Decision Management and Analytics in Insurance
AxionConnect helps insurance companies to develop analytical frameworks using a wide range of statistical application to solve complex business problems.
- Acquisition Programme
- Lapsation and Persistency
- Risk Management and Capital Provisioning
- Agents and Business Partners
- Revenue Forecasting
Using advanced cross sell and UP sell models, Insurance companies can optimize the use of low cost channels and target the right customer with the right product. With recent observations and appeal from IRDA to insurers on product miss –sells, there is a certain impact on attrition. Our simple and practical solutions assist in putting a data driven selling process in place.
Lapsation and Persistency
Using a overall customer contact management framework, AxionConnect assist insurance companies to effectively manage retention programmes using advances segmentation and predictive models. With different treatment to traditional and ULIP linked products organizations can optimize our knowledge in using advanced analytics.Persistent Modelling
Persistency rate has always been a major concern for life insurers. It is the renewal rate of policy pool/ portfolio by avoiding lapses and surrenders. It has been realized that the advanced statistical approaches and techniques plays a key role in addressing the phenomenon due to an inherent stratification in the population of lapsed policies.
Hybrid model is basically a multi model approach which gives optimized profit quadrants. Claim Probability model and Claim Expectancy model in conjunction will generate most optimized set of customer with less probability of claim and long claim expectancy window.
Risk Management and Capital Provisioning
Higher incidents of non normal claims impact the complete underwriting fundamentals and product policy. AxionConnect can allow insurance companies to have deep insights into the claims profiles and identify and predict outliers for business teams to save millions.Claim Loss Model
This model is based on VaR methodology which gives expected and unexpected loss from a particular portfolio. Expected losses are embedded in technical provisioning for the running business and unexpected losses should be absorbed by capital reserves. The aggregate loss distribution from cumulative business portfolio will represent the entity level capital reserves and technical provisioning.
Probability of Claim Modelling
This model gives the probability or chances of claims for a customer. The quantified likeliness of claim for a particular type of customer helps underwriters to take efficient decisions to approve or reject a policy. This probability also supplements the product pricing in the sense that a customer having high probability should be charged high premium. This is one of the parameter used in ALM for cash flow and capital charge computation.
Claim Expectancy Model
This model gives the expectant time window when a claim is expected from a customer. The expectant time window for claim from a particular type of customer plays key role in decision making for underwriter and capital replenishment. The customer who is likely to claim in a short period for a policy should be charged a higher premium or such application should be rejected.
Ratemaking modeling is an approach in insurance industry to price the products based on the risk associated.
Business can use advanced modeling techniques to automate the issuance of policies with straight through techniques. Unlike the traditional stochastic way of calculating loss and provisioning capital, AxionConnect helps insurers to significantly predict adequacy using stastical models.
Agents and Business Partners
Third party channels are a very key sales arm of any insurer. Their behavior and profiles determine the product they are likely to suggest to customers. A deeper understanding of these profiles allows insurers to design more robust agent on boarding and product selling strategies.
AxionConnect can assist business teams with frameworks to assist the likelihood of premium collection with multiples channels. This will allow organizations to plan the gap and leverage resources appropriately.