Reinsurance Company

Reinsurance Company

With the help of a data management platform, this wholesale provider of reinsurance created its own common data categorization language and self-service data-driven applications.

Reinsurance Company

With the help of a data management platform, this wholesale provider of reinsurance created its own common data categorization language and self-service data-driven applications.

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We need to, on very short notice, combine massive amounts of data, internal and external, including satellite pictures and data that captures our experience and gives us the knowledge to identify the impact on agriculture, infrastructure, or people. It becomes a challenge, how fast can we integrate the data. And then when disasters happen, if we can be even faster than our clients at assessing the situation, we can really streamline the whole value chain, 'Hey, we can pay you this amount of money.'

Head of information standards and governance

Leading Reinsurance Company Fuels Innovation with Data Fluency

Effective data management enables standardization, automation, and algorithmic insurance

When a catastrophe strikes—a natural disaster or widespread disease—insurance companies alone can’t take on all the financial risk; They depend on reinsurance companies as backup.

"We are a knowledge company," said the head of information standards and governance for one such reinsurer. "We need to, on very short notice, combine massive amounts of data, internal and external, including satellite pictures and data that captures our experience and gives us the knowledge to identify the impact on agriculture, infrastructure, or people. It becomes a challenge, how fast can we integrate the data. And then when disasters happen, if we can be even faster than our clients at assessing the situation, we can really streamline the whole value chain, 'Hey, we can pay you this amount of money.'"

The reinsurance company implemented its data management practices with TIBCO as its foundation, receiving and delivering data to more than 300 upstream and downstream systems.

Creating data standards and a data language

Reinsurance companies need to understand the risks and regulatory bodies. For nearly every risk the world could face, the reinsurer has specialists on hand who understand the problems and make global and economic organizations aware of them.

One of the biggest challenges for the reinsurer was creating data standards. When the company first started to do this in the 1990s, terms such as "master data management," "reference data," and "metadata" weren't widespread; the business just knew that it needed a common language for talking about data.

The information standards and governance team initially focused on reference data and master data management and soon realized that once the data was standardized, they could start building applications and combining the data to make it more efficient for operations. Through data, the entire workforce can be linked to the cost center, to organizational units. Data can be linked to vendors, so users can see which analytics projects are within which area in the company, and who is working on them. Connecting to vast amounts of data and providing the right data to the right people for fast analysis is key.

Mapping data automatically for immediate use

The company is now focused on mappings between data assets and building on top of its data standards application. "We want to understand the data relationships within our firm, and to the outside world,” said the head of information standards and governance.

Because of its data standards, data from dozens of internal and external platforms is sent to the integration layer, then through the data management platform to data-driven apps and dashboards. When a provider sends data on a specific company, person, or organization, it’s automatically mapped within the company’s systems and made quickly available for risk predictions and payout assessments.

Innovating as an ecosystem

The firm's data management and data distribution automation has opened possibilities for business innovation. Predictive analytics automates parametric insurance, which insures against situations in which certain parameter values are exceeded. If the stated parameter values are met, the algorithm sets up the claim payout.

As an example, using just one prominent service for mobile and worldwide flight data, the company runs a flight-delay insurance program for as little as five euros. Because of predictive analytics and the history of the data, the firm has actual live flight stats, allowing it to offer a payout to the client and still be profitable.

Using data as a platform for innovation, the company doesn't mind failing fast and failing often because experimenting with different tools and datasets is an opportunity to learn. According to the firm, part of doing business is gaining knowledge about data and technology.

"Innovation is just a change to an ecosystem that creates more value, and this is what a lot of people don’t see," said the head of information standards and governance. "A lot of people think innovation is the person sitting in the room who has a brilliant idea, but that's not how it works. Innovation only happens from constant failure. It's about not being afraid to ask the stupid questions, to challenge results, and try new things."

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systems needing data
Case Study