2. Agenda
The local insurance industry
The international insurance industry
A powerful solution exists
Where to from here?
3. An Intro to TU Africa: Driving Information for Good
Leading provider of risk and
information solutions:
• 100+ year history in SA
• Listed on the NYSE in 2015
We leverage state-of-the-art global
data and analytics platforms/IP to
accelerate the ability to provide insights
and value-based outcomes to clients.
We want to be a true strategic
partner to our clients:
• solving complex problems and
• co-creating value
We are committed to driving
‘Information for Good’ for our clients,
our consumers, and our communities.
Our Global Presence
PropertyConsumer Commercial AutoInsuranceEIR
30 8 #1countries countries in Africa position in South Africa,
Hong Kong, India
Unique Data-sets
Strong Capabilities
• SHAPE/Hadoop - Big data platforms
• PRAMA - Analytical & insights engine
• DecisionEdge® - Front-end Decisioning platform
• Analytics - Unique algorithms & scores
Insights ActionsData
Ingest Analyze Visualise Collaborate Fulfillment Score Decision
4. An Intro to TU Africa: Data & People
AfricaDataAssets
Marketing
Contact (Credit & Non Cred)
Data Strategists
Data Scientists
Statisticians
Machine Learning experts
Solution Consultants
Marketing Specialists
Risk Specialists
Fraud specialist
Geospatial
Geocoding
Property Variable
People
700+ Associates
Insurance
Insurance Claims
Insurance Underwriting
Property data
Deeds & Bonds
NAD
EIR Data baseCommercial
Registered Companies
Trade Data
Trade References
Company Operations
Enquiries
Default Data
Civil Court Judgments
Business Rescue
Bank Codes & Banking History
Notarial Bonds
Trust Data
Auto
Vehicle master
Auto valuation
Vehicle Finance
Consumer
Payment Profile
Consumer Header
Enquiries
ID Verification
Contact Data
Default Data
Civil Court Judgments
Debt Counseling
QVS
Biometrics - Voice
Kenya
Rwanda
Zambia
Botswana
Namibia
Swaziland
South Africa
*Only SA & Kenya
8. The local industry leaped forward in recent months, but will this be good
enough to catch up with international best practise?
Overview and the local industry in perspective
Investment into FinTech and InsurTech increased by 117% between 2014 and 2015
At the moment, less than 5% of insurance is purchased online in South Africa
Less than 15% of P&C insurance can be purchased online a ~R500 billion market
28% of the population are millennials, presenting a significant opportunity
Low ranking in consumer perception
9. Overview and local industry in perspective (cont.)
IOT technology adoption rate slow
Estimated that 90% of data used in the application process is captured manually and
the validation of this data is limited with outdated and expense intensive quality
assurance processes are still being applied to “mitigate” the risks associated with poor
data capturing
High level of sophistication around pricing and risk selection
Lagging international benchmark for online use
Low adoption rate of UBI (telematics) ~ < 10%
13. Here’s a couple of things international markets are doing that we should
definitely work towards:
Internationally, the picture looks very different
80% of carriers provide online self-service
More than 70% of all online quotes generated in the US in 2015 were created online
More than 20% of insurance was purchased online – increasing every year
Up to 50% improvement in operational expenses has been experienced by businesses
that have implemented online strategies
14. Internationally, the picture looks very different
(cont.)
Significant improvement in claims processing time and associated costs resulting
in healthier combined ratios and happier customers
Quoting and underwriting processing time reduced by as
much as 60%
Insurance penetration remains the highest in the world and is set to increase as
digital channels allow easier and broader access to insurance
Operational efficiency and cost saving generated by process automation has
created capacity for insurers to innovate in improving the customer experience
The use of digital channels to deliver gamified training content ensures
continuous skill development translating into better advice and coverage for
customers
16. EIR
DB
1.48 B
Hosted
TU
Acquisition Plan
Employe
e
Count
Company
Financials
14 K
Qualification
Data
Judgments
1.2 M
Commercial
Header
5 M
Active
Commercial
1.5 M
Addres
s
4.3 M
Auto
Valuations
7.2 M
Insurance
Claims
9.7 M
Consumer
Auto
Health
Telco
Commercial
Insurance
Verified
ID
33 M
We can respond promptly and decisively through
access to some of the best data in the world
Property
Valuation Enquiries
2.7 M
Registration
Information
4.5 M
Contact
1.4 M
Insurance
Policies
4 M
Deeds
15 M
NAD
9 M
Vehicle
Master
19 M
Auto
Finance
3.2 M
Traffic
Fines
Medical
Aid
Policies Contact
21 M
Consumer
Header
51 M
Paymen
t Profile
21 M Defaults
3.4 M
Payment
data
Home
Affairs
Notices
35 K
17. Prefill demo - underwriting a personal vehicle
Insurer
Data pre-populated for
insurance decisioning*
<Name> Mary
<Surname> Smith
<Registration Number> WXY514 GP
<Address> 52 Corlett Drive Illovo
Sandton 2196
<Vehicle Make> BMW
<Vehicle Model> 320i
<MM Code> 12345678
<Loss Ratio Score> 680
<Lapse Model Score> 680
<Income Estimator> R7500
<Claims last 3 years> 3
<eNatis driver license> Yes
TransUnion
Premium decision
calculation
Business Rules and
Rating Engine
Quote
Match to
TransUnion
data
* Data returns indicated above
for illustrative purposes only
ID, Name, Surname,
Registration Number
Agent inputs
minimum data
19. • How we have helped…
Pace of change is
relentless…
New entrants entering the
market have digitisation as
the foundation of their
strategy .
Business processes
are architected around
automation, integration
and agility
Significant investment being
made by established
insurers to digitise
acquisition processes,
enhance self service and
reinvent claims processing
Traditional insurance is set to
change forever, finally in
favour of the consumer
21. Next steps – combining data and technology to
solve consumer issues
Automated on boarding processes to
increase relevance
Fraud mitigation only possible through
investment in technology e.g. machine
learning models have a 5:1 false
positive ratio in predicting content fraud
Improved customer experience through
true omni-channel capabilities being
widely adopted
The ability to combine structured and
unstructured data e.g. web scraping
essential for omni-channel and fraud
objective improvements
22. Next steps – turn data into valuable insights
(cont.)
Improvement in profitability through
better pricing and risk selection,
reduced operating expenses, reduction
in fraud
‘Internet of Things’ data and devices set
to increase exponentially allowing first
notification of loss and response to a
claim to happen in real time
Increased relevance of telematics in driver
education and rewarding safe driving,
reducing distracted driving and improving
emergency response time in emergency
situations aimed at improving road safety
in South Africa
Access to real-time business
intelligence through new data processing
and analytical tools, which creates a
significant competitive advantage by
allowing insurers to quickly identify and
react to possible threats and opportunities
23. Next steps – turn data into valuable insights
(cont.)
Growing popularity of P2P insurance
e.g. Lemonade, set to threaten
traditional insurance principles and
processes
Social media platforms set to re-shape
traditional distribution channels through
AI technology like Chatbots
Transformation from a grudge purchase to
a practical and engaging risk management
solution partner in a world where risk
complexity and exposure is evolving faster
than the solutions to mitigate them
Expanding use of technology to pro-
actively manage risk, reduce the impact of
a loss after it has occurred and convert the
learnings into engaging solutions aimed at
improving consumer knowledge
