Ping An's Healthcare Ecosystem

62 Pages·2017·4.37 MB·English

From Ping An to Platform：
Technology Innovation for Growth
Jessica Tan

Ping An Group
Group Deputy CEO
Group COO & CIO

2017.11.20
Important Notes

Cautionary Statements Regarding Forward-Looking Statement
To the extent any statements made in this presentation containing information that is not historical
are essentially forward-looking. These forward-looking statements include but are not limited to
projections, targets, estimates and business plans that the Company expects or anticipates will or
may occur in the future. These forward-looking statements are subject to known and unknown risks
and uncertainties that may be general or specific. Certain statements, such as those including the
words or phrases "potential", "estimates", "expects", "anticipates", "objective", "intends", "plans",
"believes", "will", "may", "should", and similar expressions or variations on such expressions may be
considered forward-looking statements.

Readers should be cautioned that a variety of factors, many of which may be beyond the Company's
control, affect the performance, operations, and results of the Company, and could cause actual
results to differ materially from the expectations expressed in any of the Company's forward-looking
statements. These factors include but are not limited to exchange rate fluctuations, market shares,
competition, environmental risks, changes in legal, financial and regulatory frameworks,
international economic and financial market conditions, and other risks and factors beyond our
control. These and other factors should be considered carefully, and readers should not place undue
reliance on the Company's forward-looking statements. In addition, the Company undertakes no
obligation to publicly update or revise any forward-looking statement that is contained in this
presentation as a result of new information, future events, or otherwise. None of the Company, or
any of its employees or affiliates is responsible for, or is making, any representation concerning the
future performance of the Company.
Agenda
1. Ping An Group: 5 Core Technologies

2. From Ping An to platform: Output
services to 4 ecosystems
a. Financial Services Ecosystem
b. Health Care Services Ecosystem
c. Auto Services Ecosystem
d. Real Estate Finance Ecosystem
In the past decade, Ping An invested over RMB50bn in innovative technologies
such as fintech, healthtech, and AI to strengthen competitiveness and serve
society.
Internally: enhance Externally: supply
competitiveness services and cash in
1 PA Biometrics
 Boost efficiency
 Financial Services
 Cut costs PA Big data system
2

 Improve  Healthcare
3 PA AI+Brain
experience ecosystem

 Strengthen risk  Auto ecosystem
4 PA Blockchain
management
 Real estate
PA Cloud ecosystem
5
22,000+ IT developers, 500+ big data scientists
2,000+ global patents, among the world’s leading financial institutions
4
1 PA Biometrics：World-leading technologies

PA Facial PA voiceprint PA Micro-
PA Big Data
recognition recognition expression
+ + +
• 99.8% accuracy, • 99+% accuracy • 54 complex • 880mn people
the world’s No.1 • 50mn+ voiceprint micro-expressions • 26K data fields
• 800mn+ usages records • 1-second recognition • 3,300+ data fields per
• 200+ scenarios • 10+ scenarios • 300k+ loan approvals person overage
• 100+ clients • 730mn credit inquiries
5
1 PA Biometrics：Diverse and extensive scenarios

Financial Health care Life/service Security
scenarios scenarios scenarios scenarios
• Small loans: 30mn+ • Checkup identity • Exams: The post-graduate • Airport security
face recognition-based verification: entrance examination in screening:
identity authentication, 50,000+ times Shenzhen in 2018, to cover 140mn+ identity
fake identities down • Social health: 1mn+ exam takers in check at
from 29% to 0% covering 14 cities Guangdong next year Shenzhen Airport
• Community in
• Large loans: • Real estate Guangzhou:
300,000+ micro- administration bureaus: 38mn call-ups
expression approvals, 9 locations, 1.30mn+
efficiency up 10% while times of services
errors down 5%
6
2 Big data: 1+N ecosystem partners
Health
care
Finance Auto
Real
estate
Finance Health care Auto Real estate
430mn+ internet Credit data of 180mn users 32mn+ daily active 21mn+ users
users 880mn+ people users
310mn+ app users 143mn+ financial 38mn P&C users
customers (online) 1bn+ claims photos
1.4mn+ life Social Health 300+ developers
insurance sales Insurance in 257 150+ cities data
agents 400+ banks cities 26,000 4S stores 2.50mn+ second-
20K+ outlets 2,000+ non-bank 42K+ clinics 100,000 garages hand houses
60K+ customer institutions 2,000+ hospitals 34,000 used-car
service agents dealers
PA 29 years of business, 880mn+ people, 26,000+ data fields
Big Data 70mn+ businesses, 300+ partners
7
3 PA AI+Brain: AI+understands you better
Voiceprint (V)
Risk (R) V Account (A)

R A
Property (P) P B Business (B)

AI+
P&C claim(M) M C Customer (C)
Understands you

better
Image(I) I … D Driving (D)

H F
G
Health (H) Face (F)

Government (G)
8
3 PA AI+ Brain：Across all business process
AI+Perception AI+Forecast AI+risk control AI+services
Finance：AI+recording P&C：AI+claim(KYM) Finance: Loan (KYR) Finance: AI+customer
(KYV/KYF) • Image-based • Loan application from service (KYS)
• 23 clients, 160mn recognition and anti- offline to 100%online • IVR success rate 85%
usages, Agent leakage • Overdue ratio down by • Online robot reply
efficiency up 30X, • Loss estimation 0.5%, credit loss ratio accuracy 95%
customer waiting time accuracy92% down by 3.7% • Customer waiting time
down 75% down by 20%内
Health：AI+ medical Health: Diesase Finance: SMB loan P&C: AI+ investigation
imaging(KYH) forecast (KYH) (KYB) (KYM)
• Flu accuracy 90+% • 70 mn SMB • Arrival at accident
• Reading time down
• COPY accuracy 92% • KS up by 30% sites within 10
from 20 mins to 10s,
• Approval time down by minutes in 90% of
diagnosis omissions
90% cases
down from 40% to
2% 9
3 PA AI+ Brain Risk control（KYR）：enabled by cutting-edge risk
management and AI technologies
Bad experience，customer
needs to go to store 2 times,
Needs
Approval 3-4 days

New sales ↑2.5x
Overdue rate↓64%
Credit loss↓60%
Offline stores↓68%
Impact2
Fee rate↓39%
300K+loan applications
through micro-expressions

10
10
1. 2020 forecast 2. Impact comparison based on 2015 vs 2017 Jan to Oct