S T A T E O F C A L I F O R N I A Budget Change Proposal - C o v e r Shee t DF-46 (REV 08/16)

Fiscal Year 2017-18

= -.IT- . • —

Business Unit 0845

Department California Department of Insurance

Priority No.

Budget Request Name Program Subprogram 0845-001-BCP-2017-A1 0530 - Fraud Control 053055 - Enhanced Fraud -

Fraud Division

Budget Request Description

Enhanced Fraud Investigation and Prevention (Warner Chilcott Settlement)

Budget Request Summary

The California Department of Insurance (CDI) successfully litigated an anti-fraud case resulting in a settlement payment to the State of California which, according to statute, shall be used by CDI for enhanced fraud investigation and prevention efforts. Therefore, CDI is requesting a General Fund appropriation of $1,864,000 in Fiscal Year (FY) 2017-18 and $728,000 in FY 2018-19 through FY 2020-21, which is consistent with Insurance Code Section 1871.7 (g)(1)(A)(iv). These funds will provide resources to implement a fraud data analytics tool and support 2.0 positions to analyze the data generated from the data analytics tool.

Requires Legislation Code Section(s) to be Added/Amended/Repealed

• Yes M No

Does this BCP contain information technology (IT) Department CIO Date components? | ^ Yes • No David Noronha 4/1/2017

If yes, departmental Chief Information Officer must sign.

For IT requests, specify the project number, the most recent project approval document (FSR, SPR, S1BA, S2AA, S3SD, S4PRA), and the approval date.

Project No. 0845-052 Project Approval Document: Approval Date: 3/8/2017

If proposal affects another department, does other department concur with proposal? • Yes | ^ No Attach comments of affected department, signed and dated by the department director or designee.

Prepared By Date Reviewed By Date Crista Hill 4/1/2017 Julia Cross 4/1/2017

Department Director Date Agency Secretary Date Erika Sperbeck 4/1/2017 N/A

Department of Finance Use Only

Additional Review: • Capital Outlay • ITCU • FSCU • OSAE • CALSTARS • Dept. of Technology

BCP Type: • Policy • Workload Budget per Government Code 13308.05

PPBA Original Signed By Tiffany fiarnia

Date submitted to the Legislature

DF-46 (REV 03/13)

Fisca l Summary (Dollars In thousands)

BCP No.

0845-001-BGP-2017-A1

Proposal Title Enhanced Fraud Investigation and Prevention (Warner Chilcott Sett lement)

Program

0530

Personal S e r v i c e s Pos i t ions Dollars Personal S e r v i c e s C Y B Y B Y + 1 C Y B Y B Y + 1

Total Salaries and Wages ^ 0.0 2.0 2.0 $0 $124 $124

Total Staff Benefits ^ 0 56 56 Total Personal S e r v i c e s 0.0 2.0 2.0 $0 $180 $180

Operating E x p e n s e s and Equipment General Expense $0 $29 $6 Printing 0 0 0 Communicat ions 0 2 2 Postage 0 0 0 Travel-In State 0 2 2 Travel-Out of State 0 0 0 Training 0 1 1 Facilit ies Operat ions 0 19 19 Utilities 0 0 0

Consult ing & Professional Services: interdepartmental^ 0 0 0

Consult ing & Professional Services: External ^ 0 850 0 Data Center Services 0 266 1 Information Technology 0 515 517

Equipment ^ 0 0 0

Other/Special Items of Expense:

Total Operating E x p e n s e s and Equipment $0 $1,684 $548

Total State Operat ions Expendi tures $0 $1,864 $728

Fund S o u r c e Item Number

Fund S o u r c e Org Ref Fund

General Fund 0845 002 0001 $0 $1,864 $728

Special Funds^ Federal Funds Other Funds (Specify) Reimbursements

Total Loca l A s s i s t a n c e Expendi tures

Fund S o u r c e Item Number

Fund S o u r c e Org Ref Fund

General Fund

Special Funds^ Federal Funds Other Funds (Specify) Reimbursements

Grand Total, State Operat ions and L o c a l A s s i s t a n c e | $0 $1,864 $728

^ Itemize positions by classification on the Personal Services Detail worksheet. ^ Provide benefit detail on the Personal Services Detail worksheet. ^ Provide list on the Supplemental Information worksheet. " Other/Special items of Expense must be listed individually. Refer to the Uniform Codes Manual for a list of standard titles. ^ Attach a Fund Condition Statement that reflects special fund or bond fund expenditures (or revenue) as proposed.

DF-46 (REV 03/13)

F i s c a l Summary (Dollars in thousands)

BCP No.

