richard hill_fico_marketforce insurance fraud_final_20150324

© 2015 Fair Isaac Corporation. Confidential. This presentation is provided for the recipient only and cannot be reproduced or shared without Fair Isaac Corporation’s express consent.

Fraud is the cost of doing business – why bother chasing the bad guys?

Richard Hill Client Services - Partner FICO 24th March 2015

Agenda

© 2015 Fair Isaac Corporation. Confidential. 2

► Too much fraud, crime & deception

► Should we care?

► What can we do about it?


Too much fraud, crime & deception

4 © 2015 Fair Isaac Corporation. Confidential.

Not being 100% honest isn't always a crime…

► “I think the blue dress is better than the red one”

► “That was such a delicious meal…”

► “I love listening to the junior school concert”

► “Ha ha that joke was hilarious Boss…”

► “Have you lost weight? You look great!”

► “It was already like that when I got here…”

Oxford Dictionary definition of fraud:

Wrongful or criminal deception intended to result in financial or personal gain


Famous criminals – known & revered through the ages

► Convicted murderers are more easily remembered & recognised

►Al Capone

►Fred & Rosemary West

►Dr Harold Shipman

►Ian Brady & Myra Hindley

► However financial fraudsters are less well known/recognised

►For example, who is this?


Bernie Madoff – King of Financial Crime

► Former Non-Exec Chairman of NASDAQ – a respectable chap…

► Founded Bernard L Madoff Investment Securities in 1960

► Became one of the top market maker businesses on Wall Street

► 10/12/2008 his son told authorities his father had confessed to running a Ponzi Scheme

► 12/02/2009 Madoff pleased guilty to 11 felonies going back to 1970’s

► Amounts missing from client accounts valued at $65 Billion

► Estimated actual losses to investors was $18 Billion

► Sentenced to maximum 150 years in prison

► BUT HE WAS ONLY CAUGHT AFTER HIS SON BLEW THE WHISTLE - NOT BY REGULATORS, CLIENTS OR POLICE


► "Year-on-year, impersonation fraud continues to grow. Since 1999, impersonation fraud has risen by 163% and is one of the fastest growing fraud types in the UK" - CIFAS

► False identity/impersonation fraud remains the most rapidly growing type of fraud in the United Kingdom." - CIFAS

► "An annual figure of £1.3 billion pa is the minimum quantifiable cost to the economy arising from identity fraud" - Identity Fraud: A Study, Cabinet Office

► "Identity theft is Britain's fastest-growing white-collar crime, increasing at nearly 500% a year." - BBC TV's Money Programme

And when you don’t know who is actually committing

the crime it is even more difficult…

► "A recent report on identity theft warned that there is likely to be "mass victimisation" of consumers within the next two years. The report said consumers should be extra careful to monitor all their financial transactions for unexplained account activity, withdrawals, or fund transfers." - The Gartner Group, a technology research group

► "More than £1.6 million worth of card fraud occurs on UK plastic cards every day. A fraudulent transaction takes place every eight seconds" - APACS

► "Experts report that a victim can spend anywhere from six months to two years recovering from identity theft." - CNNfn.com

► "Most people don't find out they have been a victim of a stolen identity until they are turned down for a loan or credit card. A copy of their credit report explaining the denial may unveil weeks or months of fraud." - CNNfn.com


Should we care?


► Private Sector fraud

► Fraud losses as a proportion of turnover estimated in the region of 0.54 per cent, with 0.18 per cent lost to detected fraud and 0.36 per cent lost to hidden or undetected fraud.

► This is approximately equivalent to £15.9 billion per annum

► Financial Services fraud

► The Department for Business, Innovation and Skills (BIS) has indicated that turnover data for Financial and Insurance activities were not comparable with other private sector turnover data.

► To overcome this, the business survey has been supplemented by an analysis of identified fraud losses and an estimate of possible undetected fraud loss from Financial and Insurance activities using the relative percentages of gross domestic product (GDP) for the sectors.

Estimated UK Fraud Losses – it’s a lot…

- Source: National Fraud Authority –Annual Fraud Indicator 2013

► If Financial and Insurance activities represent 11 per cent of all GDP, compared to 67% for the rest of the private sector, hidden or undetected losses would equate to £1.8 billion.

► In conjunction with other identified fraud loss estimates we have a combined figure for fraud in the Financial and Insurance activities of £5.4 billion

► The identified fraud losses in the Financial and Insurance activities include:

► £2.1 billion of insurance fraud

► £1 billion mortgage fraud

► £475 million of retail banking fraud.

