.
As an increasing number of insurers partner with insurtechs for smarter and deeper analytical insights — existing processes are improving, and competitive and strategic advantage is being achieved. At the same time, emerging markets such as sustainable tech, and cyber risk require new models to advise clients, insurers, and regulators. To acknowledge these unique risk scenarios expertise of insurtechs is again essential.
