In practice, the directive had more radical repercussions, acting as a catalyst for insurers to generate cleaner asset data – both in terms of accuracy and quality. By doing this, the data has become more than a way of assessing risk and business and exposure, but something potentially actionable.
But the big question now is how? What tools are needed to commoditise this mountain of data?
Answers are already beginning to emerge and in two ways in particular. First, we are seeing a shift from the “passive” application of data, such as mandatory reporting, to a more “active” use of data – the use of Solvency Capital Requirement data to win RFPs is a good example.
Second, there is a new interest in using the enriched data to produce risk management visualisation tools. Insurers are looking internally and, increasingly, externally for solutions to meet this objective – with companies such as custodians and FinTechs using cutting-edge technology to bring an unprecedented level of insight and analysis to risk data.
What are the potential benefits?
This shift to actively employing data carries many potential benefits for asset owners and managers alike – all of which can support business growth, help manage risks, inform stakeholders and, of course, ease regulatory reporting.
Ultimately there are many real world examples of how clean, enriched data can give insurers a better understanding of their risk and attribution, and allow for more consolidated and granular data visualisation and asset management oversight.
With coherent and accessible data, insurers and asset managers will be better equipped in their hunt-for-yield and are also better able to identify risk clusters and opportunities – putting their capital to use in smarter ways.
The process of extracting value depends first and foremost on two main elements – the ability to clean the data accurately and effectively, and how much your organisation understands the potential application of the data.
But getting to this stage is the hard part. The first element is obvious; the second is critical.
So, how is this achieved?
1. Make sure your data has been cleaned by a reputable organisation with the right experience and, importantly, a deep understanding of the Solvency II directive.
2. Educate your organisation about potential benefits. This usually is top-down and necessitates C-level support.
3. Link your strategy with potential data applications and see where data fits with different elements of strategy.
4. Think commercial benefits. Up to the 1 January 2016, Solvency II was about reporting. The current shift is from regulation to commercial applications.
5. Educate your organisation to look at data in different ways. For example:
a. Can we use our data to increase our group reported solvency ratio?
b. Can we use data to tailor fund solutions to insurers, not just provide off-the-shelf packages that may not fit with clients’ needs?
c. Do we as an insurer have the right asset managers managing our assets? How do we view their investment decisions?
d. How do we cut time-to-market in reacting to market events that impact our asset portfolio value and hence reported returns?
A future revolution?
As the industry evolves, asset data becomes more critical. Add to this the actionable and visual elements of data with other FinTech trends, and we are looking at a software and hardware combination that stands not just to impact the operations value chain and operating models, but also the competitive landscape.
At present this is still an evolution. In the future, we may yet face a revolution.
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