0845-001-BCP-2017-A1

Proposa l Tit le

Enhanced Fraud Invest igat ion and Prevent ion (Warner Chi lcott Set t lement)

Program

0530

P e r s o n a l S e r v i c e s Pos i t ions Doi lars P e r s o n a l S e r v i c e s C Y B Y + 2 B Y + 3 C Y B Y + 2 B Y + 3

Tota l Salar ies and W a g e s ^ 0.0 2.0 2.0 $0 $124 $124

Tota l Staff Benefi ts ^ 0 56 56 Total P e r s o n a l S e r v i c e s 0.0 2.0 2.0 $0 $180 $180

Operat ing E x p e n s e s and E q u i p m e n t Genera l Expense $0 $6 $6 Printing 0 0 0 Communica t ions 0 2 2 Postage 0 0 0 Travel- In State 0 2 2 Trave l -Out of State 0 0 0 Training 0 1 1 Facil i t ies Operat ions 0 19 19 Util it ies 0 0 0

Consul t ing & Professional Serv ices: interdepartmental ^ 0 0 0

Consul t ing & Professional Serv ices: External ^ 0 0 0 Data Center Serv ices 0 1 1 Informat ion Techno logy 0 517 517

Equipment ^ 0 0 0

Other /Specia l I tems of Expense: *

Total Operat ing E x p e n s e s and E q u i p m e n t $0 $548 $548

Totai State Opera t ions E x p e n d i t u r e s $0 $728 $728

F u n d S o u r c e tem Number

F u n d S o u r c e Org Ref F u n d

Genera l Fund 0845 002 0001 $0 $728 $728

Specia l Funds^ Federal Funds Other Funds (Specify) Re imbursements

Totai L o c a l A s s i s t a n c e E x p e n d i t u r e s

F u n d S o u r c e tem Number

F u n d S o u r c e Org Ref F u n d

Genera l Fund

Specia l Funds^ Federal Funds Other Funds (Specify) Re imbursements

G r a n d Totai , State Opera t ions and L o c a l A s s i s t a n c e $0 $728 $728

' Itemize positions by classification on the Personal Services Detail worksheet. ^ Provide benefit detaii on the Personai Services Detail worksheet. ' Provide list on the Supplementai Information worksheet. " Other/Special Items of Expense must be listed individualiy. Refer to the Uniform Codes Manual for a list of standard titles. ^ Attach a Fund Condition Statement that reflects special fund or bond fund expenditures (or revenue) as proposed.

P e r s o n a l S e r v i c e s Deta i l (Whole dollars)

BCP No.

0845-001-BCP-2017-A1

Proposal Title

Enhanced Fraud Investigation and Prevention (Warner Chilcott Settlement)

Salaries and Wages Detail

Classification^ ^ Positions Saiary

Range Doliars

Classification^ ^ C Y BY B Y + 1

Saiary Range C Y BY B Y + 1

Associate Governmental Program Analyst 0.0 2.0 2.0 4,600-5,758 $0 $124,296 $124,296

Totai Salaries and Wages^ 0.0 2.0 2.0 $0 $124,296 $124,296

Staff Benefits Detaii C Y BY BY + 1 OASDI $0 $3,378 $3,378 Health/DentalA/lsion Insurance 0 18,252 18,252 Retirement

Miscellaneous 0 33,222 33,222 Safety 0 0 0 Industrial 0 0 0 Other: 0 0 0

Workers' Compensation 0 1,539 1,539 Industrial Disability Leave 0 0 0 Non-Industrial Disability Leave 0 0 0 Unemployment Insurance 0 3 3 Other: 0 0 0

Totai Staff Benefits^ $0 $56,394 $56,394

Grand Total, Personal Services $0 $180,690 $180,690

' Use standard abbreviations per the Salaries and Wages Supplement. Show any effective date or limited-term expiration date in parentheses if the position is not proposed for a full year or is not permanent, e.g. (exp 6-30-13) or (eff 1 -1 -13) Note: Information provided shouid appear in the same format as it would on the Changes in Authorized Posit ions.

^ If multiple programs require positions, please include a subheading under the classification section to identify positions by program/element.

^ Totals must be rounded to the nearest thousand dollars before posting to the Fiscal Summary.

P e r s o n a l S e r v i c e s Detail (Whole dollars)

BCP No.

