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Summary
- As data sets continue to grow in complexity and size, proactive data management practices are considered to be synonymous with forward looking risk management.
- While it is easy to identify the problem of lacking data management practices, improving it comes with its own challenges.
- Set a clear risk management strategy. You may have a strategy to review and optimise how much insurance you buy versus how much risk you retain, so prioritise asset data which will help you make this decision.
- Procuring, and maintaining the best available data from across a business is a team effort, but there are clear benefits to be had for all.
- To build a successful and effective data management strategy, both buyers of insurance and insurers must work closely together to unlock better and more suitable coverage, better pricing and better risk management conversations.
- Data shared with the insurance market needs to improve – it needs to be better structured, more complete, and users need to be confident that it is accurate. Research what tools are out there to make that goal a reality.
- Explore using tooling to help improve relevance, completeness and accuracy of data and to assess overall renewal preparedness.
As data sets continue to grow in complexity and size, proactive data management practices are considered to be synonymous with forward looking risk management. And risk managers who prioritise superior data quality will secure better conversations about ongoing risk management priorities with their insurers. However, with data quality becoming an increasingly critical focus area, what steps do you need to take to transform your data management framework and what are the challenges to reaching that goal?
Barriers to entry
While it is easy to identify the problem of lacking data management practices, improving it comes with its own challenges. For example, data is often held in multiple, disparate systems and spreadsheets to support multiple processes, often differing by territory or business entity.
Similarly, it's not enough to simply possess the data - it must also be maintained. However, ongoing maintenance of data is usually not top of any risk manager’s to-do list resulting in highly time-consuming annual processes. When it comes to turning that data into one suitable format ready for submission, they are often riddled with inefficiencies.
Should risk management professionals not invest in systems to support risk management and insurance across their organisations, legacy systems with outdated methods of calculating and verifying insured value will not be enough and will often result in insurers coming back with additional requests, further adding to the administrative burden.
Five steps to breath life into your data management process
1. Set a clear risk management strategy
Insurance will be one element of this, and the use of data needs to support your overall risk management and transfer strategy. You may have a strategy to review and optimise how much insurance you buy versus how much risk you retain, so prioritise asset data which will help you make this decision. Similarly, in a loss scenario, think about how you would prioritise getting data to support your risk management decisions.
2. Collaborate internally
Procuring, and maintaining the best available data from across a business is a team effort, but there are clear benefits to be had for all. To ensure the best insurance outcomes, you need to make sure the best possible data is being sourced from across your organisation and ending up in the hands of the broker and the insurer.
Check for any leaks - are there data points being captured that aren’t making it into the hands of your underwriter which might make a difference? And if there are data points which insurers would find useful which aren’t being captured, ask yourself: “why not?”.
3. Collaborate externally
It may seem obvious upon reading, but many buyers do not know the full extent of how their data is being used. If you fully understood this, how would your business priorities and processes change?
To build a successful and effective data management strategy, both buyers of insurance and insurers must work closely together to unlock better and more suitable coverage, better pricing and better risk management conversations.
A good place to start is by building a shared plan with your insurer and broker. Share your risk transfer strategy with them, get them to understand your priorities, and make sure you understand how they use your data.
4. Data quality rules
Next up on your list should be a concerted effort to introduce minimum standards and data quality checks, starting with priority areas. Data shared with the insurance market needs to improve – it needs to be better structured, more complete, and users need to be confident that it is accurate. Research what tools are out there to make that goal a reality.
5. Use available tooling
Explore using tooling to help improve relevance, completeness and accuracy of data and to assess overall renewal preparedness. If budgets are tight, industry standard tools like Excel can help you consolidate your data and draw some focus into the priority areas.
For those who may not know where to start, we have created a valuable tool to help you effectively prioritise the collection of your property data in an order which will make the biggest impact on your insurance renewal, in terms of pricing and suitable coverage.