The use of artificial intellgence has increased exponentially across the insurance industry. Right from using simple chatbots to create a smoother customer experience to making sense of their existing data tgo create an impact in people’s insurance policies, AI has already started playing a crucial role in insurance companies.
Where has AI helped for insurance companies#
Some of the use-cases we’ve helped our clients in the insurance domain using AI are:
- Risk analysis using AI in insurance underwriting.
- Fraud detection using AI in insurance cliams.
- Conversational chatbots that use AI to automate claims submissions by clients from whereever they are.
- Using AI to improve process efficiency for insurance claims.
- Using AI to help automated claims approvals for clients.
- Creating predictive analytics dashboards for CxOs to help them make bettwe decisions.
And so much more. The use-cases are nearly limitless when it comes to using AI in the insurance industry.
Understanding AI for Insurance#
Before we could start exploring the possibilities of AI in Insurance, it is important for us to learn what we mean by using AI for Insurance. To begin with, the term artificial intelligence is vast and wide. Meaning, machine learning, predictive analytics, intelligent automation and so many such machine-driven actions fall under artificial intelligence.
Simply put, the decisions that humans take, repeatedly, when automated using a certain set of algorithms that are data driven, constitutes to what we call Artificial Intelligence.
In an industry like Insurance companies, imaging this scenario:
Currently, the decision of a claim getting approved or rejected depends on the training, experience and limited data that are available to the person taking that final call. This could be time-consuming as well as troublesome considering the bias that people could be carrying.
Now imagine the same scenario with two things in mind, that is automated using AI:
- Experience - fed, built and trained with the help of years worth of data
- Speed and accuracy of operations - comes with the available compute power, parallel processing and works 24x7.
This simple automation itself has now added a huge business value for the insurance company, helping them march forward in the industry, by providing better customer experience and return on investment.
This is where AI could help insurance companies:
- Making use of existing data (years worth of data)
- Automating repetitive tasks using intelligent robotic process automation bots
- Speed of operations
- Faster ROI since it constantly keeps improving itself
- Allows humans to work on complex tasks
AI could be complex though#
Artificial Intelligence (AI) is a technology that has a direct impact on the customer experience. This makes it easy for people to assume that they understand AI and take things for granted ignoring the complexities the AI could bring while implementing or solving a solution for a business problem.
During one of the meetings, one of our customer wanted the AI to run their entire customer service desk operations so that the users get their questions handled automatically. Though the intention was good, their systems never recorded the customer requests since they started about 20 years back. In such a case, we preferred to not work with the customer, since AI without data is nothing better than a dead-investment.
Understanding the fact that artificial intelligence and robotic process automation relies heavily on the existing data that a business would have collected.
Implementing AI or Intelligent Automation without prior data is the same as asking a two year old to manage a business process.
Cost of implementing AI for Insurance companies#
Artificial Intelligence is not the same as buying any software from the market and implementing them just like that. It does not fall under the traditional way or procuring a software product and implementing it your business.
AI is expensive. It involves people ranging from backend engineers, test engineers, training personnels, algorithm developers and so on.
Implementing an AI solution in your company is something more than just going-live today and it automatically runs kind of a practice. Implementing an AI solution is more on the iteration front.
Every single day, you need engineers to train the system to keep improving, and handle more than just what it was told to handle or at least have the data and learning model ready to support expansion in the future. The more we give context to the AI learning engine, the better it is for us to get results from it.
What do you need to implement an AI solution successfully#
For any company to implement an artificial intelligence based solution, the organization should prepare itself to provide the following resources:
- Data - the more data you have, the better it is for your AI solution. It is as simple as that.
- Clear roadmap - a very clear Product Discovery Document that has the roadmap for implementing an AI solution.
- Invest for long-term results - implementing an AI solution does not necessarily always result in immediate results. It is like hiring a new person on an organization level. They/it needs time to adopt, learn and deliver results.
- Work with consultants - this will be your immediate ROI factor. Working with consultants like us elimiates the entire risk of failing due to lack of talent pool. The amount of care Skcript puts in to train, develop and implement AI solutions by our engineers is immense. This process is our core business.
What would be the first step towards implementing AI solution for insurance companies#
The very first step is to learn from your past, and to know where you need help. As an important stakeholder, you know how your company runs, and where things could be made better. Once you know what to solve first, you will automatically have a tangible result that you can measure.
So when you implement an AI solution, and when the solution starts delivering the results, you can measure it with the past and know exactly the amount of impact the AI solution has created for your business process.
So, where do we start now#
For you to start looking at using AI for your insurance organziation, all you have to do now is simple:
- Start working with a consultant who knows what is AI clearly and have helped large Governments implement AI solutions (email@example.com).
- Work with them to build a workflow roadmap for AI for Insurance.
- Get a quotation from them.
- Start working on the solution.
- Measure the value delivered at every single step.
We wrote this since we found a ton of insurance companies approaching us to know such information. We beleive that this information would be useful for you to take the next steps in AI. You can also talk to our AI Engineering Support people to know more - (firstname.lastname@example.org).