ASX:HWH

Case studies.

“The noblest pleasure is the joy of understanding”

Leonardo Da Vinci, 16th Century Polymath
CASE STUDY

H1N1 Virus.

The Problem
at a Glance
If the H1N1 Virus spread to Australia, what factors could mitigate the spread?
PROVIDING

CLASSIFIED CONSULTING + ANALYSIS AUGMENTED-INTELLIGENCE MODELLING DATA EXTRACTION AND REPORTING PRESCRIPTIVE ANALYTICS

pig covid 19
The Approach

Bring the experts together in one place.

  1. Immunologists
  2. Virologists
  3. Veterinary immunologists and virologists
  4. Transport & logistics

DAY 1: Each expert was given
a chance to describe, defend,
demonstrate and link their opinions and views.

DAY 2: Taking everyone’s opinions into consideration, the question of risk mitigation was modelled in our software. to 2026.

The Outcome

The prediction and result of our
modelling concluded the likelihood of a pandemic had increased significantly by threefold.

Our assessment took two days with actionable recommendations for Australia sent to the Government. (The US government assessment took 6 months to produce a similar result.)

In June 2009, the World Health
Organization (WHO) declared the new strain of swine-origin H1N1 as a pandemic.

CASE STUDY

Category & brand migration in the Australian motor vehicle industry.

The Problem
at a Glance

Two in three customers
change buying Segments?

PROVIDING

INTERACTIVE AUGMENTED-INTELLIGENCE ML SOLUTIONS DATA. EXTRACTION AND REPORTING CONSUMER BEHAVIOURAL ANALYTICS. CRM LOOPING (D2SD = DATA TO SALES DELIVERY).

The Approach

Identify stress points. Define loyalty.

  1. When are customers most likely to buy again?
  2. What vehicle are customers likely to buy?
  3. How do we influence customer loyalty?
The Solution
  1. Using data from a large scale syndicated Automotive program, we used machine learning to establish a baseline model.
  2. Prescriptive analytics filled in the gaps for incomplete records.
  3. And, we mapped previous vehicle migration including socio-economic, psycho-graphic, and behavioural data.
The Resulting Model

Customer Centric Communications.

Identified with significant certainty the vehicle type customers most likely to buy.

Potential benefit to surprise and delight the customer. With ‘They see me and my needs.’

The prediction and result of our modelling concluded a high degree of success with an ability to continually feed the Houston we Have AI model for ongoing improvement and refinement.

The Outcome

Predicting individual
future behaviour(s).

The Houston We Have Model increased the likelihood of customer retention by identify timing and, in turn, motivational factors of vehicle choice and purchase propensity.

The Metrics
Age of previous
% Correct
Most likely
73%
Most & second likely
90%
Segment
% Correct
Small Cars
79%
Small SUV
82%
Medium SUV
72%
Large SUV
56%
4×4 Utility
79%
Aggregated Total
73%
CASE STUDY

APPRAISE - Better Provider
profiling for health funds

The Problem
at a Glance
How to help health funds detect unusual behaviour in ancillary providers before it becomes a problem.
PROVIDING
APPRAISE (by Prometheus) is an automated tool for Health Funds. Using multiple probability-based measures, it analyses ancillary provider claims behaviour to help prevent minor issues becoming major problems.
The Profile
There are more than 35 health insurance funds active in Australia providing hospital cover to more than 11 million people and some form of private treatment cover to more than 13 million.
The Challenge
How to improve claims quality and ensure ancillary providers operate with accuracy and in line with fund principles. Funds typically use information sourced from staff, fund members, health service providers and the general public to assess provider claim veracity and accuracy. This can be time consuming, labour intensive and highly manual. Health funds need a better way to reduce the time and costs associated with triaging the extensive and disparate information that’s available.
The Solution

To determine which providers warranted increased monitoring, reminders of procedures or other forms of intervention, Houston We Have Prometheus created an automated and bespoke system for profiling ancillary providers – APPRAISE.

Based on research and experience in the identification of claims errors and other forms of potentially problematic behaviour, seven indicators were identified.

APPRAISE calculates multiple probability-based measures to rank individual providers versus their peers against these indicators.

Presented as a dashboard with graphs, this information alerts health funds to the potential need to audit and or investigate further. This advanced warning systems means health funds can help drive desired claims behaviours rather than apply punitive measures once problems occur.

The Result

APPRAISE is helping funds achieve significant reductions in claims waste, improvements in claims quality and the reduction of fraud.