► This is clearly an under-estimate as it does not include unknown fraud losses that have not been identified.

https://www.gov.uk/government/uploads/system/uploads/attachment_data/file/206552/nfa-annual-fraud-indicator-2013.pdf













Fraud is where there is a financial benefit involved

Opportunistic Premeditated Organized

Fraud schemes cross a wide range of perpetrator intention, potential impact and planning

► Eric’s home is broken into. How does it hurt if he claims he had an 80” television?

► Marissa knows most insurers will give her easy money for whiplash to settle a claim quickly before it escalates to higher payments. She slams on her brakes in front of a tailgating policyholder.

► Michael takes his job seriously. He knows the more people he can pack into the two junk vehicles he is staging a crash with, the higher the payout.


The Impact of Not Managing Fraud

► Direct financial loss

► Act as a magnet for MORE fraudsters when identified as a “soft touch”

► Increased policy costs encourage “claim inflation” by customers

► Reputational damage to your corporate brand ►Instant 24hour news

►Permanence of the internet


What can we do about it?


► “Veteran fraud management company FICO lives up to its reputation,” the report stated.

► “FICO is one of the most long-standing fraud management companies; its product provides robust real-time, cross-channel interdiction and easy configuration of case management fields.

► It offers easy alert aggregation as well as integration with third-party reporting and analytical solutions using a published database schema.

► The company has a differentiated mobile and cloud partnering and extensive behavioural analytics strategy. FICO has a large vertical footprint in financial services/banking, insurance, retail, government, and telecom verticals.”

Talk to FICO - Analysts rank us Leaders in Enterprise Fraud

► Forrester’s report cited the need for stronger defence systems in the face of staggering worldwide losses. “Forrester estimates that globally … banks and financial services organizations are losing between $12 billion and $15 billion annually,” the report said. Companies struggle to balance tougher antifraud efforts with a positive customer experience, the report noted.

► Companies reviewed included 41st Parameter, ACI Worldwide, CA Technologies, CyberSource, Fair Isaac Corporation (FICO), FIS, NICE Actimize, and SAS.

► Companies invited to be reviewed but declined were Accertify, Detica, Fiserv, and Retail Decisions Source: The Forrester Wave™: Enterprise Fraud Management, Q1 2013. FICO was among the select companies that Forrester invited to participate in this Q1 2013 report.


Marketing Policy Underwriting Loss Ratio Solution

Development Fraud

Profit per account through cross

marketing and selling

Straight-thru processing

Decrease in loss ratio Decrease in systems development time

Decrease in fraud losses through early

identification

30% 99% 35%

Sample Client Results within Insurance

8 % 50%

FICO bring benefits to the insurance industry

► FICO has engaged with a large number of insurance clients to improve their business’ functions and profitability

► FICO has driven performance improvements in core business functions through Decision Management led initiatives based around business rules, analytics and optimisation

► We work with insurers around the world and can share “global best practice”


Case Management

Analytics Social Network Analysis Business Rules / Model

Authoring Tools

FICO Fraud Solutions for the Insurance Industry

FICO provides the expertise, the analytics and the

environment for insurance fraud within the following portfolios:

MOTOR / PROPERTY / HEALTHCARE / INSIDER FRAUD

with immediate bottom line impact

An end-to-end fraud management solution

Business Consulting

Professional Services Operationalize:


FICO Analytic capabilities – use your data effectively

Fraud trained Outlier detection

Use tags to

differentiate the

innocent from the

guilty

Learn patterns and

identify aberrance

Fraud

SNA

Connects fraud rings across

seemingly unconnected data by

detecting and linking identity

information

Learn complex relations from identified fraud in historical data, then leverage this to predict fraud

Uncover new types of fraud by identifying outlier and aberrant claims

Social Network Analysis for identity and entity resolution

FICO uses multiple detection methodologies to improve detection rates and reduce false positives


“Organizations should continue with business analytics projects that

can help reduce costs or retain customers. There is growing evidence

that higher business analytics competency and pervasiveness

have a direct impact on competitiveness.”

—Worldwide Business Analytics Software 2009-2013 Forecast and 2008 Vendor Shares, August

2009, IDC #219383

“Through 2015, analytic applications will remain one of the fastest-

growing categories of BI and business applications..”

— Gartner: Predicts 2010: the Top Five Concerns in the Analytic Applications Space for the Coming Year,

12/14/2009, G00173384

“The chaos in the markets…should be a boon to firms that evaluate

portfolio risk. Buying in companies like these is a bet that in a world

awash in data and complexity, the firms that crunch the data will

become more valuable.” — Forbes, May 7, 2010

Today’s Top Businesses Compete Analytically Today’s Top Businesses Compete Analytically


“FICO is growing its presence in and beyond financial services by extending the

precision of analytics across all decision areas and by bringing more advanced

decision modeling and mathematical optimization within the reach of decision

management professionals.” — The Forrester Wave: Predictive Analytics and Data Mining Solutions, Q1 2010 (February 4, 2010)

“FICO continues to lead the services operations analytic applications segment

of the market.”

