Insurance Rajendram

8/2/2019 Insurance Rajendram

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Agenda

• Overview of Insurance & Takaful in Malaysia

• ISM Insurance Services Malaysia

• What is Insurance Fraud

• IAIS Guidance Paper on Fraud

• Developing and operating industry claims databases

• Use of fraud analytics for the detection and preventi

on of insurance fraud• Actual case study

• Challenges / Moving Forward

2ISM PUBLIC - All Right Reserved



Malaysia




Malaysia

• Independence in 1957

• Constitutional Monarchy

• Population 28 million

• Multiracial composition

• Official Religion – Islam• Language – Malay & English

• Economy – NaturalResources, Manufacturing andServices

• 1 Euro~MYR4.00• 1USD~MYR3.25

• GDP per Capita ~ Euro6,250

Malays &

Indigenous

Borneo, 60%

Chinese,

30%

Indian, 8%

Others, 2%

4



Malaysia GDP

Agriculture,8%

Mining, 7%

Manufacturing,31%

Services, 58%Construction,

3% 5ISM PUBLIC - All Right Reserved



Insurance Industry – No. Co’s

1716 16 16 16 16

17 17

14

4644

3736

35 3534 34

31

2 23

4 45

7 8 8

2 23

4 45

7 8 8

0

5

10

15

20

25

30

35

40

45

50

2000 2001 2002 2003 2004 2005 2006 2007 2008

Life Non-Life Takaful Family Takaful General




Market Size

8,889

11,685

10,832

12,308

13,326

14,539

15,447

5,9296,404

7,449

8,1868,558

9,386 9,63910,046

10,896

297 369 452 511 604 726 1,267

203 267 333 252 329357 714

-

2,000

4,000

6,000

8,000

10,000

12,000

14,000

16,000

18,000

2000 2001 2002 2003 2004 2005 2006 2007 2008

R M ( m i l l i o n s )

Life Non-Life Takaful Family Takaful General7ISM PUBLIC - All Right Reserved



Per Capita Insurance Spend

378

487

440

489

582600

644

695676

252 267303

324 329352 362 369 374

51 27 30 31 37 46

73 86

8 9 10 13 13 18 21 24

-

100

200

300

400

500

600

700

800

2000 2001 2002 2003 2004 2005 2006 2007 2008

Life Non-Life Takaful Family Takaful General




Non-Life Market Share by Product

Motor45%

Fire

18%

Marine,

Aviation &Transit

12%

Others

25%




Takaful

• Takaful is an insurance contract which is grounded inIslamic Muamalat (practice), observing the rules andregulations of Shariah (Islamic Law).

• The current Takaful practice uses a combination of two

types of ‘Aqad (contract). – These are the Tabarru' (donation) and

– Mudharabah (investment) contracts which are free from theelements of Riba (interest), Maisir (gambling) and Gharar(uncertainty).

• In the Mudharabah contract, however, participantscontribute to a fund that is managed by the Takafulcompany and share in the profits from such investment.




ISM INSURANCE SERVICES MALAYSIA



About ISM• Founded in 2005 by 34 insurance and takaful companies• Limited by Guarantee (no shareholders)

• 60 corporate customers

• Objectives

1. Provide Infrastructure of Databases and Reporting to

Support Liberalized pricing Environment2. Build Competencies in Technical Areas of Pricing and

Reserving

3. Increase Efficiencies in Operations by:-

• Providing Online Access to Shared Information

• Increasing Utilization of IT in Insurance Operations

• Provide World Class Fraud Detection Systems and

Capabilities

www.ism.net.my


http://www.ism.net.my/

http://www.ism.net.my/



Transforming Information into Knowledge & Statistics into Strategy

Identifying Suspicious Claim, Paying Legitimate Claims Faster

Better Operational Efficiency, More Competitive Costs

Your trusted Source for Automotive Intelligence 13ISM PUBLIC - All Right Reserved



ISM Insurance Services Malaysia




INSURANCE FRAUD



What is Insurance Fraud?

• Hard Fraud – Premeditated / Carefully Planned

– Incident giving rise to claim often staged /

manufactured – Serious / Organised Crime

• Soft Fraud – Opportunistic / Not Planned / Take Advantage

– Incident giving rise to claim is often genuine

– Also a crime, but viewed more sympathetically


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http://images.google.co.uk/imgres?imgurl=http://www.nyrealestatelawblog.com/Mafia.jpg&imgrefurl=http://www.nyrealestatelawblog.com/accidents_generally/index.html&h=1200&w=900&sz=622&hl=en&start=26&um=1&tbnid=QIvUnLxC3W70OM:&tbnh=150&tbnw=113&prev=/images?q=Mafia&start=18&ndsp=18&svnum=10&um=1&hl=en&sa=N



