ADVANCING YOUR ORGANIZATION WITH ANALYTICS Clyde Analytics software is designed to help you unleash analytics innovation within your organization and accelerate adoption of analytics throughout the enterprise. Our solution, combined with your team’s capabilities, will help you drive performance improvement across the company. For more information on Clyde and our solutions, visit clyde-analytics.com
ADVANCING YOUR ORGANIZATION WITH ANALYTICS The efficient and effective development, management, and deployment of predictive models can be used across the insurance enterprise to drive better business results. Technology, combined with your team’s capabilities, can help you develop insights through analytics that can be transformed into actions that have significant business value. One of the important aspects of enterprise analytics is ensuring it’s not a once-and-done process, but can be sustained for change over time. Technology and data advances have created excellent opportunities to generate new insights through analytics. But technology alone is not the answer – it’s important to select the right solution and deploy it in a way that can be used throughout the enterprise. Based on our experience, there are key principles to ensuring analytics is used most effectively within the insurance organization: •
There is no silver bullet. A continuous improvement loop is critical in today’s environment. Innovation comes through iteration, and ensuring that you have options and choices is critical to achieving the best results.
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Collaboration is the new competitive advantage. Linkages within and between technical and business users are critically important. It’s all about creating opportunities to collaborate, sharing output and deploying for lasting results.
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Humans are critical to the process. Software alone doesn’t solve the problems. Insurance data and analytics have unique nuances, requiring people to drive decision-making.
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Have a plan for implementation before you start. This is often addressed after the solution is in place, but it is critical for sustainability.
We started Clyde Analytics because we believed there was a better way to maximize the potential of analytics within insurance carriers. Our tools are designed to help you unleash analytics innovation within your organization and accelerate adoption of analytics throughout the enterprise.
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For more information on Clyde’s insurance analytics software, contact us at (888) 816-8851 or info@clyde-analytics.com. Visit our web site at clyde-analytics.com.
OUR APPROACH We have deep experience in P&C insurance. Clyde’s principals have spent their whole professional careers in P&C insurance. We partner with experts in the insurance industry. We focus specifically on partners with deep roots in data & predictive analytics. We have a clear idea of the challenges and opportunities. We appreciate what that means to modelers, business staff and technologists. We believe in the power of technology, backed by people. As a young company, we have an advantage in our ability to leverage technology and data advances, using a mix of modern & emerging technologies that make your team stronger. We understand that attaining more production is a priority. Our focus is on helping you include more staff in the process and answer more business problems via analytics. We know you need to achieve better results. Our software helps you use new science, algorithms, and ensembles in innovative ways. We continue to add technical functionality based on our own research and customer input. We appreciate your need for speed. Our software is designed to help you increase the speed of modeling, decisions, and implementations.
OUR CUSTOMER RELATIONSHIPS For us, the only perspective that counts is yours. We are continuously engaged in dialogue about our customers’ needs, and incorporate that feedback into our solutions. Our customers benefit from having a voice and seeing their feedback quickly transformed into development plans and deliverables. We want to delight customers with our approach, to be transparent, and we’re committed to your success. We only win when you are successful.
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For more information on Clyde’s insurance analytics software, contact us at (888) 816-8851 or info@clyde-analytics.com. Visit our web site at clyde-analytics.com.
OUR SOFTWARE •
Developed for insurance needs and workflow, an intuitive design gets users productive quickly.
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Empowers internal teams and is easily integrated into existing processes.
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Extensive library of algorithms.
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Easy to implement – no infrastructure or set up challenges.
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Cloud-based model feeds enterprise collaboration.
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Implementation-ready output accelerates deployment.
FOCUS ON TECHNOLOGY
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Analytical platform with GLM, non-parametric methods, text mining, and rate factor optimization in one application.
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Balance between ease of use (modern, web-based, point and click with gentle learning curve), user flexibility and self-service functionality.
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Application available as a SaaS model which provides a unifying framework for model development, sharing/reviewing, and documentation.
For more information on Clyde’s insurance analytics software, contact us at (888) 816-8851 or info@clyde-analytics.com. Visit our web site at clyde-analytics.com.
SOLUTION INFRASTRUCTURE Client user interfaces enable users to upload data, perform data manipulation, set model fitting parameters, and review results from a web browser. We use custom code to deliver an easy-to-use GUI, web-based, pointand-click experience. This provides a unifying framework to build, evaluate and share models and communicates with analytical processes to pass arguments and receive results.
