1. Why Hire Navin Sinha for BIG Data
Healthcare Fraud Analytics?
1. What credentials does Navin offer?
2. Why would Navin be
the logical and inescapable choice for
healthcare fraud analytics?
3. High stakes commitment-
Why should Navin be the only choice?
4. Why should I actually trust Navin? How good is
his judgment?

2. 1. What credentials does Navin offer?
1. Saved ex-employer, DSM Food Specialty (2001-2003) from $20 Million defective
product lawsuit. The top external CPG client based in Minnesota, claimed that
DSM bacteria culture were in effective in making cheese. The client had collected
and analyzed data, and was moving towards $20 million product liability lawsuit...
Reviewed statistical methods and client accepted the since no data was collected
and analyzed by survival analysis, the lawsuit has no merit. All together saved $30
million in 3 years in CPG industry.
2. Stopped ex-employer, Best Buy spending $2 Million in bad marketing campaign
(2004). Served as internal client to sales and marketing department. Requested
and analyzed advertising data before a key marketing campaign. Platform (store)
analysis results indicated no statistical difference in control and marketing
targeted stores. Further statistical analysis found the right segment to market in
later advertising campaigns. All together saved $4 million in 4 months.
3. As a Analytics entrepreneur, advised Top Banking and Office supplier in USA (2004-
2005). My efforts saved them $ 200K and $100K, respectively.
4. Saved >20 million $ between February 2005 and June 2007 from Healthcare
Insurance Fraud for United health Group.
5. Global Sourcing was a failing venture for UHG (2005-2007). Demonstrated how to
train UHG-India analyst; leading to successful off shoring of Healthcare Insurance
Fraud Analytics. They are still saving money today…

3. 1. What credentials does Navin offer?
6. COMPLETED XCEL ENERGY PREDICTIVE ANALYTICS IN RECORD 240 HOURS AND
INCREASED PREDICTIVE POWER FROM 19% TO 52%. THAT IS ADDITIONAL $1 MILLION
SAVINGS WHERE NONE WAS EXPECTED. ALL TOGETHER SAVED THEM $5 MILLION
WITHIN 6 MONTHS (2007-2008) IN AN INDUSTRY WITHOUT PRIOR EXPERIENCE.
ANOTHER TOP 5 CONSULTING COMPANY HAD TO RETURN >$ 250K ON SAME PROJECTS
AS RESULTS WERE JUDGED IN COMPARISON TO MY OUTPUT- ‘BELOW STANDARD’.
7. ADVANCE ANALYTICS ON BEHALF OF EX-EMPLOYER WIPRO CONSULTING FOR THEIR
CLIENT (TOP US NEWS MAGAZINE) WAS SO CONVINCING THAT EVEN THOUGH GERMAN
LAW PROHIBITED OFF SHORING, $50 MILLION CONTRACT WAS WON (2008). ALL
TOGETHER , MY ANALYTICS EARNED $100 MILLION CONTRACT FROM 4 DIFFERENT
CLIENTS FROM 4 DIFFERENT INDUSTRIES, IN 10 MONTHS (2008).
8. HEAD OF HEALTHCARE FRAUD ANALYTICS WAS OFFERED BY SATVIK ANALYTICS (200
MILLION $ COMPANY, INDIA) CEO IN APRIL 2010. DEEP CLINICAL TALENT WAS NOT IN
INDIA IN 2010.

4. 1. What credentials does Navin offer?
9. QUITE LARGE SIGNING BONUS FOR HEALTHCARE FRAUD ANALYTICS LEAD SCIENTIST POSITION
BY 2 BILLION $ VERISK ANALYTICS COMPANY IN SAN FRANCISCO WAS OFFERED IN JULY 2010.
HIRED AS A SUBJECT MATTER EXPERT (SME), JUST MY SALARY WAS MORE THAN TWO TIMES THAT
OF 2007 SALARY IN UHG. AT THAT TIME UNEMPLOYMENT OFFICIALLY IN CALIFORNIA WAS >14.0%
AND IN BAY AREA WAS >12.0%.
10. I SAVED $10 MILLION $ FROM ONE PREDICTIVE ANALYTICS ENDEAVOR OVER 5 MONTHS FOR A
TOP 5 HEALTHCARE INSURANCE CLIENT IN USA. I CREATED 95% OR 400 HEALTHCARE FRAUD
VARIABLES; HALF OF THEM WERE CLINICAL. WHEN THESE VARIABLES WERE APPLIED TO RELATED
VERTICALS, IT SAVED ANOTHER $10 MILLION. MADE TWO VERY SUCCESSFUL PRESENTATIONS TO
CEO; ALL OF THIS WAS ACHIEVED WITHIN ONE YEAR OF EMPLOYMENT.
11. I WAS LURED AWAY FOR HEALTHCARE FRAUD MANAGER POSITION IN TN WHERE I
SAVED AT LEAST 6 MILLION $ IN 4 MONTHS (>$1 MILLION/ MONTH; OCTOBER 2011-
JANUARY 2012).

