I N D U S T R Y I N V E S T I G A T I O N also be used to monitor an individual ' s health changes over time alongside wearable and other health data sources .
Intelligent automation – using digital twins to scale underwriting capabilities
The key to leveraging technology effectively is to enable underwriters to examine risk profiles and make decisions without physically having to work through the vast quantities of data available . Making a platform available to underwriters which combines all the disparate data in a structured way and a centralised location is the first step to driving efficiencies . The next step is to enable underwriting decisions to be made automatically .
This can be achieved through decision engines which , given the correct parameter inputs , can provide an output decision – provided all the required inputs exist and the decision engine rules have been set up to cater for scenarios encountered . Decision engines are really a form of RPA ( Robotic Process Automation ) in that the rules must be set up carefully upfront and the system will then step through the decision tree structure in a logical fashion , reaching an outcome which is pre-defined .
A natural evolution from traditional decision engines is to use another form of technology known as digital twin modelling . Digital twins are AI-trained models which replicate human decisions , given specific data inputs and required output decisions . These models allow insurers to model underwriting decisions without the need for complex decision tree structures .
Expert underwriters create a matrix of the data inputs they consider , and sample data is then presented to the underwriter for decisions . The AI then learns from the expert and creates an algorithm which mimics the underwriters ’ decisions . This algorithm can then be deployed into the business process as a virtual expert which makes automated decisions on data presented to it . This type of AI embraces human judgement and bias in the decision-making process , something that a decision engine is simply incapable of doing , as it needs to follow very specific rules that have been pre-programmed . These decision models will obviously only ever be as good as the human decision-makers they were modelled on , therefore the best
INSURERS AND HEALTHCARE PROVIDERS MUST BE WILLING TO EMBRACE CHANGE .
people in a business need to be used when engaging with this type of technology . By modelling the best people within a business means that that insurer is maintaining its underwriting expertise and USP , so a digital twin of one business will not be the same as another company ’ s . While still relatively new , this technology has been used very successfully in many industries across the globe , including banking and insurance verticals in recent years .
Making digital data sets available to AIdriven algorithms for decisions allows for an automated business process , involving little to no human intervention . Only where a digital twin model is unable to create a decision would a human underwriter be needed to evaluate the data presented , potentially request additional information and then make a final decision . This end-to-end automated process is something that , until recent years , has only been discussed theoretically . Now that the right technology toolsets are available , this theoretical process is now a reality .
The automated process described above is equally applicable in other insurance business processes , most notably claims and risk renewal processes , where senior human decision-makers typically need to spend vast amounts of time analysing different data sets and making decisions which are both costly and time-consuming . This results in efficiency gains for the insurer and a far improved customer experience for the consumer .
Ultimately , insurers and healthcare providers must be willing to embrace change and adapt to a more open and transparent process with clients . Having a platform that connects to an entire ecosystem of data , solving data interoperability and providing a unified view of a consumer ’ s individual health profile , however , delivers strategic value that can help insurers and healthcare providers unlock new business growth and reduce risk across their books of business . �
www . intelligenthealth . tech 43