10 September 2017 Insurance

Creating data you can trust

Big data holds great potential for re/insurers, but only if they can validate and thus rely on it, Frank Fortunato and Kunal Patel of CATEX tell Monte Carlo Today.

While all insurers and reinsurers understand the potential of leveraging so-called big data, most have a fundamental problem that prevents them fulfilling this in any part of their business: the inability to efficiently collate disparate sources into data they can trust. The effort that requires is often too costly and the raw data they’re using is often fundamentally flawed and incomplete.

That is the view of Frank Fortunato, chief executive of CATEX, one of the original insurtech companies, founded back in 1994. CATEX offers a number of data transformation products powered by artificial intelligence that are licensed to clients around the world. Fortunato says demand has rocketed recently as more companies are trying to get a better handle on the vast amount of data they’re receiving, and in response CATEX has improved and widened its product offering.

“In an era of big data, one of the biggest challenges facing our clients is how to import data coming in disparate formats and layouts. Analysing big data is impossible if there’s no easy way to transform it into structured data that they can trust,” Fortunato says.

“Every re/insurance CEO is facing this challenge at the moment and they are facing it at many levels within the same organisation,” he says. “They have the raw data but they have no easy way to transform and validate the data. Without that, the conversation stops at the water’s edge. Everyone has this challenge and that means that they are receptive to talking to us about to solve the problem.”

CATEX processes more than $7 billion in premiums and claims in over 20 countries and seven different languages.

“We see our share of challenges with data imports. This is especially true with delegated authority and exposure management systems where data comes from a variety of sources with varying degrees of data capture and export capabilities,” Fortunato explains.

Solving the problem

CATEX’s solution to this problem is the Data Vera suite, a software-as-a-service (SaaS) product designed to import, transform, validate and autocorrect data, while maintaining detailed audit logs of all changes. It also exports data in a variety of industry standard formats at the click of a button.

Kunal Patel, chief technology officer of CATEX, explains that the system is a very practical, easy-to-use solution, which has the capability to learn and adjust the way it processes data based on past experience.

“It is able to take data from many different sources and process it quickly and accurately in a way that also logs all corrections that have been made so they can also be checked as needed,” Patel says.

“We had a few goals in mind when we designed Data Vera: no pre-processing of the files (mapping templates); ability for the software to learn as it processes data; automatically correct data based on that learned behaviour; and maintain a detailed audit logs of all the changes being made,” he explains.

“Data Vera does just that. It uses algorithms and previously processed data to recognise data patterns in files sent by different users and systems and tweaks the way it validates/autocorrects data.

“It crunches through millions of records of data using our high processing computing environment in seconds to make these decisions and informs the user of the changes using colour codes. The best part is that the more data it processes, the smarter and more efficient it becomes.”

CATEX offers Data Vera as two products: Data Vera for Binder Management, a delegated underwriting authority management system to manage facilities and bordereau data; and Data Vera for Exposure Management, a product mainly used by cat modellers to address data challenges around COPE management; address cleanup/geocoding; modelling vendor integration; and analytics. Both products have a sophisticated workflow management and robust team collaboration/communications capabilities built-in.

Patel adds that he has witnessed growing interest in this product in recent years, from different types of companies and from different business groups within companies in order to better use big data to support a variety of business activities.

“Our clients are looking for a single solution that allows them to address a variety of data challenges within their companies” he says. “We have enhanced the usability of Data Vera to make it more relevant to the different groups within a company for their day-to-day work.

“Validated data that a company can trust usually involves a team of individuals spread throughout the company and often spread across a number of time zones. We have enhanced the capabilities in our product that allows the whole team to collaborate and communicate online as the data moves throughout the organisation.

“It is about data that the company can trust and use throughout the organisation, regardless of its origin.”

Fortunato adds that the application of such technology also has the potential to also be a force for good in the industry in a wider sense. He notes that while Hurricane Harvey could cause economic losses of some $100 billion, only around 20 percent of this will be insured.

“People think the coverage gap is something that exists in emerging markets but we have seen time and again how big it can get in developed economies,” he says.

“With Harvey, the 80 percent that is not covered represents a huge amount of data that needs to be taken in, analysed and understood. Using data in that way can help close the coverage gap and help the industry at the same time.”

Frank Fortunato is the chief executive of CATEX. He can be contacted at: ffortunato@catex.com

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More on this story

Insurance
30 October 2017   While the soft market encourages re/insurers to get a better handle on their data, this momentum is unlikely to abate even if the cycle now reverses and the hard market returns, says Frank Fortunato, chief executive of CATEX.
Alternative Risk Transfer
16 October 2017   The wide divergence in loss estimates given by the risk modelling community in the aftermath of the US hurricanes could prompt more re/insurers to invest in their own analytical capabilities and get a better handle on their data.
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1 August 2017   Now in its third year, our Influential Women in Re/insurance report remains one of our most anticipated pieces of research and extremely popular online. The nature of the report is starting to change, as are the responses given by those we profile.

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