WHAT WE DO / INDUSTRY SOLUTIONS
Insurance
Insurance Solutions – Overview
LatentView’s analytics offerings for the Insurance industry span a variety of functional areas and processes, such as renewals management, marketing and customer management, as well as distribution and fraud management.
Customer Management:
The insurance industry is uniquely characterized by very high front-end acquisition costs, which makes it especially important for insurers to ensure greater depth and longevity of their customer relationships.
LatentView’s proprietary CLV Framework for Insurance™ takes a comprehensive view of customer value derived through multiple sources, to provide a single integrated CLV measure which can be used across different business activities, such as:
Renewals Management:
Policy lapsation has been a growing concern for insurance companies, especially in emerging markets. Early-stage policy lapsation, driven by improper selling practices adopted by agents coupled with relatively lower levels of financial sophistication on part of the customer, has severely impacted the bottom-line of several insurers.
LatentView’s analytical solution for renewals management involves two steps:
The Policy Value-at-Risk measure can be used to rank-order policies and target collections efforts on high-value, high-risk policies.
Sales Force Management:
LatentView’s suite of predictive analytics solutions for distribution can be used at different stages in an agent’s lifecycle, to improve the volume, value and quality of business through each agent, and manage the relationship effectively.
Pricing & Risk Management:
Traditional pricing approaches, where risk is measured through very broad segments, have typically led to pricing inefficiencies such as underwriting leakage (due lower premium charged for a higher level of risk) and lost business (due to higher premium charged for a lower level of risk), thereby undermining the insurer’s profitability.
LatentView’s predictive analytics solutions can help insurers improve accuracy of risk assessment, through better prediction of claims incidence and severity, thereby vastly improving pricing efficiency. Further, more accurate claims prediction can also enable optimal claims reserving, leading to better profitability.
Claims Management:
LatentView’s predictive analytics solutions for the insurance claims process can help improve process efficiency and profitability at multiple levels:
Insurance
Insurance Solutions – Overview
LatentView’s analytics offerings for the Insurance industry span a variety of functional areas and processes, such as renewals management, marketing and customer management, as well as distribution and fraud management.
Customer Management:
The insurance industry is uniquely characterized by very high front-end acquisition costs, which makes it especially important for insurers to ensure greater depth and longevity of their customer relationships.
LatentView’s proprietary CLV Framework for Insurance™ takes a comprehensive view of customer value derived through multiple sources, to provide a single integrated CLV measure which can be used across different business activities, such as:
Optimally target customers for cross-sell / up-sell campaigns
Provide differentiated customer service basis customer value
Targeted retention of high-risk, high-value customers
Renewals Management:
Policy lapsation has been a growing concern for insurance companies, especially in emerging markets. Early-stage policy lapsation, driven by improper selling practices adopted by agents coupled with relatively lower levels of financial sophistication on part of the customer, has severely impacted the bottom-line of several insurers.
LatentView’s analytical solution for renewals management involves two steps:
Generating a predictive lapse risk score for each policy, reflecting its likelihood to lapse over its tenure, by combining data from different dimensions such as policy, customer, agent and transactions.
Combining the lapse risk score with policy value to construct a Policy Value-at-Risk™ measure
The Policy Value-at-Risk measure can be used to rank-order policies and target collections efforts on high-value, high-risk policies.
Sales Force Management:
LatentView’s suite of predictive analytics solutions for distribution can be used at different stages in an agent’s lifecycle, to improve the volume, value and quality of business through each agent, and manage the relationship effectively.
Acquisition – target the right agents for acquisition, by focusing on agents with high sales potential
Performance Management – estimate agent lifetime value, and use it to identify high-potential agents early on in their tenure
Retention – target retention and win-back efforts on high-potential agents with a high risk of attrition
Risk Management – estimate an agent’s propensity to indulge in improper selling practices, and use it to effectively manage risk and quality of business
Pricing & Risk Management:
Traditional pricing approaches, where risk is measured through very broad segments, have typically led to pricing inefficiencies such as underwriting leakage (due lower premium charged for a higher level of risk) and lost business (due to higher premium charged for a lower level of risk), thereby undermining the insurer’s profitability.
LatentView’s predictive analytics solutions can help insurers improve accuracy of risk assessment, through better prediction of claims incidence and severity, thereby vastly improving pricing efficiency. Further, more accurate claims prediction can also enable optimal claims reserving, leading to better profitability.
Claims Management:
LatentView’s predictive analytics solutions for the insurance claims process can help improve process efficiency and profitability at multiple levels:
Fraud Prediction – Claims can be scored based on their risk of being fraudulent, which can be used for:
Triage – Straight through processing can be carried out for low-value, low-risk claims, so as to reduce resolution time and thus improve customer satisfaction
SIU Investigation – Potentially high-risk claims can be flagged for targeted investigation by SIU
Reserving – Optimal reserving can be carried out for ongoing claims, using refined claims predictions
Adjuster Assignment – Adjusters can be segmented based on past performance, and the right adjuster can be assigned to the right claim, to ensure speedy resolution
Subrogation – Claims with high subrogation potential can be identified, for targeted recovery efforts