Analytical processor is the application server that hosts Clyde’s data manipulation and model fitting procedures (the algorithm library). It receives arguments from the client interface, and uses custom code to perform data manipulation and fit models. Results are posted back to the web browser interface for display to users. Data storage is handled by Clyde data servers that store customer’s data and model results. Utilization of instance storage and elastic block storage occurs via Amazon Cloud. Data upload/ download is facilitated from/to client interface with data access by the Analytics Processor, like a local file. Score service is a scoring engine that stores the model description, enabling models developed by the Clyde application to be implemented via web services. It receives an item to score in JSON file from an external calling application and returns a JSON file with model fitted value or other desired output and error status.
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For more information on Clyde’s insurance analytics software, contact us at (888) 816-8851 or info@clyde-analytics.com. Visit our web site at clyde-analytics.com.
SOLUTION BENEFITS
You’re in control. Our solution is specifically designed to empower your team. Routine, frequently performed tasks are well-supported in a single, easy-to-use toolbox and can be easily integrated into your processes. And, if a user is less experienced in insurance modeling, the software is intuitive, enabling him to get up to speed quickly. You’ll get fast results. It’s easy to use, easy to get started, and it works fast. The tool will help you get the answers you need, including exporting data results and graphs quickly. It enables you to collaborate. Everything is easily accessible and shareable -- in the cloud. Output is delivered in ways that make it easy to share with the business. We’re in partnership with you. We listen to feedback and move quickly to deliver. Our clients are often very excited about our ability to address new requirements quickly through our rapid development cycle.
Our product development focuses on customer business problems:
90%
OF CUSTOMERS HAVE PROVIDED FEEDBACK
WHICH IS INCORPORATED INTO OUR SOLUTION WITHIN 60 DAYS.
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For more information on Clyde’s insurance analytics software, contact us at (888) 816-8851 or info@clyde-analytics.com. Visit our web site at clyde-analytics.com.
HOW CARRIERS USE OUR SOFTWARE Today, most customer initiatives are focused on pricing. There are opportunities for carriers to get increasingly sophisticated and to move up the analytics value chain, from rate plan development to rate factor optimization. There are also opportunities to advance operational effectiveness using analytics for underwriting analysis, portfolio and distribution management, marketing and claims.
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For more information on Clyde’s insurance analytics software, contact us at (888) 816-8851 or info@clyde-analytics.com. Visit our web site at clyde-analytics.com.
APPLICATIONS FOR OUR SOFTWARE MODEL DEVELOPMENT
Developing new models or extending existing ones Customer profitability/value: segmentation & scoring • rating class plans • underwriting: real-time (new) & batch (renewals) • target marketing and campaign/contact management Portfolio management / trend analysis • portfolio score: portfolio-level metric as leading indicator of profitability and growth (such as quality of business produced, non-renewed, quoted but not bound) • common metric across an organization & all lines of business • renewal portfolio optimization • competitive positioning insights Distribution management • performance measurement, including expected profitability and growth trends (make up for lack of credibility of data) • margin-driven compensation plans: tiered commission, profit sharing based on quality of production Operational efficiency • marketing: response models, cross/up-sell, policy longevity • underwriting: external report/data ordering optimization (MVR, home inspections) • claims: triage, fraud, subrogation/litigation optimization
MODEL VALIDATION
Assess different methods and data GLM testing (same variables, additional variables) Residual analysis of existing models Certification of results
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For more information on Clyde’s insurance analytics software, contact us at (888) 816-8851 or info@clyde-analytics.com. Visit our web site at clyde-analytics.com.
OUR TECHNICAL APPROACH
We believe the key to success lies in using multiple methods – including GLM and non-parametric methods – to produce better technical results. Our approach – based on our direct experience – takes into account: GLMs are good at finding main effects signal, but miss higher order, local interactions. The higher order interactions have explanatory power on a subset of the data (local interactions). The models predict better on these slices of the data. The deviation is typically substantial (say 20% or more) on 50% of the data, so our view is this is not something to ignore. The non-linear methods are simply an extension of the technical toolset. We have found decision trees are useful not only for feature detection (i.e., finding 2 or 3 way interactions to potentially plug back into the GLM), but the nodes of the decision tree (segmentation) can be used as a categorical predictor directly in the GLM. This is the same for boosted trees, (scoring) using the bins of the fitted value as a predictor into the GLM. We have tuned our algorithms for insurance data. We use a split objective function that is more resilient to noise in insurance data. The standard algorithm uses the R-squared as the split objective, which implicitly assumes the data is normally distributed. Insurance data is not. In addition, we introduce randomness in the search process to explore more of the solution space (mitigate greedy nature). We believe our approach will become standard practice. These methods can be used across coverage, risk, policy and customer data and works well for loss cost (frequency, severity or pure premium), demand models (binary response), and operational models such as claims triage, litigation models, inspection spend optimization, marketing and response models, etc.
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For more information on Clyde’s insurance analytics software, contact us at (888) 816-8851 or info@clyde-analytics.com. Visit our web site at clyde-analytics.com.
