Expert view: Aggregating risk in innovation

In a previous life running an international IT division for a multinational company, a large legacy system had to be converted to alternative technology. The project was scheduled to take more than 18 months, across two countries, with a multi-million dollar cost of conversion, new software, and hardware. The system was a major revenue earner, and the switchover from old to new had to be seamless. 

In the event, the project was delivered six weeks ahead of schedule and under budget. My boss at the time, while full of congratulations, let me know he had taken out insurance for late delivery. Oh, ye of little faith! And yet, given the critical nature of the project, what a sensible thing to do.

This set me thinking recently about assessing risk in innovation projects – insurers should be good at assessing and underwriting risk.

Managing risk

Let’s take an innovation project portfolio. Some projects are at the idea stage, some prototyping, some failing, some scaling. The money and time being spent on them should be as little as possible to get them to a more certain stage or fail. 

We have a risk book/ledger here. The projects that fail are on the debit side – in effect, claims. The projects that scale are on the credit side and their return on investment will be somewhat predictable. The projects in between? They are trending one way or the other.

A question to ask is: what return is acceptable from the whole portfolio of risk? 

Also, what is an acceptable overall combined operating ratio with specific targets for claims, commissions, and expenses? This would then provide a clear view of risk/return on an underwriting profitability basis. 

We can, of course, mitigate the overall risks in many ways to improve the ratios and margin. 

Involving clients

Firstly, make sure projects follow a process. At Ninety we have a 123 Framework – ideation, one-day MVP, two-week prototyping, three-month build, and launch. This involves clients at every stage, Agile development, money only allocated on passing a stage, and increasing confidence and certainty. 

Secondly, taking the example of reducing risk from project specific insurance in the construction sector, specialist consultants from insurers analyse the key risks of the project and offer practical solutions and advice. Innovation lab staff should be undertaking such tasks. Ninety’s Lab-in-a-Box helps set up such a support function.

Thirdly, partnering with others.

I have some concerns that partnering with an early start-up insurtech actually increases risk, but there are some more mature insurtechs that could provide proven technology and reduce uncertainty. They can be part of a one-day MVP to explore options.

Fourthly, shared risk. This may be used as a strategy to improve the commitment of stakeholders to a project. For example, if underwriting and claims share the risks of a project, it may be more likely to succeed versus a situation whereby claims bears all risk.

The above is not a complete list of course, but, lastly, the data you can collect on projects – there are many data points – could provide the basis for a predictive risk model. By leveraging such learning over time, and by using the data to design and train the model, you have the opportunity to build a competitive advantage regarding innovation.

Short term challenge

It will be a challenge in the short term to show the results that can be achieved. However, early indicators can be collected for projects as uncertainty decreases, and identifying such indicators is key to improving model performance. In addition, you may need to build algorithms that are specific to your target population.

Who knows – in the future – could the insurance sector be leading the way? I hope so. Thinking about it, perhaps this new template would work for many industry sectors attempting innovation projects. 

Only time, along with some fresh thinking and bold risk-taking, will tell…

ninety.co.uk