0845-001-BCP-2017-A1

Proposal Title

Enfianoed Fraud Investigation and Prevention (Warner Chilcott Settlement)

Salaries and Wages Detail

Classification ^ ^ Positions Salary

Range Dollars

Classification ^ ^ CY B Y + 2 B Y + 3

Salary Range CY B Y + 2 B Y + 3

Associate Governmental Program Analyst 0,0 2.0 2.0 4,600-5,758 $0 $124,296 $124,296

Totai Salaries and Wages ̂ 0,0 2.0 2.0 $0 $124,296 $124,296

Staff Benefits Detail CY BY + 2 BY + 3 OASDI $0 $3,378 $3,378 Health/DentalA/ision Insurance 0 18,252 18,252 Retirement

Miscellaneous 0 33,222 33,222 Safety 0 0 0 Industrial 0 0 0 Other: 0 0 0

Workers' Compensation 0 1,539 1,539 Industrial Disability Leave 0 0 0 Non-Industrial Disability Leave 0 0 0 Unemployment Insurance 0 3 3 Other: 0 0 0

Totai Staff Benefits ̂ $0 $56,394 $56,394

Grand Totai, Personai Services $0 $180,690 $180,690

' Use standard abbreviations per the Salaries and Wages Supplement. Show any effective date or limited-term expiration date in parentheses if the position Is not proposed for a full year or is not permanent, e.g. (exp 6-30-13) or (eff 1-1-13) Note: Information provided should appear In the same format as it would on the Changes In Authorized Positions.

^ If multiple programs require positions, please include a subheading under the classification section to identify positions by program/element.

' Totals must be rounded to the nearest thousand dollars before posting to the Fiscal Summary.

S u p p l e m e n t a l I n f o r m a t i o n (Dollars in thousands)

BCP No.

0845-001-BCP-2017-A1

Proposal Title

Enhanced Fraud Investigation and Prevention (Warner Chilcott Settlement)

E q u i p m e n t C Y B Y B Y + 1

Total $0 $0 $0

C o n s u l t i n g & P r o f e s s i o n a l S e r v i c e s

External - Fraud Data Analytics Vendor Set-up and Configuration $0 $850 $0

Total $0 $850 $0

Faci l i ty /Capi ta l C o s t s

Total $0 $0 $0

One-T ime /L imi ted -Term C o s t s X No

Descr ipt ion B Y B Y + 1 B Y +2

Descr ipt ion P o s i t i o n s Dol lars Pos i t ions Dol lars Pos i t ions Dol lars

OE&E (Std. Complement) 0.0 $16

General Expense 0.0 5 Consulting & Professional Services - External 0.0 850

Data Center Services 0.0 265

0.0 $1,136 0.0 $0 0.0 $0

Fu l l -Year C o s t Ad jus tment Yes

Provide the incrementai change in doilars and positioi IS t

No

3y fiscal ye

X

ar.

Item Number B Y B Y + 1 B Y +2

Item Number P o s i t i o n s Dol lars P o s i t i o n s Dol lars Pos i t ions Dol lars

Total 0.0 $0 0.0 $0 0.0 $0

Future S a v i n g s Y e s

Specify fiscal year and estimated savings, including a

No

ny decrease i

X

r? p( Dsltions.

Item Number B Y B Y + 1 B Y +2

Item Number P o s i t i o n s Dol lars P o s i t i o n s Dol lars P o s i t i o n s Dol lars

Total 0.0 $0 0.0 $0 0.0 $0

S u p p l e m e n t a l Information (Dollars in thousands)

BCP No.

0845-001-BCP-2017-A1

Proposal Title

Equipment C Y B Y + 2 B Y + 3

Total $0 $0 $0

Consulting & Professional Serv ices

Total $0 $0 $0

Facility/Capital C o s t s

Total $0 $0 $0

One-Time/Limited-Term C o s t s Yes LX_ No

Description B Y + 3 B Y + 4 B Y + 5

Description Posit ions Dollars Positions Dollars Positions Dollars

Salaries & Wages / OE&E 0.0 0 2.0 $728 0.0 0

0.0 $0 2.0 $728 0.0 $0

Full-Year Cost Adjustment Yes No

Provide the incremental change in dollars and positions by fiscal ye

X

ar.

Item Number B Y + 3 B Y + 4 B Y + 5

Item Number Posit ions Dollars Positions Doilars Positions Dollars

Total 0.0 $0 0.0 $0 0.0 $0

Future Savings Yes

Specify fiscal year and estimated savings, including a

No

ny decrease ii

X

ipc isitions.