5. 2. Why would Navin be the logical and inescapable
choice for healthcare fraud analytics?
1. SERVED HUNDREDS OF UNITED HEALTH GROUP (UHG) CLIENTS AND APPLIED 50+
STATISTICAL METHODS TO STOP PROVIDER FRAUD, WASTE AND ABUSE (FWA) IN UHG NET
WORK. THESE METHODS WERE INCLUDED IN FWA PRODUCTS AND MADE KEY $ SAVINGS
CONTRIBUTIONS BETWEEN FEBRUARY 2005 TO JUNE 2007. (
HTTP://WWW.INGENIX.COM/CONTENT/ATTACHMENTS/06-
10298%20UHC%20CASE%20STUDY.PDF ).
2. UNDERSTOOD THE VALUE OF PROCEDURE AND DIAGNOSIS COMBINATIONS AND
TRAINED QUITE DEEPLY IN CLINICAL ASPECTS OF HEALTHCARE FRAUD
(HTTP://WWW.INGENIX.COM/~/MEDIA/INGENIX/RESOURCES/DOWNLOADS/1003622_PPI
_WHITEPAPER_FINAL.PDF ) ANALYTICS.
3. QUITE CURRENT IN PROCEDURE (CPT) ICD9 AND ICD9 TO ICD10 CROSSWALKS.

6. 2. Why would Navin be the logical and
inescapable choice for healthcare fraud analytics?
11. THERE IS A STARK DIFFERENCE HERE; BILLION $ COMPANIES ARE FROM FINANCIAL
INDUSTRY. THEIR MAIN OBJECTIVE IS TO SELL MILLION $ PROPRIETY ANALYTICS TOOL .
NAVIN SINHA HAS NO SUCH VESTED INTERESTS!! IN FACT, NAVIN TOOK THE $10 MILLION
FRAUD PROJECT IN PREVIOUS EMPLOYMENT AND FINISHED IT ON A =<$100 TOOL .
2.THERE IS A STARK DIFFERENCE HERE; BIG COMPANIES INCREASE THE OVERHEAD COST BY
MILLIONS $ PER YEAR. COMPARE THAT WITH $0.0 OVER HEAD EXPENSE OF NAVIN SINHA!
3. I SAVED $5 MILLION IN PREVIOUS JOBS FROM SIMPLE STATISTICS ANALYSIS. I USE
ADVANCE MATHEMATICS IF AND WHEN NEEDED. MY RATES DO NOT GO UP IN ORDER TO
MAKE IT UP FOR ABSENCE OF SELLING MILLION $ PROPRIETY ANALYTICS TOOL.
4. NAVIN SINHA IS A ONE STOP HEALTHCARE FRAUD ANALYTICS SHOP. WITH INSIDE OUT
CLINICAL KNOWLEDGE AS WELL AS MATHEMATICAL DEPTHS , I PROVIDE BEST OF THE TWO
WORLDS AT NEVER BUDGET BUSTING RATES! ANALYTICS TOOL IS YOUR CHOICE, NOT MINE!!

