The document discusses the need for organizations to refresh their financial systems beyond regulatory reasons, highlighting environmental challenges and the importance of technology upgrades. It emphasizes that modern financial systems are crucial for compliance, competitive advantage, and effective data management. The text outlines strategic considerations, implementation challenges, and best practices for transitioning to new financial systems to enhance operational efficiency and responsiveness.

1. Presented by:Presented to:
THE NOLAN COMPANY
Why Regulation isn't the
Only Reason to Refresh
Financial Systems
Steven M. Callahan, CMC®, FFSI
August 29, 2013
Practice Director
www.linkedin.com/in/stevencallahan

2. 8 Financial Systems Replacement : August 29, 2013
Overview of Financial Systems Fit with Legacy Upgrades
Table Of Contents
• The Nolan Company
• Webinar Overview
• Environmental Challenges
• Relevant Survey Results
• Implementation Considerations
• Closing Thoughts

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Introduction
The Nolan Company
• The Nolan Company is a management consulting firm comprised of highly skilled
and knowledgeable industry experts.
• Celebrating 40th Anniversary serving Insurance, Healthcare and Banking clients.
• Focus is on solving complex operational and technical business challenges.
• Approach is by partnering with clients to bring our industry expertise to client staff.
• Outcomes are improvements in client competitiveness, effectiveness, and
performance that continue long after our involvement ends.

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Webinar Overview
Why Regulation isn't the Only Reason to Refresh Financial Systems
Environmental reasons add to functional reasons for new financial systems
• Regulatory and financial pressures are a prime enterprise concern.
• Solvency II, IFRS compliance, and healthcare reform
• Low interest rates and sluggish economy amplify bottom line concerns
Financial systems tend to get minimal attention even though a core enabler
• New systems focus on policy admin, billing, distribution, underwriting and claims
• SMAC (Social media, Mobile, Analytics and Cloud) attract remaining attention
Modern financial systems essential to
• Meeting reporting and compliance mandates from regulators
• Working in a "big data" world with the latest analytic capabilities
• Engaging new markets and diversifying product lines to maintain profitability

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PC Claims Severity
Industry Faces Challenging Times
Investments
Regulation
Market Exits
Technological Advances
Competition
Life Insurance Ownership

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Decision-making processes and strategic focus changed
‒ Economic conditions limiting portfolio returns
‒ Competitiveness and market saturation challenging organic growth
‒ Cost structures seen as unsustainable, cost management critical
Costs and capital investments heavily scrutinized
‒ Structural changes: outsourcing, consolidation, acquisition, divestiture
‒ Process changes: LEAN, CI, Value Analysis, Process Optimization
‒ Technology: Legacy replacement, Decision and Process Automation
Automating insurance processes driven by
‒ Rapidly advancing technology
‒ Accelerated consumer adoption
Integrated service experience solutions drive
‒ Increased profitability
‒ Improved customer satisfaction
‒ Improved retention
Session OverviewDriving Foundational Changes

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With Increasing Technological and Operational Complexity
Broader Generational Diversity Influencing Service Methods
Surge in Social Media Channels
and Data Availability
Five Generations of Consumers, Large New Wave Coming
(% of TotalPopulation)
Increased Ethnic Diversity
Influencing Service Delivery
The Digital Generations
- powerful consumers

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Driving an Evolving Service Delivery Model
One Size Fits All
§ Same service for all
segments
§ Over invest in some, under
invest in others
§ One model to manage
across lines and customers
§ Differentiation created at
company level with brand or
channel vs. segment levels
§ Easier to match capabilities,
one target to work with
Individualized Service
§ Segmentation of needs and
value derived
§ Appropriate service
investment in each segment
§ More challenging with sets
of models to manage
§ Differentiation created at
segment levels driven by
service and economic value
§ Harder to replicate by the
competition, people based,
multiple targets

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Many Software Options and Needs, Budgets Flat to Down

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Service Systems and New Technology Get the Attention
System Deals – Flat to Down but Showing Improvement in 2013
• Many vendors have seen a decline in new deals since 2012
― Processing and document/content management have seen declines
― This despite increased variety of solutions and functional advances
• Despite these overall trends down, two areas have shown actual growth
― Distribution systems that help address multi-channel opportunities and needs
― Infrastructure and financials is the other category showing an uptick
• Fewer deals being cut with existing partners – openness to new vendors
― Breadth of solutions available across the technologies being leveraged
― Increased tendency to wrap legacy with rules engines and web front ends
― Data mastery solutions also key focus (warehousing, analytics, ETL)

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Survey Results Give Insight
The Nolan Company’s Executive Survey gives insight into priorities

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Survey Results Give Insight
Implementation Success faces many challenges

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Survey Comments Provide Depth
A Relevant Insight
“The ability to integrate the use of multiple data sources and types into decision-
making processes ranging from pricing to underwriting to servicing to claims is
essential in today’s competitive environment. Managing the recent dramatic increase
in data diversity is ideally accomplished using next-generation data management
tools, data warehouses and robust analytical tools.”
Takeaways relevant to financial systems:
• Need ability to handle multiple data sources and multiple data types
• Must reach across servicing / transactional systems
• Advanced data management and data warehousing integral
• Importance of analytical reporting tools useable by the business emphasized
Attempting to meet these needs with legacy financial systems increase
costs, complexity, implementation timeline, and the risks of failure.
• Realizing all benefits of a new processing system limited by financial system

