In the Insurance Industry, data forms the basis of the information that is used in the decisions, which shape the long term plans of each company, as well as the day to day decisions made by underwriters, brokers and other individuals. Data quality is a significant concern for most actuaries.
Duplicated policy records create confusion for the users, as premiums and claims could easily be misaligned.
Even if a small proportion of data is of poor Data Quality – their impact on underwriting decisions can be catastrophic. The business impacts of poor quality data have the potential to be severe a view that is shared by the regulators, as they focus upon the quality of the data used throughout an organisation, and within the requirements of Solvency II.
An EY Global Insurance CFO Survey (2014) of financial and actuarial executives at insurance companies which reported that 66 percent did not have access to the quality and granularity of data required to do their jobs most effectively,
The Medical Insurance fraternity world over has several issues – one of them being related to Multiple Claims being authorized by a doctor for a single individual either against same plan or multiple plans.
Billing for services not rendered, misrepresenting dates of a service, billing for a non-covered service, getting same drug prescriptions from different physicians, misrepresenting locations of service are some examples of possible fraud. Some of this may be genuine – some may be an inherent pattern of fraud waiting to be uncovered by identifying patterns across claims.
Underwriting uses contact data, particularly address data, to assess the risk on a given property and to set rates for coverage. If contact data is inaccurate, an insurer may take on an unknown risk or provide an incorrect rate quote for a new policy.
Premium underpricing by 3-5 % due to lack of information results in billions of dollar loss annually
Agent Model of Acquisition puts cross-sell and CRM in hands of agents – chances of success being low
Smart Onboarding Systems not in place results in inability to take advantage of newer channels of data acquisition
Customers are largely sourced through agents – who influence the customer and prevent any direct interaction between the motor insurance company and customer. Details of data – including contact information are incorrect resulting in CRM programs being ineffective and loyalty prediction models going awry. Vehicle insurance premiums depend on past history, demographic profiles, car profile, driving patterns, mileage among other factors. A lot of this data is not properly captured or available resulting in generic evaluations.
The life insurance Industry has better data than General insurance. The challenges for Life Insurance providers are maintaining a high client persistency (renewal rate) for ensuring a profitable business. A big barrier to persistency is absence of good contact data.
Once claims are raised the insurance companies have a policy of generally reimbursing claims without harassing the customer. It is essential to have proper underwriting before issuing the policy. Here too, data is not available or analyzed resulting in poor modelling.
While the agent model kills data quality newer channels of data acquisition are throwing up newer challenges. While independent agents and call centers are still an important connection point, insurers are moving to online and mobile channels to satisfy policyholders.
Insurers are no longer relying on trained staff to enter information, they have to ensure the accuracy of self-entered information from policyholders. Unfortunately, the increasing number of channels is hurting data quality within insurance organizations.
How can Ixsight's solutions help the insurance industry?
Whether data capture is through Agents, channels or online - Ixsight’s intelligent onboarding systems can prevent Data errors and do validations without later rework or need to reach out to customers to correct misinformation. During onboarding, one can also check whether the customer has a previous policy.
Data quality & identity management for marketing, persistency and underwriting
A deduplicated and cleansed database can guide informed decisions on agency management, business development, underwriting and claims. This increases KYC integrity, MIS accuracy, persistency and strategic decision making.
Claim patterns analysis
Prior to disbursing claims – sophisticated Deduplication system can identify common patterns across claims within a time period, across providers, doctors, lawyers and motor vehicle garages.
Data of multiple injured claimants in low impact accidents etc. can be analyzed to detect any unnatural patterns. Should there be “Medical notes” stored in electronic forms – Ixsight can text-analyze this to relate it to claim for any major mismatch. This can also help insurers in their subrogation claims.
Identify location of service providers closest to customer and customer catchment analysis
Insurance policies are sold online, through banking channels and agents. The competition for the customer is high. Understanding customer-penetration by locality is very useful for up-selling. Location data can also be used for fraud management.
Unhappy service is a major cause of Switching Services. Ixsight’s solutions can analyze feedback data to deepen customer engagement and increase customer satisfaction and delight.
Specific compliances like IRDA – rural classification
Financial inclusion or reporting is required in some countries like India. Insurance companies need to have an auditable report on policies sold in rural areas. Ixsight’s RuralClassifix can help in this.