7. 3. High stakes commitment-
Why should Navin be the only choice?
1. HEALTHCARE FRAUD ANALYTICS IS A LOGICAL SCIENCE WITH STEPS BUILT IN IT. ONE STARTS WITH
DATA ERROR/ QUALITY, DATA SAMPLING, SIX SIGMA STEPS, SIMPLE DESCRIPTIVE AND PREDICTIVE
ANALYTICS, MULTIVARIATE STATISTICS AND LAST, ADVANCE ANALYTICS. WHEN COMBINED
APPROPRIATELY WITH HEALTHCARE BUSINESS, AT LEAST 50% OF THE FRAUD CAN BE CAUGHT IN THE
BEGINNING STEPS. FOR EXAMPLE, IN TN (2012), I CAUGHT 4 MILLION $ FRAUD ON ONE PROJECT IN
3 WEEKS. THE PROCEDURE AND DIAGNOSES COMBINATION DURING DATA QUALITY AND SAMPLING
SHOWED UP FOR COMMERCIAL POPULATION, WHEN IN FACT IT MUST BE BILLED FOR MEDICARE
PATIENTS ONLY. IF YOU DON’T KNOW CLINICAL AND BUSINESS ASPECTS OF HEALTHCARE, ONE ENDS
UP APPLYING GIGA (GARBAGE-IN-GARBAGE-OUT) ADVANCE ANALYTICS…
2. MANTRA HERE IS, “SIMPLICITY, CREATIVITY AND SENSE OF URGENCY” FOR MY CLIENTS. I CARE
FOR SIZE OF PRIZE; I DON’T CARE FOR SQUATTING A FLY WITH ATOM BOMB. FOR EXAMPLE, I WAS
LOOKING AT THE CARDIOLOGY SPECIALTY IN TN STATE AND APPLIED BASIC STATISTICS. I FOUND
MOST FREQUENT OBSERVATION AROUND $20. FIRST THOUGHT, CAN YOU HAVE HEART SCREEN FOR
SUCH A LOW $? THEN I LOOKED AT THE TOP 2 DIAGNOSES WITH THEM. THESE DIAGNOSES MUST BE
BILLED IN FACILITY/ HOSPITAL ONLY! NO WAY A PROVIDER/ DOCTOR BILLS THIS CHEAP/ DOWN
CODING! THAT’S WHEN I REPORTED THOSE PROVIDERS BILLING 2 MILLION $, TO THE COMPANY.

8. 3. High stakes commitment-
Why should Navin be the only choice?
1. VERISK (2011-2012) HAD HAND PICKED PHD ENGINEERS FOR HEALTHCARE FRAUD ADVANCE
ANALYTICS. WE ALL REPORTED TO VICE PRESIDENT(VP). THE RESULTS WERE SUCH THAT CLIENT HAD
FINGER ON TRIGGER; GIVE ME TWO REASON FOR NOT TAKING MY BUSINESS ELSEWHERE. THE VP
SENT EMAIL- “I AM IN A MEETING AND ITS VERY CRITICAL FOR ME; REPLY WITHIN 5 MINUTES!” AS A
SME, I WROTE- “1) IT IS POSSIBLE THAT THERE WERE NOT ENOUGH HISTORY TO SCORE PROVIDERS
HISTORICALLY. FOR EXAMPLE, ID ANALYTICS DELIVERED PREDICTIVE ANALYTICS FOR UNITED HEALTH
GROUP THAT INCLUDED MEDICAID PATIENTS. IT TOOK VERY LONG TIME TO CREATE AND CAUGHT
ONLY $1 MILLION FRAUD FOR CLIENTS. 2) WHEN HISTORY IS INFREQUENT, ONE NEEDS TO BUILT
FRAUD CONDITIONS TO SAVE MONEY PROSPECTIVELY. WITH SOME TUNING, IT CAN BE USED AS
VARIABLES FOR ADVANCE ANALYTICS SUCH AS DECISION TREE. FOR EXAMPLE, QUANTIFYING
PROVIDERS BILLING ON SUNDAY ONLY IS A FRAUD CONDITION. NEED AT LEAST 100 FRAUD
CONDITIONS LIKE THIS. I HAVE DONE A LOT IN UNITEDHEALTH GROUP AND REQUIRES SOLID
UNDERSTANDING OF PROCEDURE & DIAGNOSIS OCCURRENCE MATRIX. I WILL SHOW HOW BUT
DEPENDS UPON CLIENT ‘S AFFORDABILITY ($). “
2. THE ABOVE EXAMPLE SHOWS MY DEPTH IN HEALTHCARE FRAUD. A VERY TENSE MOMENT FROM A
DIFFICULT CLIENT WAS TURNED INTO A BUSINESS OPPORTUNITY. HOW MANY HEALTHCARE ADVANCE
ANALYTICS PROFESSIONAL ARE ABLE TO TURN THE TIDE THIS WAY???

