Fraud is a crime and civil violation involving intentional deception for personal gain, costing the global healthcare system an estimated $415 billion annually. Data analytics can help detect fraud through identifying anomalies like duplicate claims, age/gender-specific procedures outliers, and physicians billing outside their specialty. Singapore suspended two dental clinics for continuously breaching rules through non-matching claims and procedures not performed. Data analytics provides a defense against fraud through monitoring for irregularities.

1. FRAUD AND
DATAANALYTICS
Fighting fraud in Healthcare with Data

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.

7. Why commit fraud?
Pressure or Motivation
Opportunity Rationalization
Fraud
Triangle

8. HOW CAN DATA
ANALYTICS HELP?
Using Data Analytics to detect anomalies

9. Three Line of Defense Model
Data Analytics

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

12. Maturity level of Data Analytics

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.

15. THANK YOU!