Appsure Pty offers state-of-the-art insurance infrastructure, including AI-powered quoting, application, underwriting, administration, pricing, claims, finance and business intelligence support systems. Appsure supplies all components a challenger insurance company requires to establish a viable enterprise with support for AI, straight-through processing, emergent payment technologies, mobile support and customer-centric views. The Appsure architecture supports multi-tenancy (e.g., for brokers and distribution channels), and policies can support multiple insurers, multi-bank payment terms and premium splits.

Mark Hutson, MD Appsure, says, “Using DMN was essential in providing a rapid yet fully-featured pricing engine that supports all of our products, transparently integrates AI into the pricing process, gives fully explained prices and enabled our business analysts a direct role in reviewing and innovating pricing policy.”

About Appsure Pricing Engine

The Pricing Engine is a series of decision services based on a flexible product model using the Decision Model and Notation (DMN). This OMG standard for expressing business logic is comprehensible to business subject matter experts and deployable to a run-time system, and has allowed Appsure to develop a pricing engine that:

• Improves agility
  • Allows the business to directly and rapidly innovate, test, visualize and deploy new pricing policies and products.
  • Supports measurement of business KPIs such as commission payments, retention and discount leverage
  • Enables impact analysis of every proposed policy change on future profitability using a CI/CD approach and allows the business to visualize the impact of every suggested change.
• Ensures integrity and accuracy
  • Guarantees complete consistency between the pricing policy approved by the business and that used in the production system because these are the same.
  • Improves the transparency and accountability of business logic: every product pricing is fully itemized and explained.
  • Places and emphasis on logical completeness and integrity – reporting inconsistencies with new pricing strategies in real-time.
  • Validates all policy groups, providing real-time feedback to resolve common problems.
• Delivers transparent support for compliance
  • The traceability and transparency of models allow Appsure to be specific about its support for compliance regulations (e.g., income insurance caps, sustained support for in-force rates to established customers even after repricing)
  • Every financial metric used in pricing calculations is recorded to enable a full explanation of prices to be produced for consumers, brokers and product designers.
• Allows for integration of AI and machine learning models
  • Machine learning models are used to predict customer lifetime values, product desirability, the propensity to churn, and the likelihood of fraud and make other forecasts to enhance profitability.
  • Large language models (LLM) are used to mine and semi-automate the application procedure and provide automated QA on insurance products.
• Empowers scalability
  • With a demand-led, dynamically scalable decision service architecture, the pricing engine can price the most complex products faster than ever before.

Why DMN?

1. Appsure selected DMN because it is a widely used standard
   1. Over 20 different vendors currently support DMN in their toolsets, including FICO, IBM, Oracle, Red Hat and Fujitsu. There are several open-source tools for DMN and plenty of supporting literature. In contrast, the support for vendor-specific approaches rests only with the vendor itself.
   2. The standard has created a community of decision modelers and a talent marketplace. As a result, this skill has been commoditized – you can hire individuals from this marketplace who share a common language and can work effectively together.
   3. The standard expressly supports the interchange of models to avoid vendor lock-in. Models created in one product can be loaded into any other compliant product.
   4. The healthcare and finance industries have adopted DMN; for example, MISMO has selected DMN as the standard means for mortgage brokers, lenders, investors and resellers to exchange product details.
   5. DMN is designed to work with BPMN (process modelling) and CMMN (case modelling), widely used within Appsure.
2. Offer support for a shared vision across the company
   1. Decision models are used as communication tools, allowing live business pricing policies to be shared between subject matter experts, business analysts, actuaries, implementors and newcomers alike.
   2. Key-person dependency risk is reduced as business know-how is safely vouched in sharable, transparent decision models rather than code, which requires technical expertise.
   3. Decision modelling allowed for the rapid discovery of data provision holes.
   4. DMN Presents a single ‘prime record’ for business requirements that is both comprehensible to the business and deployable to a run-time system. This dual purpose removes the need to translate requirements into code, preventing communication errors and providing a precise, business-oriented definition of decision-making understood and often managed by the business rather than IT. DMN models are measurably aligned to business KPIs, allowing their effectiveness to be tracked. This high business legibility means that DMN models can even act as the basis of a training aid for new business analysts.
3. DMN’s emphasis on logical completeness and integrity allows it to detect and report logical inconsistencies. This rigor eliminates the errors that occur when translating specifications to implementation code.
4. Of critical importance to a regulated industry like insurance, DMN decision modelling improves the transparency and accountability of business logic. Run time models can be the focus for a post-hoc explanation of business decision-making outcomes, which is often helpful and frequently required in a regulatory context.
5. DMN promotes agility in the (model-driven) development of decisions, leading to more cost-effective automation. It ensures that decisions are easy to change by subject matter experts and that they can quickly understand the full consequences of such change.

6. DMN enables impact analysis. Decision modelling focuses on the dependencies between decisions, sub-decisions, authorities and data. It allows a rapid assessment of the business and technical impact of change (triggered from within or outside).
7. DMN commoditizes business knowledge. Decision modelling insurance pricing offers a vehicle for Appsure to sell its pricing expertise and compliance with regulatory standards, legal constraints and industry conventions.