Presented by Shaun Bennet at the 4th Annual East Africa Finance Summit Single master data record of client Unique client reference Easy management of client references Ability to match similar record on a continuous basis

1. 4th East Africa Finance Summit 2019
A Data Science solution
Single view of customer

2. Agenda
QED Actuaries & Consultants | 2
A fragmented customer reality
The data merging challenge
Data science and a solution
The final outcome

3. Agenda
QED Actuaries & Consultants | 3
A fragmented customer reality
The data merging challenge
Data science and a solution
The final outcome

4. | 4QED
Client data freely available
Telematics Activity Sentiment
Financial Underwriting Browsing

5. Telematics
| 5QED
Client data freely available
• Reckless driving
• Location
• Impact alert
• Time of use
Activity Sentiment
Financial Underwriting Browsing

6. ActivityTelematics
| 6QED
Client data freely available
• Reckless driving
• Location
• Impact alert
• Time of use
• Heart rate
• Stress monitor
Sentiment
Financial Underwriting Browsing

7. SentimentActivityTelematics
| 7QED
Client data freely available
• Reckless driving
• Location
• Impact alert
• Time of use
• Heart rate
• Stress monitor
• Brand loyalty
• Price elasticity
• Influence
• Marketing
Financial Underwriting Browsing

8. Financial
SentimentActivityTelematics
| 8QED
Client data freely available
• Reckless driving
• Location
• Impact alert
• Time of use
• Heart rate
• Stress monitor
• Brand loyalty
• Price elasticity
• Influence
• Marketing
• Affordability
• Price sensitivity
• Fraud
• Lapse
Underwriting Browsing

9. UnderwritingFinancial
SentimentActivityTelematics
| 9QED
Client data freely available
• Reckless driving
• Location
• Impact alert
• Time of use
• Heart rate
• Stress monitor
• Brand loyalty
• Price elasticity
• Influence
• Marketing
• Affordability
• Price sensitivity
• Fraud
• Lapse
• Improved ability
to underwrite
• Impact of
technology
Browsing

10. BrowsingUnderwritingFinancial
SentimentActivityTelematics
| 10QED
Client data freely available
• Reckless driving
• Location
• Impact alert
• Time of use
• Heart rate
• Stress monitor
• Brand loyalty
• Price elasticity
• Influence
• Marketing
• Affordability
• Price sensitivity
• Fraud
• Lapse
• Improved ability
to underwrite
• Impact of
technology
• Number of visits
to company site
• What
information is
being accessed

11. | 11QED
Pockets of information within an organisation
Multiple internal source
systems
Data not centrally located within an organisation
Legacy systems from
acquisitions
Un-migrated data
Data from external
providers
Data warehouse that is in progress
Lack of consistency
Different data
structures
Missing or lost customer
information
Unusable data

12. Agenda
QED Actuaries & Consultants | 12
A fragmented customer reality
The data merging challenge
Data science and a solution
The final outcome

13. | 13QED
The challenge of merging data
Large number of
applications
Large data
volumes
Differences in
underlying data
structures and
formats
IT infrastructure
including legacy
systems
Constantly
changing business
environment
Lack of unique
customer ID

14. | 14QED
What is the desired target state?
Client Data
External Data
Analytics
Holistic view of client Data driven decisions
Ability to easily
incorporate new data
Deep customer
understanding

15. | 15QED
• Exponentially more complex the more data you have
• If we have 1,000,000 customers
• Information contained on each customer on 10 systems
• 10
60
operations to compare every record
• 10
80
atoms in the universe
• Increases in complexity if data tables are inconsistent
The mathematical complexity
Does Data Science have a solution?

16. Agenda
QED Actuaries & Consultants | 16
A fragmented customer reality
The data merging challenge
Data science and a solution
The final outcome

17. • CRM
• ERP
• Third-party
• Date of capture
• Last date of update
• Products held
• Number of dependants
• Name
• Address
• Contact Details
• Gender
• Date of Birth
• Identity Number
| 17QED
What data can we use?
Does Data Science have a solution?
Personal
Information
Categorical
Information
Time
Information
Data Source

18. | 18QED
Does Data Science have a solution?
ERP CRM App
AI Engine
Customer Master Data Record
Uniquereference

19. | 19QED
Does Data Science have a solution?
AI Engine
Fred Smith
+1-225-447-0039
Fredrick Smith
225-447-0038
15 Coventry Court
Louisiana
Fredrick Smith
151 Main Rd
Kansas
ERP CRM App

20. | 20QED
Does Data Science have a solution?
Fredrick Smith
225-447-0038
15 Coventry Court
Louisiana
[0.593, 0.333, 0.4193,
0.1254, 0.734, 0.234]
[0.224, 0.224, 0.943,
0.984, 0.234, 0.493]
[0.1983, 0.298, 0.1845,
0.984, 0.6489, 0.1983]
Fredrick Smith
225-447-0038
15 Coventry Court
High dimensional
vector representation
of client data

21. | 21QED
Graph algorithms and human validation
Does Data Science have a solution?
Similarity Graph Human validationGraph
• Use distance metrics to
cluster similar vectors
• Cross-validate on
additional fields
• Calculate a reliability
score
• Use graph algorithms
to structure data
• Automatically validate
records above
threshold
• Spot checks to
validate algorithm
• Ambiguous matches to
be manually validated
• Easy interface to
manage data
Validations used to retrain underlying algorithm to allow it to improve over time

22. | 22QED
Does Data Science have a solution?
AI Engine
Fred Smith
+1-225-447-0039
Kansas
Fredrick Smith
225-447-0038
15 Coventry Court
Louisiana
Fredrick Smith
151 Main Rd
Kansas
ERP CRM App
Match

23. Agenda
QED Actuaries & Consultants | 23
A fragmented customer reality
The data merging challenge
Data science and a solution
The final outcome

24. | 24QED
What do we get out of this process?
The Final outcome
Single master data record of client
Unique client reference
Easy management of client references
Ability to match similar record on a
continuous basis
Integrated data environment for ongoing
business information and analytics
Adaptable environment to allow for business
growth
The data merging challenge Access to data
Integrated environment Fluid data environment

25. | 25QED
Case studies: Insurance
The Final outcome
7 systems
Both new and legacy
>97% processed by AI
Years of work saved
> 400,000 customers
Can handle large scale

26. QED Actuaries & Consultants Pty Ltd
1st Floor, Hunts End Office Park,
38 Wierda Road West, Sandton,
South Africa
QED Actuaries & Consultants Kenya Ltd
Nairobi Garage, Cove Court,
Watermark Business Park, Karen, Nairobi,
Kenya
QED Actuaries & Consultants Mauritius Ltd
The POD, Vivea Business Park,
Moka,
Mauritius
QED Actuaries Nigeria Ltd
Workstation Offices, No. 7 Ibiyinka Olorunbe Close,
Victoria Island, Lagos,
Nigeria
www.qedact.com