INTRODUCTION
I remember the first and last time I went into a casino. There were bright lights and loud sounds everywhere, and they were playing ABBA music in the background. I had £10 in my pocket. I started out by playing the blackjack (or 21) tables. Within ten minutes, I had won 8 out of 10 hands and was up by £50. When I then decided to call it quits at the blackjack table, the dealer looked at me in surprise. I don’t think he was used to someone walking away so quickly after having such a successful run.
I learned two things that day. The first is that gambling could be a really easy way for me to make lots of money in a short amount of time, but most likely wouldn’t be. The second is that I could easily develop a gambling addiction, which is why I refuse to gamble again. However, people gamble in a professional manner all the time. Stockbrokers and investment bankers make gambles every day. And in the insurance industry, underwriters gamble that the risks they underwrite will make the company money. Granted, underwriters have a wealth of industry knowledge and experience, so their gambles are nowhere near as risky as me going into a casino.
THE COMPLEXITY OF UNDERWRITING
When underwriting risks, there are many factors to consider. To underwrite someone’s car insurance, you have to consider the experience of the driver, the risk of the vehicle having a mechanical failure, the present value of the car, and so on and so on. When it comes to something a bit larger, like a space rocket, the complexity becomes orders of magnitude more difficult. There you have to consider who is building the rocket, what technology it is using, the duration of the spaceflight, and many other considerations.
MAKING UNDERWRITING MORE INTELLIGENT
With all of these factors and the complexity involved, whatever you can do to help the underwriter become more ‘intelligent’, the quicker and easier it is to do business.
At the end of the day, underwriting is about looking at a set of data and determining whether a risk is good or bad and what it will cost to carry that risk. By way of introducing the concept of intelligent underwriting, I will cover three things that you can automate:
- Information-gathering
- Decision-making
- Workflows
Information-gathering
As mentioned, when underwriters are determining whether they want to carry a risk or not, they have to do a lot of information-gathering. As such, anything you can do to make it easier to gather this information would greatly help the underwriter.
You can build data integrations from external systems. These can then pull information from public datasets, e.g. court judgments, credit agencies, company overviews. You can also pull information from internal datasets, e.g. policyholder claims history, bespoke risk tables. Automating this data retrieval would help ensure that the underwriter has all the relevant information required to make an informed decision.
Decision-making
The second thing that can help underwriters is to automate some of the decision-making process. Certain parameters can be set, e.g. building is no closer than 50 metres to a river, driver has had their licence for a minimum of two years, cargo ship is not to carry explosive materials, and when an insurance submission falls outside these parameters, it can be auto-declined. This will free the underwriter to focus on the submissions that have a possibility of being underwritten and, therefore, really adding value to the business.
Workflows
The third thing that will benefit underwriters is automating the workflows. Currently, most workflows are manual. Oftentimes, the underwriter will receive an email that will kick off the workflow and then the approvals and communications will all be email-based as well. You could create a central portal that can drive the workflow, which would trigger automatic submissions, approval requests, and communications. This would free the underwriter from the mundane, manual processes and allow them to focus on the value add and complex cases.
CONCLUSION
As you can see, helping to automate the information-gathering, some of the decision-making, and the workflow will make underwriting easier and potentially less risky. It frees the underwriter to focus on the things that will make the insurer money. And while this sounds like something that should be relatively easy to do, it’s actually notoriously difficult to get right. There are many ways that you could do this though. Whether you buy a system or leverage a low-code platform to build your own, Endava has a history of helping underwriters do just this. I would love to help you make your underwriting process more ‘intelligent’. You can take a chance on me.