—Worldwide Business Analytics Software 2009-2013 Forecast and 2008 Vendor Shares, August 2009, IDC

#219383

“FICO is notable among analytic application providers in its extensive experience in

delivering high value in industry-specific, decision-centric applications.”

— Henry Morris, Senior Vice President , Worldwide Software and Services IDC

.”

FICO is the Leader in Analytics for Decision Management


FICO Identity Resolution Engine

Federated Search

Search across disparate data – BIG data and

SMALL data - in real time, or in

batch, to see where entities match across records

Discover

Real time visualization of

linking from known attributes and their

related entities

SNA

Pre-built visualization and inquiry of smart

networks to promote proactive analysis,

and facilitate reactive review

Reactive Review Proactive Analysis


Federated Search – Unique linkage across data sets

Search Request

• Full Name John Smythe

• Address 325 Mast Ct

• City Midland

• State MI

• Country USA

• DOB 9/22/1966

• Passport 981347823

Match Results

Match Full Name Address Passport Ref #

99% Jon Smythe 325 Mast Ct 981347823 345333

96% John Smythe 335 Mast Apt 202 981347820 656966

95% Jonathan Smith 202 – 325 Mast 981347820 965233

92% John Smith 352 Mast Ct 981347832 966898

• Connects to any data source – internal or external

• Utilizes more than 50 proprietary similarity search algorithms that can be tuned to the nuances of your

data and your appetite for fuzzy matching

• Avoids privacy issues and exposition of sensitive data via the privacy mode

• Does not require data cleansing, ETL or warehousing thereby eliminating problems associated with data

normalization and protecting the forensic integrity of data

• Leverages standards-based architecture utilizing technologies like SOAP web services, Java Script, XML,

LDAP and JDBC

• Easily tunable and extensible to scale to your needs


Discover (link analysis)

Expensive

• Valid identity info (phone numbers, addresses, etc) must be obtained and managed

Physical limitations

• People are limited to how many cell phones they can carry with them or number of addresses that they can have access to

Mental limitations

• There are only so many fictitious details a person can remember

Re-use or recycling of information

Relationships between seemingly unconnected data can be found

Extending the single entity view to visualize where attributes

are shared between these entities, in real-time


Link Analysis

Social Network Analysis

SNA is link analysis on steroids

Social Network Analysis (SNA) delivers 2 core functions:

► Analytics to drive detections of undesirable behavior

► Visual user interface to guides analysts to the connections that matter

While Link Analysis is an investigative tool that starts with a lead,

such as a customer whose connections you want to explore,

Social Network Analysis starts by building all the connections in the

data so that we can use analytics to inform where we investigate.


General Usage Models – Bi directional analysis B

atc

h F

raud

Dete

ction

Broad Search Analytically

Prioritized Results New Suspects

Tra

nsactional

Investig

ation

Known Suspect Targeted Search Specific Output


FICO Analytical capabilities – the best fraud defense

Description Claim Level Network Level

Association with

Known Bads

Using known bad data such as

hot addresses and existing

case data to find more fraud

Individual on a hot list

appears as a claimant

Multiple cases with fraud

outcomes and recoveries

exist on this network

Domain Specific

Rules

Using known footprints /

patterns of fraudsters, business

rules are written to identify for

review

Delayed claim report date

Incident date is close to

policy inception

This network shares injured

third party claimants across

otherwise unconnected

incidents

Statistical

Outliers

Using profiles of grouped claim

characteristics to identify

aberrant patterns

Medical billing is unusually

high given typical claim type

profile

High velocity of claims on

this network compared to

most networks

Predictive

Analytics

Using statistical models to

understand if and how

predictive varying indicators

and attributes are of future fraud

Claims containing a high

number of soft tissue injuries

is correlated with a fraud

outcome

Networks which contain

repeated incident

descriptions across claims

are correlated with fraud

outcomes

Fraud

Analytic capabilities


Conclusion

► However good you think your fraud defences are, you are under attack.

► Your data plus FICO’s expertise and analytic tools can help the fight back

► Don’t leave it till another day to talk to us…

► FICO can uniquely offer consultancy, software, data and analytic tools plus the associated training to make you self sufficient.

► Cloud hosted options reduce delay in obtaining IT resources

► All FICO fraud prevention investments pay for themselves within 6 months

© 2015 Fair Isaac Corporation. Confidential. This presentation is provided for the recipient only and cannot be reproduced or shared without Fair Isaac Corporation’s express consent.

Thank you.

Richard Hill Client Services – Partner E: [email protected] T: +44 7930 451758 Find me on Linked In.

mailto:[email protected]

richard hill_fico_marketforce insurance fraud_final_20150324

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