ABI Insurance Fraud Survey

• October 2007 Study

– More fraud detected and prevented

• 11% of claims involved some element of

opportunistic fraud

– 50% on property policies, mostly home contents

– 85% were exaggerations of claims, 15% invented

– 50% of undetected fraud




ABI Insurance Fraud Survey

• Characteristics of Fraudsters – Age over 45 less likely to commit fraud

– Average premiums of $500 or more, 50% less likely to

commit fraud – Homeowners less likely to commit fraud

– Males are 1.6 time more likely

– North of England 1.7 times more likely

– Unsecured debt greater than $1,000 2.0 time more likely

– Household income of $10,000 or less 2.6 times more likely




Malaysia Insurance Fraud Survey • “…31% believed that insurance companies can afford it”

• “…61% would commit fraud if they know that they can get away with it”

• “…44% believed that exaggeration of an otherwise legitimate claim isthe most common categories of insurance fraud, followed by non-disclosure or misrepresentation of material facts at 27%”

• “…44% viewed that motor class of business is where most fraud is

perpetuated, followed by Health/Medical at 22%”




Fraud Triangle

Opportunity

Motive / Incentive

Rationalisation




Where is Insurance Fraud Rampant?• Where 3rd party service provider is involved

– Healthcare Insurance

• Healthcare establishments, doctors, drugs

– Motor Insurance• Workshops, lawyers

• Where Utmost Good Faith is critical

– Cargo Insurance

– Travel Insurance

• Where Indemnity Principal violated

– PA & Life Insurance

– Theft Claims 21ISM PUBLIC - All Right Reserved



IAIS Guidance Paper on Fraud

• International Association of Insurance

Supervisors

– The objective of the paper is to provide guidance

so that the potential risk of fraud can be identifiedand reduced

– covers insurers (including reinsurers), insurance

intermediaries and insurance supervisors




IAIS Guidance Paper on Fraud

• Insurance Core Principal 27

– Insurers and intermediaries take the necessarymeasures to prevent, detect and remedy

insurance fraud – Legislation addresses insurer fraud.

– The supervisory authority promotes the

exchange of information between insurers with

respect to fraud and those committing fraudincluding, as appropriate, through the use of databases.




Fraud Management Services

Fraud Detection Systems






ISM Fraud Management Services

ISM Claims Database

ISM Link Analysis and Fraud Scoring

MotorMedical

& Health

Personal

AccidentBI Claims

Others (Travel,Property etc.)

ISM Claims Info System (ICIS)

DataUpload

DataVerification

ClaimMatching

Local DataCubes

ClaimEnquiry

ICVS







What is our Objective?

• Our Objectives in Combating Fraud is NOT

– Prosecution of Fraudsters

– Identification of Fraudulent Claims that have been

Paid

• Our Objective in Combating Fraud

– Identifying & Preventing Fraudulent Claims from beingPaid




Fraud Detection

Detection

INDUSTRY CLAIMS

Investigation

SUSPECTED FRAUD

Fraud Detection System Groundwork / Investigation

Goal is to make Suspected ~ Fraud




Fraud Detection Technologies

• Red Flags

• Exception Reporting

• Predictive Modelling

• Data Linking Analysis




Insurance Red Flags

• E.g. Rules• X claims in last X years

• X similar claims paid in xx months

• Claim intimated within x days of coverage

• Claim amount over RMx,000

• Exception report generated via Central Claim System

• Aggregate scores and compare to threshold

values – Low / Medium / High

– NFA / Monitor / Investigate




Red Flags

• Advantages – Simple to administer and maintain

– Need continuous refinement over time – with

industry database this process can be accelerated• Disadvantages

– Success depends on number and combination of

flags (too many, too little)

– Can Result in High False Positives – marketing will

complain!




Exception Reporting

• Detecting Anomalies in Patterns

• Statistical method to identify outliers

• Again refinement achieved much quicker forcompanies by testing against industry database

of claims




Predictive Modelling• Generalize fraud patterns for automatic

detection

- Identify typical patterns

- Score new claims automatically for fraud probability

• Modeling techniques:

- Predictive Modeling:

• Decision Trees• Neural Networks

• Regression

• GLMs




Data Linking Analysis

• Detect unexplained Relationships- Profiling of suspicious cases

- Direct and indirect links between seemingly unrelated

transactions

• Modeling Techniques

- Associations / Sequence analysis

- Link analysis / Path analysis

- Fuzzy matching

• Powerful investigative tool when have industry-

wide claims data35ISM PUBLIC - All Right Reserved



Which Method is Best

• Hybrid approach is required to fend off

different types of fraudsters

– Red Flags / Predictive Models – Soft Fraud

– Data Linking / Exception Reporting – Hard Fraud

ISM PUBLIC - All Right Reserved 36



Sample Insurance Fraud Cases

• Case 1




Sample Insurance Fraud Cases

• Case 4


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Looking Ahead

• Increasing Consumerism – Shorter Decision Time for Claims Managers

– Fraud System must be predictive yet have low false

positives• Solvency II

– Fraud Management is a key component of enterpriserisk management

– Insurers need to share information to deter fraud• Information Security Management

– Managing data confidentiality / privacy vs.accessibility




Thank You

Carl Rajendram CFE, FCII, PMP

Chartered Insurance Practitioner, Certified Fraud Examiner,

Project Management Professional

ISM Insurance Services Malaysia [email protected]@gmail.com

40ISM PUBLIC All Ri h R d

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Insurance Rajendram

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