Item Number B Y + 3 B Y + 4 B Y + 5

Item Number Posit ions Dollars Positions Dollars Positions Dollars

Total 0.0 $0 0.0 $0 0.0 $0

Analysis of Problem

A. Budget Request Summary

The California Department of Insurance (CDI) successfully litigated an anti-fraud case resulting in a settlement payment to the State of California which, according to statute, shall be used by CDI for enhanced fraud investigation and prevention efforts. Therefore, CDI is requesting a General Fund appropriation of $1,864,000 in Fiscal Year (FY) 2017-18 and $728,000 in FY 2018-19 through FY 2020-21, which is consistent with Insurance Code Section 1871.7 (g)(1)(A)(iv). These funds will provide resources to implement a fraud data analytics tool and support 2.0 positions to analyze the data generated from the data analytics tool.

B. Background/History

On December 18, 2015, Insurance Commissioner Dave Jones announced that a $23,250,000 settlement had been reached between the CDI and whistle-blowers with pharmaceutical company Warner Chilcott to resolve a lawsuit alleging drug marketing fraud in violation of State law. The settlement resolved allegations contained in a pay-for-play qui tam health insurance lawsuit filed by three former Warner Chilcott employees. The whistle-blower lawsuit was filed in 2012 in a California Superior Court by the Simmer Law Group on behalf of the whistle-blowers. It alleged Warner Chilcott executives violated the California Insurance Code Insurance Frauds Prevention Act, which prohibits anyone from defrauding private insurance companies by using kickbacks or other inducements to procure or steer clients. As required by the State's insurance whistle-blower law, the Warner Chilcott settlement payment was divided between the whistle-blowers and the State of California. The State's share was $11,852,000, which was paid to the General Fund for enhanced fraud investigation and prevention efforts upon appropriation by the Legislature.

Commonly referred to as the "whistle-blower law". Section 1871.7 of the California Insurance Code (CIC) is set forth as part of the Insurance Frauds Prevention Act (IFPA, Chapter 12, Article 1, Section 1871 et seq.). Enacted in 1992, CIC Section 1871.7 of the IFPA provides that a private person, company, or entity may bring a civil lawsuit in the name of the State against any individuals, entities, or organizations that are alleged to be involved in the submission of false or fraudulent claims to an insurer.

Under the IFPA, the Commissioner is authorized to use his or her own attorneys to handle this civil litigation. If the Commissioner intervenes and is successful in recovering funds either in settlement or at trial, he or she is entitled to costs and attorney fees in litigating the case, and the State of California is entitled to 60-70 percent of the proceeds after payment of costs. The whistle-blower is entitled to 30-40 percent of the proceeds, the amount of which is determined by negotiation between the Commissioner's attorneys and the whistle-blower's attorneys. After the proceeds are paid pursuant to these percentages, CIC Section 1871.7(g)(1)(A)(iv) mandates the funds be paid to the General Fund and directs the Legislature to appropriate these funds for enhanced fraud investigation and prevention efforts.

As a result, CDI submitted a FY 2016-17 Budget Change Proposal (BCP) seeking General Fund resources for enhanced fraud investigation and prevention efforts and the Legislature approved an appropriation of $6,460,000 for a five-year period, leaving an available balance of $5,392,000.

Part of the funding received in FY 2016-17 supports Information Technology project planning activities for the Fraud Data Analytics Software (FDAS) project. These resources are being used to research software system alternatives, develop the project schedule and project plans, and finalize requirements that will be utilized for the procurement and system testing.

Analysis of Problem

Enforcement Branch - Fraud Division - Deputy Headquarters Office Resource History

(Dollars in thousands)

Program Budget FY 2012-13 FY 2013-14 FY 2014-15 FY 2015-16 FY 2016-17 (Projected)

Authorized Expenditures '̂ $2,627 $2,936 $3,055 $3,470 $3,558 Actual Expenditures '̂ $2,584 $3,090 $2,986 $3,311 $3,558 Authorized Positions '̂ 31.0 32.0 32.0 35.0 38.3 Filled Positions '̂ 29.9 31.5 27.3 30.7 38.3 Vacancies 1.1 0.5 4.7 4.3 0.0 " Based on Allotments. '̂ Based on FM13 year-end budget reports. Based on Salaries & Wages (7A).

C. state Level Considerations

This proposal aligns with the goals of the Commissioner to fight insurance fraud in California. One of the Commissioner's highest priorities has been to reduce insurance fraud as the cost of fraud is ultimately passed on to consumers in the form of higher insurance premiums. Insurance Fraud costs every household between $700 and $1,000 each year.

This proposal also aligns with CDI's Agency Information Management Strategy (AIMS), strategic business plan, and the State's strategic direction for Information Technology (IT) as well as the Department's strategic goal to advance effective and efficient business processes. The FDAS tool would enhance operational efficiencies by analyzing data to identify trends, patterns of fraud and networks of fraud that otherwise would go undetected. Moreover, once CDI gets a list of "usual suspects" the Department may be able to collaborate with other entities that have claims databases to target specific claims for suspects who may be involved in many complaints. This could provide an additional level of targeted enforcement opportunity.

