Strategies and Solutions to Create Accurate, High Quality Predictive Model

Results for Underwriting

Jeff Fluke, Managing Director, Underwriting ServicesIngenix Consulting

Agenda

• National Health Reform and Predicting Risk • Predictive Modeling Basics• Lessons Learned• New Business Focus

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Individual and Small Group–

Mid Market and Large Group• Renewal Focus

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Individual and Small Group–

Mid Market and Large Group• Integration Options • Predictive Modeling and Actuarial uses• Benefits• ROI

Risk Evaluation and Rating

• National Health Care Reform and Predicting Risk

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New policy requirements, new restrictions, and new regulations will require health plans to be flexible, adaptable, and fully understand their current and possible future risk.

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A change to the health care system means more opportunities for well prepared insurance carriers to dominate the market. In order to secure financial success in the changing environment, insurance carriers need to be prepared and the status quo may not be enough.

Risk Evaluation and Rating

• National Health Care Reform and Predicting Risk

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It is critically important that we distinguish between a carrier’s understanding of an individual’s or group’s risk level versus the use of that risk knowledge in rating (i.e. accepting or rejecting an individual application or small group for coverage or the setting of differentiated prices/rates).

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While all or some aspects of the latter may be restricted in the future, the need for the former will never be eliminated.

Risk Evaluation and Rating

• National Health Care Reform and Predicting Risk

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Change is imminent and essential.

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Health care plans know that health reform will bring big changes to the way one conducts business.

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The best way to prepare is to put measures and tools in place that are both flexible and strong enough to handle anything that comes one’s way.

Predicting

“Prediction is very difficult, especially about the future.”

- Neils Bohr

Predictive Modeling

• Identifying risk underlies all pricing and risk assessment methods and models

• Predictive modeling:

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Goes beyond age, gender, area, industry and other ingrained risk classification criteria for new business and renewal practices

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Effectively introduces individual health dynamics

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Can supplement/replace risk assessment information from medical questionnaires and historical experience

Why use Predictive Modeling in Underwriting

• Goal: set the right rate (improve accuracy)–

Determine underlying health risk of population–

Retain and attract good business• Goal: set the right rate (improve consistency)

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Match premium revenue with expected costs – promote stability and profit (consistency)

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Improve market/employer perception of ability to forecast and manage costs

• Goal: increase productivity (improve efficiency)–

Value-added information produced on a systematic basis – supports automation and standardization

• Goal: increase value to the organization–

Understand risk and share information with other parts of company

• Value proposition–

Better information on health risk for individuals and groups can enhance the underwriting process

In Other Words…

• Predictive modeling provides the opportunity to:

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Improve risk classification knowledge

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Explain trends and deviations

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Drive health plan performance

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Drive efficiencies in process and staffing

Improve accuracy, consistency, and efficiency

Lessons Learned

• Focus on 4 key questions

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How to use for new business?

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How to use for renewal business?

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How to blend the transition in pricing from new to renewal?

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How to integrate with other risk assessment techniques?

• Its not plug and play... using any PM tool/process in pricing models requires detailed planning, modeling and understanding of implications and transitions

• One size does not fit all... different segments of business (individual, regulated small group, mid size, large group) require different implementation approaches

Using Predictive Modeling New Business Underwriting – Key Considerations

• Individual–

Depth and scope in the drill down of data is critical

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The cost of a condition, and complications

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The likelihood of recurrence and/or complication

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Will prior expenses continue

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Co-morbidities

• Small Groups (2 – 50)–

In states where a health status adjustment is allowed

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Increased accuracy – area of greatest benefit

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Automate moving from a risk score to a rating action

Using Predictive Modeling New Business - Individual and Small Group

• Begin with health questionnaires and self disclosure

• Establish debit or estimated known claim basis

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Can incorporate predictive modeling in this process

• Identify drug and disease interactions and co-morbidities

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Difficult to quantify; need Predictive Modeling tools or experienced underwriters

• Automated process – speed to market

• Strong business rules needed to be most effective

• Requires robust reporting capabilities

Using Predictive Modeling New Business - Individual and Small Group Change the Playing Field

• Pharmacy profiling opportunity

• Up to five-year historical profile of pharmaceutical usage

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Detailed prescription history, dosage, quantity, number of refills, timelines, and indicator of compliance

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List of prescribing physicians and specialty

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Potential diagnoses

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Predictive modeling – 12 month healthcare cost estimate

• Delivered online – to your desktop in minutes

• Requires member authorization for HIPAA compliance

Using Predictive Modeling New Business Underwriting – Key Considerations

• Mid Market–

Supplement with existing risk assessment techniques–

Difficult segment to price historically–

Some companies moving to health applications and pharmacy profiling to better understand risk

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Aid in overall base rate and factor setting

• Large Groups–

PM activities for early clinical identification–

PM run of prior carriers claim experience to degree detailed data obtained

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If large claimants provided, PM could be used to gather additional information

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Aid in overall base rate and factor setting

Predictive Modeling for Renewals

• Typically have more, credible information for renewal pricing

• You should know more about your in force group than your competitor does about that group

• How to supplement predictive modeling into renewal risk assessment

• Linking your new business methodology to your renewal methodology is critical to consistent pricing

Using Predictive Modeling Renewal Business Underwriting – Key Considerations

• Individual–

Can be used for specific member level pricing

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Used for block of business analysis (product, region, risk tier, trends, etc.)

