Predictive Analytics Models (PAM)

Building Predictive Analytics Models (PAM) for Banking, Insurance & Takaful. 121Advisor solutions focus on predictive marketing & sales, customer service, new business underwriting, personalization and claims management.

Using Predictive Analytics for Insurance, Takaful, Banks, Investment

  • Select Model to Build
  • Identify possible Predictive Algorithms
  • Collect Data
  • Define Attribute & Features
  • Run Test Models
  • Clean Data
  • Choose best Algorithm Model
  • Train Selected Model
  • Run Predictive Models to generate event triggers
  • Use events to trigger RPA

Collect & Clean Data from Front-ends, Back-ends & Social Data

Build AI Models with Machine Learning & Validate Predictions

Personalised Lead Scoring

Predict New Products to Buy

Personalized Risk Scoring for Investment

Predict Fraudulent Claims

Predictive Underwriting

Predict Lapsation for Insurance & Takaful

Predict churn for Banks

Implement AI Solutions & Interact with People via RPA processes

KYC, Identify & Define Personas, Understand Consumer Needs, Nurture Leads, Identify Sales triggers Sales compliance

Use Alternative data, Assess Risk Score (health, stress, occupation), Assess Recommendation, Automate Underwriting Risk

Regular Risk & Claim Assessment, Product Sustainability, Dynamic Pricing Process

Build & Assess Predictive Models to Manage Risk. Use Personal Engagement to reduce Lapse/Churn, Reduce delays in claim processing

Automate Services, Claims & Capital Management with Robotic Process Automation with event triggers

Run Trained Model periodically to Predict Lapse

  • Create production version of Trained Model
  • Extract data from back-end load, clean, compute features & export to CSV file
  • Use Machine Learning to continually refine lapsation model
  • Run trained model and generate lapse probabilities
  • Define the Lapse Probability Factor e.g. > 0.5
  • Export probability results, upload & generate event triggers based on the Lapse Probability Factor
  • This triggers the RPA process to either notify agent or customer team (if orphan policy)

Predictive Analytics Benefits & Considerations

Predictive Analytics Benefits
  • Better Predict and Mitigate Risk
  • Applies to marketing & sales, customer service, new business underwriting, personalization and claims management
  • Estimated that AI can drive cost savings of $390 billion across insurers' front, middle, and back offices by 2030
  • Artificial intelligence has the potential to move from a detect-and-repair mindset to a predict-and-prevent philosophy
Predictive Analytics Considerations
  • Use multiple algorithms to assess the best predictive model
  • To ensure that AI in the front office is successful, insurers need to have a clear strategy for implementing AI tech and use it for solution for specific problems
  • Use a hybrid model between digital & human to ensure they cater to all consumers
  • AI should be viewed as a means to Augment but NOT replace human capabilities

How can 121Advisor Help?

  • Combined strength of 121Advisor enables us to quickly extract, map & clean data, build & test predictive models & move to production to run periodically (monthly) that triggers Robotic Process Automation processes
  • Led by Data Scientist based in Malaysia
  • Significant experience in building Predictive Models and other Data Products
  • 121Advisor has expertise in design of data, extract, map & optimize data from back-ends and build RPA processes with event triggers


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