This request is consistent with applicable State law and policies. Law does not need to be added, amended, or repealed in order to implement this request. Because the State received these funds as a result of CDI's enforcement efforts, the funds should be appropriated to CDI for enhanced fraud investigation and prevention efforts to be consistent with State law. If the State does not appropriate these funds for the purpose stipulated in statute, it may be seen as a waste of targeted resources for the fight against insurance fraud.

D. Justification

Fraud Data Analytics

The core mission of the Fraud Division (FD) is to protect the public and prevent economic loss through the detection, investigation, and arrest of insurance fraud offenders. The FD oversees the following five fraud programs: (1) Automobile Insurance Fraud Program, (2) Organized Automobile Fraud Activity Interdiction Program, (3) Disability and Healthcare Fraud Program, (4) Workers' Compensation Insurance Fraud Program, and (5) Property, Life and Casualty Fraud Program. These programs are funded through a combination of annual insurer general assessments and insurance policy assessments. The FD receives approximately 30,000 suspected insurance fraud referrals a year.

The Department has resources to investigate only approximately 5 percent (1,500) of these referrals. While investigating a case, investigators have access to materials provided by consumers and insurance companies, data, and reports from CDI's Fraud Investigation Database (FIDB), and manual research of external data sources. At case intake and supervisor review, CDI staff must manually look up data in internal and external data sources to identify the most likely cases to investigate.

Analysis of Problem

Cases are assigned at intake based on county. Currently, there is no way to immediately determine if networks of fraud (such as prescription drug fraud) that operate across several counties are linked to a single case. For example, if a fraud network operates across 10 counties, cases associated with that network will be referred to different offices. CDI's current Inability to identify related suspected fraudulent activity likely results in multiple, uncoordinated investigations and/or failure to identify larger fraud rings.

CDI would benefit greatly from having an analytical tool that analyzes information quickly, sifts through massive data sets, and assists in the FD's existing efforts to identify fraud trends and patterns and select significant and high-impact, multi-jurisdictional cases. Therefore, as part of the FY 2016-17 Warner Chilcott BCP, CDI requested funding of $450,000 that was approved for the planning phase of a Software-as-a-Service (SaaS) solution for enhanced fraud investigation and prevention efforts. CDI is now requesting the necessary resources of $1,630,000 in FY 2017-18 to implement the SaaS and $510,000 in FY 2018-19 through FY 2020-21 for maintenance and operations. Future resource requirements for maintenance and operations will be addressed through the annual budget process.

Note: The California Department of Technology (CDT) conditionally approved CDI's Stage 1 Business Analysis on April 1, 2016. CDT approved the Stage 2 Alternative Analysis on March 8, 2017. Stage 3 Solution Development is being completed and is anticipated to be approved by May 2017 and once Stage 4 Project Readiness and Approval is formally approved by CDT, the Department will procure the solution, complete organizational change management, implement the solution, and train the users on the software system. This collaboration with CDT will result in the successful implementation of the Fraud Data Analytics tool.

Implementation Phase

The CDI is currently in the planning phase that includes market research via a Request for Information and a Proof-of-Concept that has demonstrated the capability of the available SaaS products and the amount of configuration that will be necessary to meet the business needs. The detailed requirements reveal that there may be a significant amount of configuration necessary so that the FD can set prioritization categories and measures based on trends and the Department's priorities. Unique reports will be required to document the fraud case files. In addition to researching the technical solution, CDI is planning and implementing organizational change management strategies to ensure that the FD SaaS software users receive the new software tool positively, facilitating the acceptance and use of the new tool. The implementation will be phased, starting with the intake and assignment of functional workflows, and the FD detectives and case documentation functions will be added once all functionality has been configured.

CDI proposes to implement the Fraud Data Analytics SaaS project starting on July 1, 2017. This involves procuring the solution through a Request for Offer using the Software Licensing Program, configuring it to meet the FD's needs, testing, performing business process reengineering and organizational change management, and training users. Most of these implementation tasks will be performed by the solution vendor. CDI will provide project management, enterprise architecture, information security and technical expertise as appropriate. Cost details are identified in Table H-1 of Section H Supplemental Information.

Maintenance and Operations Phase

Effective July 1, 2018, resources will be needed to maintain the SaaS service and licensing to allow the FD to continue to perform data analytics on insurance fraud cases. All maintenance costs consist of ongoing subscription services that are prepaid annually. Cost details are identified in Table H-2 of Section H Supplemental Information. Since the Warner Chilcott Settlement funds are limited, ongoing funding to support the FDAS system maintenance will be requested through the BCP process.

