Understanding and effectively applying pricing decision intelligence is pivotal in improving profitability for insurers. Despite its significance, the industry grapples with successfully transforming their pricing decision mechanisms. As such, pricing decision intelligence emerges as a potent tool to overcome these challenges. InsurTech hyperexponential (hx) has offered guidance on pricing decision intelligence and its use.
So, what is decision intelligence? Essentially, decision intelligence, or DI, creates an iterative feedback loop connecting data, insights, and the consequential decisions. This symbiotic relationship improves decision-making efficiency over time, much like a team sport where collaboration and coordination are key for success.
In the context of insurance pricing, decision intelligence plays a substantial role. The term “underwrite” originates from Old English underwritan, which means “to write at the foot of.” This is precisely what underwriters once did – they pledged to pay in the event of a calamity in exchange for a fixed premium, by signing at the end of a risk assessment.
In the present day, underwriting gives companies and individuals the freedom to test boundaries, from launching reusable rockets into space to creating new AI technologies. In doing so, insurance decisions stimulate innovation, empowering society to outwit the unknown and unleash hidden potential.
Insurers routinely make a plethora of decisions, each with varying complexity and implications. The quality of these decisions depends largely on the quality of inputs and processes at each stage. However, this varies dramatically across the market, leading to significant differences in the effectiveness of resulting decisions.
The secret to efficient decision-making lies in predictive data and profound insights. The more data insurers have, and the better they understand it, the more they can spot opportunities for growth and profitability. Weaknesses in the decision-making engine can result in flawed decisions, with repercussions rippling across the entire business.
Insurers cannot afford any inefficiencies, whether it be the failure to capture emerging insights, a lag in deploying actuarial models, or ineffective collaboration and feedback loops, all of which negatively affect the customer experience. Moreover, a lack of automation and scalability burdens IT departments and hampers business agility.
Insurers now face a crucial decision – adapt or perish. Although pricing is the central driver of profitability, many insurers have been unable to meaningfully transform their pricing decisions, despite the promise of emerging technologies. This hesitation can no longer be afforded, as the rapidly changing world is putting even mature sectors like commercial property under stress. To accurately price emerging risks, insurers must leverage all available data and insights.
Poor decision-making hampers insurers from exploring new market opportunities, leading them to decline propositions they could have accepted, or vice versa. Such missed opportunities hinder efforts to reduce loss ratios, scale profitable business, or enhance efficiencies and customer experience. Therefore, how insurers utilise their unique landscape of data and insights becomes their defining competitive edge.
Merely having pricing models is insufficient. Insurers have tried converting pricing models into decision-making tools, but they fail to facilitate rapid iterations or improve with each action. As such, they cannot function as effective decision engines.
Pricing is more than just about assigning a value. It forms the basis of an intricate decision engine that is vital to the underwriting team. With data flows and insights becoming increasingly complex, insurers must adapt these systems to keep pace with the dynamic market.
Standard data is quickly becoming commonplace, with AI hastening its commoditisation. To gain a competitive edge, insurers must delve into more complex datasets. Thus, the ability to extract insights from small, sparse, or fragmented datasets, like irregular spreadsheets and varying database schemas, will differentiate the successful from the unsuccessful.
Unfortunately, existing tools cannot handle this modern data landscape, which demands the conversion of disparate datasets into actionable business insights. However, new tools, such as open-source programming languages and libraries coupled with versatile databases and cloud infrastructures, can help insurers manage any data.
Despite these tools’ potential, creating this platform in-house may not be feasible or economically viable for most insurers. This is where hx Renew, the world’s first pricing decision intelligence platform, comes into play.
hx Renew acts as the hub of your decision engine, automating key processes and supplying the right data to the right person at the right time. It enables the generation of strategic insights from regular pricing actions and constructs a coherent data asset that improves with every decision.
Designed specifically for the realities of sparse and fragmented insurance pricing data, hx Renew strengthens the feedback loop between data, insights, and decisions, thus laying the groundwork for world-class decision intelligence. It facilitates seamless collaboration across the pricing team, creating a virtuous cycle of ever-improving decision-making.
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