Leveraging superior underlying models is a better starting place for any optimization process. The optimization process is sensitive to the strength of the underlying cost models. Rating factor optimization is a difficult and complex problem. Gradient-based methods are not well suited for some of the challenges. The error surface has multiple local minimum points and exhibits regions which are relatively flat. The objective function takes a long time to compute and is highly dimensional (i.e., 20, 30 or 50 factors optimized at the same time).
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We introduce stochastic optimization methods to get past these difficulties. These methods add substantial value. Running times for stochastic optimization methods are much faster than gradient based methods (increases linear versus quadratic with number of parameters). Gradient methods either take very long or fail to converge in these instances.
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We allow for both equality and inequality constraints. Trying to enforce more than one equality constraint for rating factor optimization presents challenges (i.e., it is difficult to have 2 equality constraints satisfied at the same time). By introducing inequality constraints, it provides a lot more flexibility.
For more information on Clyde’s insurance analytics software, contact us at (888) 816-8851 or info@clyde-analytics.com. Visit our web site at clyde-analytics.com.
PROVEN IMPLEMENTATION PROCESS 1. PREP DATA
What data do you have? What data do you need?
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Produce a repeatable data prep process to make data and results readily accessible to users.
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Refresh data periodically, i.e., monthly for monitoring and quarterly for modeling.
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Provide readily available connections to external data sources within our application.
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Provide transactional data batch for policies, claims, quotes, and add incremental inforce files as necessary.
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Include any external data in the file or append later.
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Perform high-level ETL within application: upload, join, aggregate tables.
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Interrogate and prep data variables: Produce and revise bins for variables, create derived fields or custom segments based on existing information, turn variables on/off for model training.
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Filter the data to analyze specific questions (i.e., filter on one or multiple variables available in the data).
For more information on Clyde’s insurance analytics software, contact us at (888) 816-8851 or info@clyde-analytics.com. Visit our web site at clyde-analytics.com.
PROVEN IMPLEMENTATION PROCESS
2. TRACK RESULTS What do you want to know? •
Derive performance metrics to analyze company data within the application.
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Likely to be those you analyze today or want to analyze. Our solution makes them readily available through custom dashboards.
An example of general analysis, monitoring and reporting
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Provide automated performance measurement and monitoring.
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Analyze mix of business over time, by any variable, or any customdefined segments, such as: •
Historical loss experience – observed claims frequency, claims severity, loss cost, loss ratio, CAT loads, and any combination of cost/premium.
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Include multiple versions of premium (i.e., historical, on-level, proposed rate change) and claims (i.e., uncapped, multiple capping levels, CAT loads, etc.).
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Customer dislocation of proposed rate changes (ratio of proposed to current).
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Customer retention, response, and conversion rates (if quote information available).
For more information on Clyde’s insurance analytics software, contact us at (888) 816-8851 or info@clyde-analytics.com. Visit our web site at clyde-analytics.com.
PROVEN IMPLEMENTATION PROCESS
3. ANALYZE DATA
What business questions are you answering?
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Enhance internal capabilities to build and implement models.
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Get greater productivity from team, find leverage in new/junior staff, bridge gaps between technical and business audiences.
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Drive technical innovation – statistical, machine learning, text mining, unsupervised methods.
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Perform analysis on any user-defined analytical objective (i.e., frequency, severity, loss cost, loss ratio, retention, conversion, inspection ordering, claims triage, etc.).
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Utilize generalized linear models to capture linear signal in data, derive relativities to compare to existing class plans.
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Employ tree-based methods to identify non-linear, local interactions in the data.
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Easily use multiple methods together, outputs from one model as inputs to another model to improve model estimates.
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Optimize rate factors to meet user-defined constraints and based on expected cost and demand (i.e., retention/conversion).
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Easily deploy results, applications include performance monitoring of production/portfolio, distribution management, underwriting, pricing, and claims analytics.
For more information on Clyde’s insurance analytics software, contact us at (888) 816-8851 or info@clyde-analytics.com. Visit our web site at clyde-analytics.com.
PROVEN IMPLEMENTATION PROCESS
4. TAKE ACTION
What actions will you take?
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Explore and deploy data insights & model results via real-time & batch processing and reports.
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Enable collaboration within your organization – share data, model settings, model results, and reports.
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Use a single source to promote process consistency, documentation, & review.
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Build dashboards to monitor business & frequent questions.
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Export data, including derived variables and model estimates via .csv, as well as any graphs and data tables available in Clyde (.csv, .jpeg, or .pdf).
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Facilitate batch scoring within the Clyde app – score/rate any data set on a select model in minutes (i.e., used for holdout validation, onleveling, etc.).
For more information on Clyde’s insurance analytics software, contact us at (888) 816-8851 or info@clyde-analytics.com. Visit our web site at clyde-analytics.com.