It is essential that these resources are approved so the FD will have the tool it needs to leverage data analytics, identify trends and patterns of fraud, and establish networks of fraud in order to protect consumers. The data analytics tool will result in more loss recovery and more cases investigated, and will also improve officer safety through the detection of additional known associates. This will be accomplished with software functionality to discover external and internal networks that will yield a list of additional known associates, which will provide investigators with a much better profile of the individual and his or her connections. This is

Analysis of Problem

critical in instances where officers serve search warrants, etc. because it will provide background that will help investigators determine what they may expect, resulting in improved officer safety.

Fraud Data Analytics Positions

The data analytics analysts will work closely with ITD and Branch Law Enforcement throughout the implementation phase to assist in the development of the system as well as system testing. The analysts will work with operational staff, utilizing the analytics system, developing investigations and working closely with the detective staff throughout the course of the research to determine best practices. They will also create procedures and protocols for reporting as well as templates and queries. A user manual will also be created for statewide training and consistency of reporting. These positions will then be tasked with the training of future staff statewide. They will create the foundation for the expansion of the program as it is rolled out to regional offices statewide.

System evaluation will involve working with Investigative staff to determine how to best extract and present the data to support operational work in the regional offices. This work cannot be done working with ITD staff as they do not have the investigative background to determine if the data is viable for use to support investigative case work. The goal of the project is to have the majority of the on-line research that is currently done by detectives completed and evaluated by the data analytics team. The team will require orientation and training by a field detective in order to understand the needs of each type of case as well as how to present information that is immediately productive for the case investigator. Additionally, as the case develops the analyst can continue to provide data support as new information and leads develop.

Once the protocols have been established the fraud data analytics tool will analyze information quickly, sift through massive data sets, accelerate and pinpoint the FD's existing efforts to identify fraud trends and patterns as well as select significant and high-impact, multi-jurisdictional cases. The results generated from the data analytics tool will need to be analyzed further to develop the findings and provide the results to the Investigators. Therefore, the CDI is requesting $234,000 in FY 2017-18 and $218,000 in FY 2018-19 through FY 2020-21 to support 2.0 Associate Governmental Program Analysts to perform the majority of the front-end case data researching and summarization. This will allow the Investigators to focus their time and effort on witness interviews, surveillance, requesting and executing search and arrests warrants, and working with the DAs on case prosecution. (See Attachment A for Workload Analysis.)

If this request is not approved, the Department will not have the necessary resources nor the Fraud Data Analytics tool to increase fraud loss recovery, validate and confirm suspect profiles, decrease the amount of time required to identify potential known associates, and increase fraud network identification.

E. Outcomes and Accountability

Fraud Data Analytics

• Increases the capacity to investigate likely fraud cases by weeding out potential or non-fraud cases. • Implementation of data analytics potentially identifies networks of Fraud, increasing investigation yield

(one network versus several individual cases). • Implementation of this solution will enable the FD to identify patterns of fraud from historical data, which

when applied to recent data, enhances fraud detection and identifies fraud that otherwise may not have been detected. The net result is a highly efficient simplified process model.

• The project will leverage data analytics to improve the Division's loss recovery through the use of suspected fraudulent claim prioritization algorithms. It is anticipated that there will be an increase of 5 percent in loss recovery for the Division.

• The leveraged data analytics will provide investigators with a list of individuals and entities who may be of particular interest to the Division. These individuals and entities may be de-duplicated by the fraud detection system, associated with multiple active investigations, or have network links to other suspects

Analysis of Problem

on open or closed cases. It is anticipated that 100 percent of suspect profiles will be validated and confirmed by the system.

• A Fraud Data Analytics tool will improve officer safety through the detection of additional known associates, via lookups and links to other cases. This capability is estimated to provide a 10-percent decrease in the amount of time required to identify potential known associates.

• Investigators will have a robust link to analysis functionality to identify matches in data for known patterns of interest, detect anomalies, and discover new patterns. This visual representation of all linked data will allow an investigator to easily navigate through related datasets to identify and tag relevant data. This capability is estimated to provide a 10-percent increase in network identification.

The FD will measure and compare the loss recovery totals for the three fiscal years post-implementation to the three fiscal years prior to implementation to validate that program goals were met. Individuals and entities of particular interest will be measured by running a system report at the end of the first full calendar year on the number of validated suspect profiles. System reports will record the amount of time taken to identify known associates during one full calendar year to compare to the current baseline.

The system will document the findings of relevant data associated with networks of fraud. Then, a report will be generated on the data during one full calendar year post-implementation to compare to the current baseline of identified networks.