9. 3. High stakes commitment-
Why should Navin be the only choice?
1. SOLID UNDERSTANDING OF HEALTHCARE FRAUD BUSINESS :- WHERE IT IS GOING. WITH PLETHORA OF OUTLIER
EVENTS, FRAUD CONDITION IS THE ONLY WAY TO GO TILL DECEMBER 2013 FOR FACILITY. NEW HEALTHCARE LAWS
COME IN ACTION FROM JANUARY 2014. ICD9 TO ICD10 CONVERSION NEEDS TO BE UNDERSTOOD AND EXPLOITED,
AND NAVIN SINHA DOES.
2. MEDICAID AND OUTPATIENT REIMBURSEMENT IS INCREASING FROM 2014. THEY WILL EXPERIENCE LARGE
FRAUD AMOUNTS. NOT SAS TYPE ADVANCE PREDICTIVE ANALYTICS; ALL TYPES OF DATA QUALITY ANALYSIS TO
ANALYTICS BASED ON SOLID UNDERSTANDING OF HEALTHCARE BUSINESS WILL BE NEEDED.
3. COMMERCIAL POPULATION OR EMPLOYER GROUP IS GOING TO BE BROKEN INTO MANY HEALTH EXCHANGES
ACROSS STATES. DATA QUALITY TO ADVANCE ANALYTICS WILL BE NEEDED HERE. THIS IS A YOUNG POPULATION
SEGMENT THAT DOESN’T GET SICK OFTEN, AND HENCE QUITE PROFITABLE. NAVIN SINHA HAS PROVED HIS
SUCCESS IN THIS SEGMENT IN PAST.
4. MEDICARE FRAUD IS 80 BILLION $ NOW. IT WILL BE $138 BILLION IN 2017 (CMS 2011). ALL TYPES OF DATA
QUALITY ANALYSIS-TO -SAMPLING- TO -ANALYTICS IS NEEDED NOW FOR PROFITABILITY IN THIS DOMAIN.
PROCEDURE (CPT) TO ICD9 DIAGNOSIS CROSS WALK IS CRITICAL ALWAYS ($)!
5. NAVIN SINHA HAS MASTERED THOUSANDS OF THESE CROSS WALK FOR FRAUD ANALYTICS . ABOUT 25% OF
THE ICD9 MAP INTO ICD10 DIRECTLY. NOT ALL ICD9 AND 10 ARE FRAUDULENT, BUT NAVIN SINHA KNOWS WHICH
ONE IS- RIGHT NOW!

10. 4. Why should I actually trust Navin? How
good is his judgment?
1. I am author of 12 peer reviewed publications, 8 as a first author. Between 1987-
2000, used plenty of judgment to plan , execute and publish the research results.
2. Curiosity is another word for judgment and I used plenty of it when confronted with
new industry data. Regardless of what industry data belonged to, I played with it with
child like curiosity. The bottom line impacting results from 2001-2011 corporate
projects presented in first few slides, have laid solid foundations for all the projects ($)
to come since 2012.
3. In 20 years or so in America, I have learned good judgment comes from 3Ps:-
Polite, Persuasive and Persistence. It was my persistence since 2001 to Invent a way to
analyze data with 50 or more non-statistically significant variables by Neural Network
on Excel. At Xcel energy, my persistence made the rest as they say-”History.”
4. All projects in Ingenix were scoped by Navin Sinha. There was 120% freedom on which
project you worked on. Every Monday morning by 10 :00 AM, I had the analytics report
ready with savings $ for Senior Management. I usually scoped 6-7 projects every
week, and used judgment to figure out- which one should be in the hopper this week
for highest fraud recovery $.
5. Used plenty of good judgment to lead Verisk in clinical as well as with healthcare fraud
mathematical success. I was asked to take over from 1st November 2010 to 31st august
2011 (8 months), a duration that saw revenue from $0 to at least $20 million.
6. Last but never the least, conceptualized the patentable product in travel industry and
made solid judgment in when and how to file and keep appealing after office action
(rejection) after first few patent filings. Eventually I got it (patent # 7,617,828) after
trying for 5 years.