Fraud Risk Management at Digital Insurance Market - Salih Taşyon (2016)

1. October 6, 2016
İstanbul
Fraud Risk Management at Digital Insurance Market
©2016 SİSEB, All right reserved.

2. Digitalization
TodayYesterday
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3. ©2016 SİSEB, Tüm hakları saklıdır.
SİSEB’s Objectives
To manage organised, systematic fraud risks on behalf of the
insurance market…
To be ‘centre of excellence’ for fraud data sharing…
To create new infrastructure to enable the insurance market
to consistently share intelligence…
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4. ©2016 SİSEB, Tüm hakları saklıdır.
Aims
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• Coordination
• Dashboard
• Awareness
• Cooperation
• Decreasing financial losses

5. 2015
• Bureau was established
• Completion of pilot study for
analytic models
• Claim files sharing by daily
• Dashboard
• SİSBİS projects
• Awareness traniee
• Social Media Analytics
• Analysis for the other LoB
• Special investigator data
• Website
• Customer scorecard
• Repairshop scorecard
• Corporate communications
• Analytical decision machine
• Crime line
• Law processes and cooperations
2016
2017
...
...
...
...
Strategy
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6. Insurance Fraud Problem
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100%
0%
10-25%
Fraud detection
All Claims
Sharply Increases
259 Mio TL
Results for the first 9 months of 2016;
Fraud
detection

7. Insura
nce
Compa
nies
Strategy
Policy
Common
Language
Risk
AnalysisControl
Activities
Data Mining
Awareness
Monitoring
Following
Process
Management
Channel
Management
Communication
Effective Fraud Risk Management
Insurance
Company
©2016 SİSEB, All right reserved.

8. Strategy
Detection Investigation Prevention
• Fraud indicators,
• Fraud coordinators,
• Fraud dashboard
• Dedicate team,
• Detection system,
• Analysis of social network
• Fraud unit,
• Coordinating with other
departments
Skill building
IT systems
Performance
Management
Organizations
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9. ©2016 SİSEB, Tüm hakları saklıdır.
Key Performance Indicators
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1. % of detected suspicious claims and/ or policies
2. Fraud savings in terms of % (all claims values)
3. Cost of detection and investigation (% of savings)
4. Time required for above process (per case)
5. Number of false positives
6. % of justified client complaints

10. Return on Investment
Evaluating the effiency
Comparing the effiency of a number of different
investment
©2016 SİSEB, All right reserved.
ROI=
Gain from Investment – Cost of Investment
Cost of Investment
Source: Investopedia

11. KPI’s & ROI
• Who is responsible for KPI’s and ROI?
• How many cases are digestible by the system?
• Is a certain % of gained savings invested back in fraud detection and prevention?
• Are diligent employees rewarded beyond salary (in processes before SIU engagement)?
©2016 SİSEB, All right reserved.

12. • Staff training
• Fraud manual
• Reporting process
• Detection and prevention
• FNOL
• Business models
• Case management
• Criminal complaint and report
• Identify potential fraud
• Control Gap analysis
• Anti fraud handbook & procedures
• Monitoring
• Fraud Committee
• Fraud policy
• Regulation and Legislation changes
• Cooperation with law enforcement
Policy
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Governance Assessment
Investigation Awareness

13. Awareness
• Policy, procedures, workflows,
• E-learning tools, platforms,
• Seminars, webinar, online conference
• Online events and website,
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14. Common Language
Common language, common sense, common vision...
 Exchange
Information
 Exchange
Information
 Harmonize
Activities
 Exchange
Information
 Harmonize
Activities
©2016 SİSEB, All right reserved.
 Share
Resources
 Exchange
Information
 Share
Resources
 Enhance
Capacity
 Harmonize
Activities
Network Coordinate Cooperate Colloborate

15. 15
Channel Management
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16. Risk Analysis
Rationalization
Justification of dishonest
actions
Pressure
Motivation or
incentive to commit
fraud
Opportunity
Ability to carry out
misappropriation of
cash or organizational
assets
FRAUD RISK
Capability
Knowledge of systems
Skills required to
undertake

17. Insurance Fraud Problem
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ActivitiesControl
• Track fraud trends, patterns closely,
• Quantify using scorecards,
• Review the using models.
• Daily what if scenarios,
• Weekly, monthly, quarterly reports,
• Build and track specific metrics,

18. Following
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 Automated detection systems
 Red flag systems for each LoB
 Automated scoring system
 Special business rules
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19. ©2016 SİSEB, Tüm hakları saklıdır.
©2016 SİSEB, All right reserved.
 Proactive Analysis
 Systematic analysis database
 Predictive modelling
 Decission tree analysis
 Data mining
 Social network analysis
 Text mining
 Picture mining
Monitoring

20. Process Management
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Data Staging
Fraud Rules
Repository
Reporting
Repository
Case
Management
Alert Rules
Repository

21. Data Mining
Anomaly Detection / Business Rules
Predictive Analytics
Text Mining
Prefill data update detection
Social Network Analyzer
Link Analysis
Industry Database Lookup
Telematics
Voice Analysis
©2016 SİSEB, All right reserved.
Image & Video Analysis

22. Fraudulent Behaviour
 Contract conditions,
 Customer experience,
 Shaped expectations,
 Ethical climate ,
 Customer communications,
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©2016 SİSEB, All right reserved.

23. Communication
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24. ©2016 SİSEB, Tüm hakları saklıdır.
Customer Experience at Fraud Management
F
1. Satisfaction
2. Loyalty
3. Suspicious and Fraud risk
©2016 SİSEB, All right reserved.

25. ©2016 SİSEB, All right reserved.
SİSEB-Fraud Management
REAL TIME
DETECTION
ALERT & CASE
INVESTIGATION
BUSINESS
INTELLIGENCE LOGIC
HISTORICAL DATA &
EXTERNAL
RESOURCES
HIGH
PERFORMANCE
PROCESSING
DYNAMIC
PROFILING
RULE
MANAGEMENT

26. Thank You
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