Risk professionals and the insurance industry have long grasped the advantages of risk modeling, but they are just beginning to appreciate the value of predictive and geospatial analytics. The ability to predict outcomes — from the likelihood of litigation in a workers compensation claim, to the physical and financial impact of location-specific events — is not just a game-changer for risk decision making. It is the next frontier for risk management and insurance.
Until now, the insurance industry has largely focused on post-loss activities. That has been the case historically with good reason; the data and analytics to support pre-loss steps such as loss prevention and containment simply were not available. Now, however, the industry has sophisticated tools that make possible a shift to a pre-loss focus.
Predictive analytics refers to a set of tools designed to identify trends, patterns and correlations that otherwise could remain unnoticed in disparate data sources. Artificial intelligence and machine learning are foundational elements of predictive analytics, which facilitate benchmarking and outcome forecasting. Geospatial analytics expands on predictive analytics with traditional data to include the context of location, timing and historical perspective. With a geospatial approach to predictive insights, risk professionals can visualize and consider not only events that might happen but also where and when they could occur.
Asking and answering new questions
To illustrate this shift from post-loss to pre-loss action, let's consider some of the questions that predictive and geospatial analytics can consider:
These are just. a few scenarios, but already it's clear that predictive and geospatial analytics allow organizations to ask — and answer — a variety of questions they might not have even considered before, let alone apply to their business strategies.
With natural language processing integrated in analytics platforms, questions such as these can be asked as they arise — without the need for translating queries into standard frameworks. It's possible to have a casual conversation with data about risks and business challenges that was impossible previously. Sentiment analysis, text analysis and word trending in unstructured data fields are additional capabilities that make predictive analytics powerful tools in risk decision making.
Foreseeing the next card
Anyone who has played or watched a game of blackjack, or 21, will understand that the ability to predict the sequence of dealt cards can fundamentally lower the players' odds and greatly increase his or her chances of winning. For example, if a player is dealt a card worth 10 points and knows the second card in the deck is likely to be of equal value, that insight may cause the player to refuse a third card, maximizing the chance of beating the dealer to 21. Knowing what cards are likely to come up also can prompt gamblers to increase their bets and their winnings.
Similarly, the ability to predict claims and loss events can make an enormous difference for risk professionals, their organizations and their insurers. Analytical models therefore are trained to predict with high confidence the second and third "cards" in the game. A predictive model lets risk professionals know what's coming up, and respond accordingly to mitigate risk or reduce litigation costs. The "winnings" in this scenario can include improved safety, lower loss costs and preservation of capital — all of which can be reinvested to support the underlying business.
Surfacing insights and trends in data are not about delivering software solutions. Predictive and geospatial analytics are much more about partnering with risk professionals to answer business questions.For more information on Ventiv's analytics, please visit www.ventiv.com.
Mark Tainton is the Global Head of Analytics at Ventiv Technology. He has more than 30 years of experience in data analytics. Before joining Ventiv in 2022, he held various executive roles at global organizations, with companywide responsibilities including business intelligence reporting, data analytics strategy and data governance.
Lorem ipsum dolor sit amet, consectetur adipisicing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut.
Lorem ipsum dolor sit amet, consectetur adipisicing, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut. Ut ad minim veniam.
Vestibulum ante ipsum primis in faucibus orci luctus etel ultrices posuere cubilia Curae.
Lorem ipsum dolor sit amet, consectetur adipisicing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut.
Sed ut perspiciatis unde omnis iste natus error sit voluptatem!
Nemo enim ipsam voluptatem quia voluptas sit odit aut fugit!
Ut enim ad minima veniam, quis nostrum exercitationem ullam!
"Et harum quidem rerum facilis est et expedita distinctio!"
"Nam libero tempore, cum soluta nobis est eligendi."
"Temporibus autem quibusdam et aut officiis debitis!"