F. Analysis of All Feasible Alternatives

Alternative 1 - Approve as requested.

Pros:

• Resources will be available to enhance fraud investigation and prevention.

• Settlement funds paid to the GF would be used for their statutory purpose.

• GDI's practices for fraud investigations will be more effective and efficient; increasing loss recovery, validating and confirming suspect profiles, decreasing the amount of time required to identify potential known associates, and increasing fraud network identification.

• CDI will have the tools necessary to investigate large volumes of referrals in the most effective and efficient manner.

• FY 2016-17 Year 1 planning resources adopted in the Budget Act would not be wasted.

Cons:

• GF resources will be impacted; however, as a result of a whistle-blower settlement these monies were deposited in the GF for this purpose and are statutorily-intended for appropriation.

• Increases position growth in State Government.

Alternative 2 - Use Insurance Fund - Fraud revenue streams to support GDI's request for resources for enhanced fraud investigation and prevention efforts.

Pros:

• GF resources will not be impacted.

• GDI's practices for fraud investigations will be more effective and efficient; increasing loss recovery, validating and confirming suspect profiles, decreasing the amount of time required to identify potential known associates, and increasing fraud network identification.

Analysis of Problem

• CDI will have the tools necessary to investigate large volumes of referrals in the most effective and efficient manner.

Cons:

• Settlement funds paid to the GF would not be used for their statutory purpose.

• This is not a viable option because the Insurance Fund - Fraud fund balances cannot support a request of this magnitude.

Alternative 3 - Deny the request.

Pros:

• GF resources will not be impacted.

• No position growth in State Government.

Cons:

• Settlement funds paid to the GF would not be used for their statutory purpose.

• A significant amount of fraud would go uninvestigated.

• Fraud Division will continue to use the current manual investigative processes and tools which are less effective and inefficient.

• CDI will not be able to increase loss recovery, validate and confirm suspect profiles, decrease the amount of time required to identify potential known associates, and increase fraud network identification.

• FY 2016-17 Year 1 planning resources adopted in the Budget Act would be wasted.

G. Implementation Plan

Fraud Data Analytics

The Fraud Data Analytics IT project implementation of a SaaS solution will include CDT project oversight. The solution will be available to procure from the Department of General Services Software Licensing Program (SLP) which will streamline the procurement process and timeline.

Analysis of Problem

FY 2017-18 - IT Project Implementation Schedule

Task Name Start Date End Date

Plan/Conduct Project Meetings 7/1/2017 6/30/2018

Project Kick Off Meeting 7/4/2017 7/4/2017

Develop and Release Solution Solicitation 7/4/2017 7/10/2017

Perform Project Oversight 7/4/2017 6/30/2018

Evaluate Proposals and Award Contract 8/15/2017 9/1/2017

Application Track 7/14/2017 11/15/2017

System Design and Documentation 7/14/2017 8/15/2017

System Testing 9/1/2017 11/15/2017

Application User Training 10/15/2017 12/15/2017

User Testing 11/15/2017 12/15/2017

Help Desk Support Services 10/15/2017 6/30/2018

Project Close Cut 12/30/2017 1/31/2018

Post Implementation Evaluation Report (PIER) 6/18/2019 7/24/2019

FY 2018-19 - FY 2020-21 Maintenance and Operations

Implementation includes a Maintenance and Operations Plan and utilizes CDI Help Desk support to assist Fraud with issues that may arise with the SaaS solution since the analytics tool used will be phased based on functionality. GDI's ITD will utilize existing staff resources to provide support to the system users. The FD will train new staff on utilizing the data analytics tool. CDI will renew the SaaS subscription annually through the appropriate procurement method.

Fraud Data Analytic Positions

The FD would begin the recruitment process in April 2017 to allow for the proper vetting of applicants and to get candidates filled by July 1, 2017. The hiring will be contingent upon approval of the positions being included in the FY 2017-18 Budget Act.

Analysis of Problem

H. Supplemental Information

Table H-1 FY 2017-18 Proposed Fraud Data Analytics Software - SaaS Vendor Cost Breakdown

Item Implementation Costs

General Expense

Department of General Services Fees @1.06% of contract value (Professional Services and License Fees)

$15,000

Consulting & Professional Services - External

Fraud Data Analytics SaaS Vendor Costs Initial Setup and Configuration $850,000

Configure Fraud's User Interface to meet the business needs. Hourly rates '̂

• Cnsite Support - $125.00 • Sr. Technical Engineer - $150.00 • Product Tech Support - $130.00 • Associate Tech Support - $85.00

Consolidated Data Center (CDT Fees)

Memorandum of Understanding - California Department of Technology • Project Manager

$185,000

California Department of Technology - IT Project Cversight (ITPCD) Consultant @ $9,380 for 7 months (includes oversight through implementation and the PIER review)

$75,000

California Department of Technology - Statewide Technology Procurement Division - $126 per hour X 40 hours (includes review and approval of Request for Cffer, Selection Plan, and resulting Contract)

$5,000

Information Technology

Fraud Data Analytics SaaS Vendor Costs Year Cne License Fees $500,000

Total $1,630,000 " SAS Response to Request for Information.