• Small Groups (2 – 50)–

Improve accuracy of rate setting

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Improve efficiency of rate setting

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Better match premium to expected risk

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Automate moving from a risk score to a rating action

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Link with new sales approaches critical to avoid discontinuity in renewal pricing

Concerns with Today’s Common Renewal Approaches

• Accuracy–

Loss ratio-based projections even though all agree the loss ratio of a small group is not credible

• Consistency–

Estimates for ongoing large claims are rarely consistent between underwriters

• Efficiency–

Manual process for determining diagnosis, prognosis, and projected ongoing amount for each large claimant

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Underwriters “touch” many renewals regardless of group size

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Underwriter must access multiple systems to gather various data components

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Hard copy reports and manual input

Predictive Modeling addresses each of these issues

Using Predictive Modeling Renewal Business Underwriting – Key Considerations

• Mid Market

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Blended with historic claims to increase accuracy

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More credibility to the predicted risk vs. prior history

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Credibility studies indicate ranges of mix from 50% to 75% for PM portion of credibility blend applied to manual rate

• Large Groups

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Some blending with historic claims can enhance accuracy

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Ability to blend PM score on those actively enrolled members and manual rate drivers on those new enrollees

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Opportunity to determine risk drivers – enhance account management function

Integration Options Transition over time

• Companies can easily transition the use of predictive modeling over time–

Added piece of data (macro and micro level)Confirm results from existing process/trends

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Support appealsEspecially where predicted risk is less than experience

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Automated large claim reviewsEnhanced ability to identify emerging claimsEase of researching groups and individuals

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Part of rating formulaRevised credibility table

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Integrate into rating processVarious levels of automation

Predictive Modeling Mapping Risk Score to Rating Action

Group

Block of Business

• Relative risk score .95 .98 • A/S factor .90 1.03

Step 1. Normalize the group risk score to the block risk score(group rrs / block rrs)(.95 / .98 = .97)

Step 2. Normalize the group A/S factor to the block A/S factor(group AS factor / block AS factor)(.90 / 1.03 = .87)

Step 3. Develop the adjusted group risk score(#1 / #2)(.97 / .87 = 1.11)

Adjusted group risk score: 11% higher than the block of business

Underwriting / Actuarial Additional Uses

• Analyze and measure risk for blocks of business–

Area, broker, product, group size, duration, etc.

• Watch trend/risk over time for book of business–

Proactive with future risk score

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Increasing/decreasing – ability to change rating before impacting financial results

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Selection issues

• Monitor marketing and sales activities• Integration with current underwriting practices

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Predictive Modeling results must complement existing information, including prior experience, credibility assumptions, and other adjusters

Predictive Modeling and Actuarial Uses

• Reserving–

Ability to evolve the reserving process to link rolling predictive values to backstop the trended pmpm claim amounts of recent months

• Trend–

Similar concept to reserving evolution

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Ability to monitor trends in blocks of business over time both historical and projections

• Product–

Ability to analyze product design potential selection and proactively adjust pricing based on projected risk

Benefits of Predictive Modeling in Underwriting

• Enhance the actuarial and underwriting process–

Increase accuracy of forecasts – for new and existing groups–

Improve market perception of ability to forecast and manage costs

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Improve efficiency and productivity of rating process• Multiple risk characteristics influence future costs

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Emerging claims, completed claims, turnover, etc.• Monitor high utilization – group and members

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Were the conditions present on the applications - was there potential fraud?

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Any potential changes in process necessary?–

Share information with other parts of organization• Consistency between new business and renewal pricing

Benefits of Predictive Modeling in Underwriting

• Potentially automate some parts of your business

• Speed to market - with accuracy

• Streamline group renewal underwriting

• Automate large claim review process

• Improved data collection and case preparation

• More stable underwriting margins

• Automate reporting capabilities

• Improved communications with groups/agents

• Improved accuracy, consistency, and efficiency

Return on Investment Improve Accuracy, Efficiency, and Effectiveness

• Automate adjusted risk scores• Credibility assumptions in order to automate rate action• Automate large claim review process• Readily available group reporting/profiles – all with an eye

toward helping you understand the risk–

Distribution of costs – by area, product, agent, group size, etc.–

Historic information on costs, risk scores, large claims, rate action, etc.

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Turnover analysis• Portfolio analysis tool

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Allows underwriters/actuaries to track the change in risk within a book of business

• Improved clinical programs – proactive • Enhance employer retention rates; thanks to lowered

operating costs

Return on Investment Predictive Modeling Systems

• Complete, reliable and actionable data • User-friendly data access and presentation • Cost effective

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Easily integrated into current processes and workflow solutions

• Flexible implementation –

Multiple deployment options based on organizational need–

Can be as flexible as needed or “right out of the box”• Right price your business – accurately reflect and

maximize revenue on poorer risks and retain more of the better risks–

Improved risk selection• Solid risk predictor foundation

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Independent studies prove accuracy

Predictive Modeling is Very Powerful Information

Questions?

• Jeff FlukeManaging Director, Underwriting ServicesIngenix ConsultingJeff.Fluke@IngenixConsulting.com952-942-3254