At QED we understand how your business can gain significant value through insights that can be generated from the efficient and complete use of your available data. That’s why we offer access to systems and skilled resources to assist in the development, deployment and monitoring of highly integrated analytical systems that will drive business value.
In order for you to be able to understand the challenges and strengths of your business, it is essential for you, as a decision maker, to be able to analyse your business in a critical way. In today’s fast-paced business world it has become increasingly important for this information to be available in real time in order to make decisions faster than your competitors. And the first step is to generate dashboards and provide this data in a way that can be easily analysed. Many businesses already have a business intelligence functionality. The modern dashboard, however, does far more than just tell the story of where your business has been. It is vital to know too where the business is going. And it is through parameterisation and predictive analytics, that the modern dashboard allows you to do just that.
Using machine learning we can analyse vastly more variables than current available models. This allows new and previously hidden patterns to be detected, which in turn creates a deeper understanding of the main drivers of churn and lapse. These results can then be integrated in to your current IT and call-centre infrastructure, so that your existing business functions can predict which customers are likely to lapse and introduce mitigating strategies.
At QED we understand that current customers can constitute one of the greatest untapped sources of sales, and that current customers thus often form a portion of any target market for existing products. Using data that you already possess, our cross-sell models through the use of machine learning, can facilitate this sales process by identifying which of those existing customers are most likely to purchase a product they don’t have.
Using statistical models, and using available data, we can discern patterns that identify claims with a high probability of being fraudulent. Our models facilitate focused initiatives that identify a higher proportion of fraudulent claims at a reduced cost – a significant benefit for fraud departments, particularly if they are under-resourced.