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Tuesday 16 January 2018

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Expert Q&A: ‘Insuring’ data quality

Written by Sophie Baker
March/April 2011

Why is data quality so important to Chaucer?

Being an insurance company, data is key to the management of our work and to the risks that our underwriters are willing to take on. We've always invested in ensuring the highest data quality, but historically the processes were manual and labour intensive. There was always the possibility of human error.

We have disparate data sources and data may not be consistent. We were aware of this and the need to address it. Also, as we are a managing agent, we receive third-party data which we may not have control over. In the past, if there were issues in the data it was sometimes a lengthy activity to locate and fix them. It was often something left to the IS department and left until the end of the month. This potentially risked delaying business processes.

The main driver behind working with Trillium Software, the provider of our data quality software platform, was to automate and speed up data quality assurance, make it more reliable and transparent.

Why did you choose Trillium Software to provide your data quality solution?

We wanted to integrate data quality into our daily processes, so we needed a tool and a way of sharing results of profiles which business people (finance, actuaries) could understand. Also, we needed business people to prioritise issues if they found them, and understand how to rectify them.

We needed a solution with suitable functionality and with a dashboard that business members could use to look at their data – we wanted a web-based tool that could be easily deployed. Trillium seemed to understand data quality and our needs. We had confidence from initial meetings with Trillium that they were looking for a partnership with Chaucer and that they would make sure we were up and running. It was right for where we were at that moment in time.

We used the product's 'out of the box' data profiling. The next stage was defining and implementing business rules. We can apply the rules to multiple data sets, which ensures consistency across our work.

What has the deal meant for Chaucer?

The deal has meant data quality has moved away from being an 'under the covers' process for IS and is now for everyone – we're all looking at data in the same way. The ownership of the issues is now being taken on by us, the business-side, and we make sure we focus our efforts.

We are improving our broker service; we will be able to deal with broker enquiries more swiftly and confidently.

The claims manager now has access to information that he previously never had – he would be waiting days from the month close process for data that is fit for purpose – and now that data is available within hours.

As our managers understand their data better, they are coming up with new ways to analyse it; and in turn they can find ways to improve that. I think as a result the confidence of business users in the raw data coming out of the data warehouse is better, and we will further reduce the rate of manual data reconciliations, and having to verify that numbers are correct.

How about going forward – what are you preparing for?

In terms of data quality we are confident that the data governance procedures now in place will enable us to meet the requirements of Solvency II. Regarding compliance, we are looking to streamline and/or automate the more lengthy manual processes.
Solvency II is a huge challenge for some insurance companies and some are better placed than others. We are seeing it as an opportunity because we are well placed.
For those organisations that manage to leverage business intelligence assets, they will come out of this with a terrific competitive advantage.

What three things do you need to do your job properly?


Clear strategy, clear sponsorship for the projects which we undertake, and funding to pay for it all.



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