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The Interface Challenge Alone Is Intimidating

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Plugging New Needs into Old Systems = Difficult, Costly
New Regulations
& Process Controls
Reorganize,Recast,
Restructures
Reporting &
Analysis Demands
NewPAS

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What to Look for When Considering New Financial System
Financial Reporting Accuracy and Reliability Core to Change
• Market Agility, Financial Accuracy and Regulatory Compliance requires
― Rapidly adaptable chart of accounts to allow expansion on a needs basis
― Transparency of processes with integrated process audit and automation
― Interoperability with other systems on a near plug-and-play basis
― Business defined capabilities and level of detail allowing dynamic adjustment
― Built in analytical functionality that can adjust level of drill-down and detail
― Straightforward reporting mechanisms that do not require specialized expertise
― Environmental simplicity: fit within the standards of today’s data centers
Survey Insight:
“Companies looking to gain competitive advantage must allocate financial and
human resources to replace aging legacy technologies, update skillsets, become
adept with data, and redesign outdated IT management practices.”

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Best of Class or Suite Solution?
Reality Leans in Favor of Best In Class
• Suite Solutions (ERP) are built for breadth of function and robustness
― They have to support a wide range of functions to covering multiple industries
― They must handle consistently high volumes of diverse transactions
― Typically built on the original conceptual frame of manufacturing systems
• Best in Class looks to serve a specific focus extremely well
― Typically focused on a particular related family of industries
― Narrow transaction breadth, looking for depth and functionality within industries
― Conceptual frame based on the specific focus of the solution versus a suite
• Often Cost of Integration pointed to for decision basis
― Absent concurrent retirement of legacy systems, interfaces are needed anyway
― Insurance industry development staff have become adept at interfacing
― Usually frame for interfacing exists already due to multiple disparate systems

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Lessons Learned
Realizing Benefits of Financial Systems Upgrade can be Challenging
• Often measured in agility, speed to adapt, simplification of reporting
― Usually minor reductions in systems costs as these are generally low cost
― Replacing existing workarounds (e.g., spreadsheets, manual tracking, manual
reports, duplicate reports) can be beneficial but difficult to measure the impact
• Preparing for the process is key
― Conduct a comprehensive scan, inventory, and roadmap of all opportunities
― Map successes against the roadmap, adjusting as needed
• Ask probing questions and push back on answers to ensure thoroughness
― What things can / should be fixed now without any system upgrades?
― What processes / practices need to change as part of the upgrade effort?
― What longer-term changes need to occur to realize the full value once the new
system is in place (people, process, and technology)?

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Lessons Learned (continued)
Scope Management and Project Governance is Critical to Success
• These efforts have a way of growing beyond the initial scope
― Starts with the replacement of GL and supporting management reporting
― Which begs the question about Chart of Accounts design and function
― Which leads to questions about level of detailed data stored in the GL
― Followed by questions around the sources of data and where it is stored
― Which leads to how this will impact source data feeder systems
― Followed by questions of replicating / replacing a data warehouse need … etc.
• These efforts can also be scoped too narrowly, delivering minimal value
― Limit to upgrading the GL system only to prevent obsolescence, no redesign
― Risk concerns result in replicating current setup with new technologies
― “Paving the cow path” fails to leverage the functional richness available

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Be Forewarned – Implementation Requires Conversion
Gartner: "83% of Data Migration Projects Fail...“
• Poor Project Planning
― Usually Addressed after the system pilot
― Handed off to the Support and Maintenance team
• Legacy Issues
― No documentation and lack of existing knowledge of old systems / interfaces
• Data Quality problems
― Unknown/never addressed
• Lack of Flexibility and Insufficient/Overexuberant Change Control
― PM Waterfall process not appropriate
― Changes happening after data mapping not integrated adequately
• Delay of Functional Testing and Data Validation/Auditing

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Overcome the Odds via Thorough Project Management
Establish and Follow a Well-communicated and Planned Process
• Continuous multifunctional stakeholder oversight and participation
― Ensure participation by leadership across key functions
― Broad project participation and awareness, not an “IS” or “Finance” only project
• Solid and realistic estimates of time and effort, no short cuts
― Usually addressed after the system pilot and handed off to maintenance team
― Focus on complexity not volume, fully address data gap and quality
• Thorough data validation plan
― Built up from a data model that fully supports all of the inventoried reports
• Closely managed specifications and data mapping
― Common repository for specifications and layered changes
― Impact reporting on each change
― Traceability between spec and test case validation reports

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Overcome the Odds Thorough Project Management
Ensure Disciplined and In-depth Testing and Implementation Plans
• Incorporation of multiple refresh / regression test cycles
― Careful sequencing of data manipulations and transformations
― Clearly documented and verifiable refresh process
― Reconciliation reports for post refresh regressions
• Clearly defined go-live strategy that modularizes risk
― Business operations plan for day 1 / week 1
― Audit process that includes history and lineage
• A data migration strategy fully vetted with cross-functional team of experts
― No documentation and lack of existing knowledge of old systems / interfaces
• Rigorous Data Governance practices and expertise
― Predetermined and communicated data rules, standards and policies
― Pre-established roles and responsibilities including on-going data governance