FINEOS Actionable Data provides operational data, predictive models and the ability to leverage cutting-edge machine learning techniques with the best customer data you have, from the FINEOS Platform. 

Machine Learning for Life, Accident & Health Insurance

Successful insurance businesses require the ability to make optimal decisions on the best available data, design innovative products that differentiate you in the market and provide the best service for the lowest cost. Machine learning helps you across all these goals using state-of-the-art models and applying new machine learning applications to the overall insurance process with cutting edge insurance technology. 

The FINEOS Machine Learning Engine™ underlies all FINEOS Predictive Models™, FINEOS Smart Connectors™ and process accelerators used across the FINEOS Platform. It is trained in insurance insights and employee benefits baselines and provides a solid foundation for purpose-built insurance and employee benefits machine learning solutions. It can be used to meet many needs beyond the purpose-built FINEOS Predictive Models™ including:  

  • Smart data transformation for existing insurance data sets 
  • Propensity to purchase modeling 
  • Sentiment analysis 
  • Natural language processing for insurance notes and contracts 

Predictive Models

Machine learning helps an insurer make better decisions. Purpose-built machine learning predictive insurance models offer strong value out of the box avoiding a long specification and development process and provide a much shorter period of model maturation.  

FINEOS Insight offers several predictive models relevant to your business.

  • FINEOS Claims Fraud: Identify short-term disability and long-term disability claims with the likelihood to be “inconsistent” based on claim characteristics.  
  • FINEOS Claims Settlement: Identify long-term disability claims with a likelihood to settle based on claim attributes
  • FINEOS Census Standardization: Normalize census files using a standardized data model
  • FINEOS Annuity Fraud Scoring: Assess annuity fraud likelihood based on application, distribution source, and employee connections

Operational Intelligence

FINEOS embedded analytics capabilities are immediately available to the operational teams to drive smart operational decisions.  

Real-time embedded dashboards provide insurer staff, policy holders, and employers immediate insight into a given case, plan or policy providing the ability for efficient decision making. People First customer experience ensures the relevant data/scores for a given scenario are highlighted to fight cognitive overload. 

FINEOS out-of-the-box claim segmentation models and processes coordinate the journeys of claims of different severities. This built-in segmentation of workload for no-, low-, and high-touch routing also provides real-time monitoring for re-segmentation/escalation to avoid creeping catastrophe claims.


FINEOS Actionable Data – Frequently Asked Questions

What is FINEOS Actionable Data?

Actionable Data is part of the FINEOS Platform that allows insurers to use customer-centric data models to gain real-time analytics data from multiple channels across their entire insurance digital ecosystem to inform operation decision making.

Does Actionable Data provide real-time analytics?

Yes. FINEOS uses embedded, real-time analytics to leverage platform data which helps insurers determine smart operational decisions.

How does real-time analytics improve decision making?

Immediate insight into a given case, plan or policy provides accurate and efficient decision making for insurer staff, policy holders, and employers.

How will operational and product trending with FINEOS Insight reduce my costs?

FINEOS Insight with real-time embedded analytics provides operational and product trending data to ensure your customers the best service experience. Identify key business trends and opportunities while also saving time and money.

What kind of AI can I expect within FINEOS real-time analytics?

The FINEOS AI program focuses on 3 different areas. The first is leveraging cloud AI platforms. The second is collecting data and presenting predictions to improve internal insurance models and providing decision assistance. The third is developing new Life, Accident & Health machine learning models. Learn more on