Modernize Policy Administration
Increase agility with SMARTS™ decision management
- Implement policy changes and launch new products faster
- Operationalize AI, machine learning, and deep learning models
- Reduce operational costs while delivering a better customer experience
- Improve the quality and consistency of decisions
- Increase flexibility, scalability, and transparency
Manage Complexity with SMARTS™
Legacy Policy Administration Systems Need an Upgrade
Increasing competition, regulatory activity, consumer expectations, and remote workforce is pushing policy administration systems (PAS) to their limits. While PAS have enabled insurance firms to create a single source of truth, automate processes, and manage the entire policy lifecycle, many firms are finding that their system has become too inflexible and costly to maintain. Modifying policy rules often requires significant IT resources, preventing firms from adapting quickly to regulatory changes and capitalizing on new market opportunities. In addition, the underlying code that automates risk and other policy-related decisions are often inaccessible or incomprehensible by the business analysts that manage these decisions. As a result, redundancies and errors accumulate over time.
The SMARTS™ Path to Next-Gen Digital Transformation for Insurance
SMARTS™ is a modern, enterprise-level, application-agnostic, decision-management platform that enables non-technical analysts and SMEs to easily automate, manage, and continuously improve business-critical decisions in daily operations, whether explicit or AI-driven, with minimal IT resources. Whether you’re a startup or established P/C, Life/Annuity, or Health insurance firm, SMARTS™ enables you to strategically augment your PAS through a microservices approach. Quickly start with one application and easily expand into other applications across the organization.
Isolate business rules and code that automate decisions across disparate systems and manage them in one place. In this example, the logic for calculating an auto insurance quote is displayed as a decision flow.
Manage decisions from our intuitive, integrated user interface. View data and KPIs in context of the decision logic.
Build custom interfaces (Business Apps) that control access and allow users to easily perform specific tasks without code. In this example, non-technical users can quickly modify eligibility and risk tiering rules without having access to the full underwriting decision logic. You can apply your own logo and CSS styling to the Business Apps.
Establish simulations and champion/challenger experiments to test different strategies on sample and live data in a low-risk manner.
Integrate machine learning and other data science models into your decision logic and create new models directly in SMARTS™. In this example, a user is exploring 3-field correlations (Maximum Accidents, Average Work/School mileage, and Claim Based Risk Indicator) through our BluePen modeling tool.
Integrate SMARTS™ into your business process or policy administration system through an API call.
Monitor performance of models and decisions in real-time. Trigger alerts when certain thresholds are crossed or patterns are detected.
What If You Could Make Policy Changes 5x Faster?
Hong Kang Life Insurance is one of the top national life insurance companies in China that desired to unify and modernize their underwriting and claims systems. Through SMARTS™, they were able to achieve the following:
- Create a global rules management system
- Enable four business analysts to manage of 100% of underwriting rules and nearly 70% of claims rules without IT
- Reduce average application processing time from 1.2 seconds to 50 milliseconds
As a result, they were able to make policy change 5x faster, reduce maintenance costs by 70%, and launch 23 new products in just 6 months!
FEATURED BLOG POSTS
Tips for Business Analysts on How to Write Business Rules Throughout the years, the business rules experts at Sparkling Logic have provided tips on how to write business rules. This post consolidates some of the best of the best with example business rules. Note, the...
Predictive Modeling Examples Predictive models can be used to improve decision making throughout an organization’s daily operations and throughout their customer’s journey. Examples of predictive modeling applications include (but are not limited to): Customer...
You are about to modernize or develop a new automatic decision-making application, based on data, knowledge, or a combination of both. You wonder whether our SMARTS platform meets your business needs and technical specifications. Nothing is better proof of a product's...