2. fraud
can be broadly defined as an intentional act of
deception involving financial transactions for
purpose of personal gain.
Fraud is a crime, and is also a civil law violation.
/frɔːd/
financial
3. How fraudulent is Singapore?
Factors
contributing
to Fraud
53% Identified weak or overridden internal
controls as a leading enabler of fraud
30% Cited collusion between employees
and third parties
17% Cited collusion between employees
Source: Singapore Fraud Survey 2014
Occurrence
29%
vs 21% in 2011
Detection
20%
vs 15% in 2011
Perpetrators
58%
vs 47% in 2011
4. Healthcare expenditure lost to fraud annually
Global estimates
USD 415 Billion
Europe
56 Billion Euro
Source: European Healthcare Fraud & Corruption Network
5. Vulnerability of Healthcare
• Large amounts of money involved, multiple parties
processes with high risk of bribery.
• High degree of information imbalances and an inelastic
demand for services.
• Healthcare providers usually assumes a cultural role as
trusted healers who are above suspicion.
• Claims amounts tends to be insignificant and thus lack of
attentive focus.
6. Health Insurance Fraud &Abuse
Scale & Impact
• It is estimated that as much as 10% of total healthcare spending in the United
States are due to fraudulent activities, amounting to a cost of about $115
billion annually.
• In the United Kingdom, the Insurance Fraud Bureau estimates that the loss
due to insurance fraud in the United Kingdom is about £1.5 billion ($3.08
billion), causing increase in insurance premium.
• Some estimate that $260 billion (180 billion euros) or approximately 6% of
global healthcare spending is lost to fraud each year. This is the equivalent to
the GDP of a country like Finland or Malaysia being stolen on an annual
basis.
Fraud is a huge issue – it is widespread and expensive. Many people think its
fine to defraud insurers, for instance, 30% would not report someone else who
defrauded an insurer. Physicians often game the system to get coverage for
patients.
10. 5 steps in Data Analytics
1. Import Data
2. Prepare Data
3. Analyze Data
4. Report
Findings
5. Automate
11. Examples of analytic applications for
healthcare
• Duplicate Claims – Identify any duplicate claims being submitted
• Age-specific procedures – Identify potentially suspicious exceptions to age-
specific procedures
• Gender-specific procedures – Identify potentially suspicious exceptions to
gender-specific procedures
• Physician specialty – Identify trending for physician’s codes which are outside
of their field of specialty
13. Case Study -
Fraud in Singapore’s Healthcare sector
• 2 dental clinics suspended from offering subsidized care to middle-
and low-income Singaporeans and Pioneer generations
• Stripped of ability to offer patients subsidies under the CHAS scheme
• Both clinics continuously made claims that breached MOH rules and
guidelines
• Non-compliance can sometimes be due to simple administrative
errors, such as: recording of wrong dates
• Possibility of fraud happens when claimed procedures does not
match actual treatment, or when claims are made for procedures that
were not done.
14. In summary…
Healthcare fraud poses a serious financial drain on
the healthcare systems in many jurisdictions and
prevents the effectiveness of providing healthcare
to those in need.
Organizations can deploy sophisticated anti-fraud
data analytics to help detect fraud and misconduct
as well as to understand the root causes of
irregularities.
Pressure or Motivation to Commit Fraud – Is the motivation behind the crime and can be either personal financial pressure, or workplace debt
Opportunity to commit Fraud – the means by which individuals will defraud the organization. It is the clear course of action by the person
Rationalization for committing fraud – Rationalization occurs when people know what they are doing is wrong, but they convince themselves it is right