Analysis of Problem

Table H-2 FY 2018-19 - FY 2020-21 SaaS Maintenance Cost Breakdown

Item Implementation Costs

General Expense

Department of General Services Fees @1.06% of contract value (License fees)

$5,000

Information Technology

Fraud Data Analytics SaaS Vendor License Maintenance Fees (Includes technical support)

$505,000

Total $510,000

I. Recommendation

Alternative 1 - This is the only alternative that will provide the resources intended and necessary for CDI to implement a Fraud Data Analytics tool and enhance its fraud investigation and prevention efforts, particularly against seniors. Without these resources California consumers will continue to be harmed by fraudulent activity that is not investigated or prosecuted.

Denial of this proposal will not provide the resources necessary to enhance fraud investigation and prevention efforts and ultimately weaken the Commissioner's fight against insurance fraud in California.

California Department of Insurance FY 2017-18 Spring Finance Letter 0845-001-BCP-2017-A1

Attachment A

Enforcement Branch - Fraud Division Workload Analysis

FY 2017-18 (In Hours)

T A S K S ASSOCIATE

GOVERNMENTAL PROGRAM ANALYST

Data Analytics Development • Work with the Information Technology Division and Fraud Division

Branch Law Enforcement to develop the fraud data analytics system through implementation.

• Perform beta testing and other analytical functions needed for the development of the data analytics system.

• Work with Investigative staff to determine how to best extract and present the data to support operational work in the regional offices.

• Work closely with the detectives and other investigative staff throughout the course of system development to determine best practices needed to have the majority of the on-line research that is currently done by detectives completed and evaluated by the data analytics team.

• Conduct research as needed to determine best data gathering practices, queries, and other databases.

• Attend training by detectives in order to understand the needs of each type of case as well as how to present information that is immediately productive for the case investigator.

• Develop process to use as a case develops so additional data support can be provided as new information and leads develop.

2,690

Development of Procedures / Protocols • Create Division procedures and protocols for fraud data analytics

reporting as well as templates and queries. • Write a user manual for statewide training and consistency of

reporting. • Develop training program that will be rolled out in year 2. 950

Total 3,640

Position Equivalent (Hours/1,778)^' 2.04 " CDI is requesting 2.0 positions for these activities.

California Department of Insurance FY 2017-18 Spring Finance Letter 0845-001-BCP-2017-A1

Attachment A

Enforcement Branch - Fraud Division Workload Analysis

FY 2018 -19 -FY 2020-21 (In Hours)

T A S K S ASSOCIATE

GOVERNMENTAL PROGRAM ANALYST

Data Analysis • Review, analyze and evaluate Fraud Division Suspicious Fraudulent

claims data. • Utilize the Fraud Division's Fraud Investigation Database and Fraud

Data Analytics System to identify crime trends and possible criminal activity.

• Research and analyze complex law enforcement data; identify and interpret activity, patterns and trends; and forecast trends to aid in the assignment of cases for investigation and the assignment of adequate personnel.

• Use computer databases, electronic spreadsheets, word processing and statistical applications to manipulate, analyze and present data. 1,820

Reporting • Make written and oral presentations, using maps, charts and graphs to

inform investigative staff and management of emerging or existing crime series, patterns and trends, as well suspect profiles.

• Develop statistical data resources to assist in on-going criminal investigations.

• Utilize Microsoft programs to create reports on analysis of crime trends and research findings.

• Develop statistical data resources to assist in on-going criminal investigations.

• Compiling and packaging relevant data and statistical analysis for case file presentation to Regional Offices,

• Maintain Regional Office fugitive files and confidential informant files, conduct required Due Diligence and update databases.

1,456

Special Projects • Assists with database development related to data analysis and case

tracking and reporting. • Conduct research and analysis as requested by the Assistant Chiefs in

assigned special projects. 182

Travel for Training • Travel to all nine Division regional offices in order to train investigative

staff on the data analytics system and reports. 182

Total 3,640

Position Equivalent (Hours/1,778)^' 2.04 " CDI is requesting 2.0 positions for ttiese activities.