More and more insurance companies are automating their processing systems to reduce throughput times for onboarding and claims processes. With less and less manual effort, insurers are reaching transparent, qualified decisions to determine whether they will insure something or someone, and at what cost to the insured. Automation with ACTICO insurance software creates flexibility in onboarding and underwriting because business users create and modify rules for decisions themselves.
Automated decisions ensure that the manual effort is reduced and only special cases still require manual processing. The costs for onboarding and underwriting go down.
Business experts can use ACTICO insurance software to adapt the rules for decisions or add new ones themselves. New rules are productive right away. This reduces time to market.
Reduced response times and a high degree of automation allow insurances to react more quickly to applications and claims. This improves the client experience and enhances client loyalty.
Digital processes can be achieved with rules that check applications and claims automatically. Requirements resulting from tariffs and business policy are represented in insurance software rules. Onboarding and underwriting decisions are then made automatically. This allows insurance companies to focus on exceptional cases that cannot be decided automatically.
ACTICO insurance software allows insurance companies to reduce paper-based data collection and processing. This minimizes the number of manual transfers, eliminates paperwork, and reduces the cost of archiving and manual rework. Onboarding and underwriting processes become faster and more reliable.
ACTICO insurance software maps the assessment and decision logic for all manual and automatic processes in the form of rules. These rules can be read and adapted by business users and IT. They can adapt them quickly and easily. All rules for onboarding and underwriting and all data are documented for auditing.
Insurance companies can use their clients’ data to automatically create risk models for underwriting and claims management. Machine learning provides methods that make better risk decisions and complement rule-based models.