Predictive Analytics and the Risk Function

Transcription

1 Predictive Analytics and the Risk Function Using Your Data as a Crystal Ball Frank Fiorille Sr Director of Risk Management Paychex

2 Paychex Payroll - HR - Retirement - Insurance Market Cap: $21 Billion More than 600,000 clients One out of every 12 private sector employees in the United States is paid by Paychex $3 Billion Annual Revenue in FY16

3 Risk Paychex Credit Preventing returns of over $320 billion of Risk exposure last year on over 27 million ACH transactions. Collections Minimizing actual annual write-offs of under $2.5 million, less than 1% of exposure. Financial Services AR Write-Offs less than one tenth of a percent of sales Compliance Navigating the complex regulatory environment Operating Risk 94% Penalty Abatement Data Science & Predictive Analytics Over 30 predictive algorithms in circulation P

4 Big Data: What does it mean? Every day, the world creates 2.5 quintillion bytes of data.(18 zeros) That s 100 quadrillion new phone numbers. (17 zeros) There are billion people on Earth. That means, every day, we add the equivalent of 14,035,088 new earths worth of phone numbers!! 2 trillion bytes represent clients employees wage data.(12 zeros)

5 Data Governance A strong data governance infrastructure creates long-term, sustainable value through improved data quality. The creation of Data Definitions, Owners, Stewards and Controls. Commitment to Data Governance as a means, not an ends. Data Governance TECHNOLOGY

6 How does Risk Utilize Big Data? Descriptive Predictive Prescriptive Analytics E.T.L. Big Data

7 Risk Big Data Users Communication Statistics Expertise Paychex/ Business Expertise Database & ETL Development & Management Data Paychex

8 Uncovering Signals Discovering and investigating data points and trends within your data that are representative or predictive of larger patterns.

9 Signal Example Investigating variability in application load durations. Initially performed clustering to form data defined segments. Comparing clusters uncovered an unexpected variable driving high load times in one of the clusters. 9

10 Risk Algorithms Predictive Model Ecosystem Risk Portfolio Strategy Portfolio Operations Portfolio Sales Portfolio Portfolio Credit Model Identifies clients likely to return within the next 3 months, for controllable reasons. Sales Territory & Mapping Predicts number of units and the inherent opportunity per zip code Core Retention Models Models predict retention, revenue and price sensitivity. Retirement Upsell Identifies Core clients most likely to purchase 401(k). AR 60 Days Past Due Scores past due invoices based on probability of turning 60 days past due. Employee Retention Models for assistance in employee retention with Human Resources Major Market Retention MMS client retention model targeting controllable losses. Agency Upsell Models to predict likely to purchase Health and Benefits or Workers Comp. Collections Model identifies which accounts are most likely to liquidate within 90 days. Client & CPA Referral Identifies current clients and CPAs most likely to produce a referral lead. ASO Retention Predicts which ASO clients are likely to churn. HR Solutions Upsell Core upsell model predicting clients best suited for ASO or PEO. Prospect Modeling Prioritize NSS call queues by likelihood for booking an appointment. 401(K) Retention 401(k) retention model for controllable losses for use in discount decisions. Time & Attendance Core cross-sell model for most likely to purchase time and attendance solutions. Client Segmentation Identifies target client profiles for strategic targeting. ASO Discount Sensitivity Predicts which ASO clients sensitivity to changes in discounting. Next Best Offer Determine which product a new Core client is most likely to purchase next. Sure Payroll Retention Sure Payroll churn model for potential use in business model fit. Retirement Conversion Modeling to determine client likelihood to convert to a Paychex 401(k) plan. Product Road Map Modeling of clients at first load to define their strategic growth of products. 10

11 Sales Upsell and Cross-Sell Salesforce.com Model scores for retention and upsell, client referrals, 401(k), coemployment & Time and Attendance are available to our reps in the field.. Direct Sales Calls monthly lists generated by predictive model scores. Targets Sales models are used to set goals, define targeted strategies and help business units deliver. Service Assists Operations generate referral leads by suggesting the clients ready for new products. Marketing Monthly campaigns for high scoring HR Solutions, Insurance and 401(k) clients. 11

12 Operations Retention & Discounting The Models Retention models for Core, MMS, 401(k) and ASO and Price Sensitivity models for Core and ASO Discounting Discount decisions are made using model scores to increase retention. Payroll Support the field with Retention, Price Sensitivity and Revenue predictions on clients. Client Retention The Client Retention Team works clients most likely to leave, proactively retaining at risk clients

13 Discount Decision Engine Predictive algorithms measuring price elasticity and retention probabilities prescribe recommendations for systematic client discount reductions. New Client Discount Established Client Discount

14 Strategy & Risk Management Protecting and Planning Collections The bottom 50% of MARCO scores are referred to an agency. Billing MARIA filters out likely payers to make invoice collections more efficient. Mapping Helping Sales tap into developing markets and identifying opportunities for sales growth. Referrals Providing Sales with the ability to focus on clients and CPA s more likely to refer new business. Retention Equipping Senior Leadership with predictive intelligence to improve employee turnover. 05 Credit Knowing the probability of a return helps Portfolio Management mitigate Risk. 14

15 Modeling Credit Risk Building algorithms that analyze credit risk on a transactional level in real time. Leverage models to focus risk efforts on the highest cost areas, improving operational efficiency while creating value.

16 Collections Algorithms As 68,000 receivables roll past due annually, our model filters out clients that are likely to pay without intervention, allowing our collections team to optimize staffing and workload.

17 Product Recommendation Algorithms Equipping Marketing and Online Advertising with the means to produce smarter, targeted strategies. Using client product purchases in conjunction with job and wage data, can we better understand how a small business grows?

18 Other Industry Recommendation Engines

19 Deployments that Optimize Value

20 Forecasting

21 Paychex IHS Small Business Jobs Index Making Paychex an integral part of the discussion on the economic situation! The Good News on Small-Business Hiring Trends Data released this week by both Intuit and Paychex IHS show a strong hiring trend for small businesses. - Fox Small Business Center Regional Performance In Washington state, small businesses are adding jobs faster than any other state in the country, according to a report from Paychex and IHS. It's also the state where minimum wage, at $9.32 per hour, is the highest. - CNN Money San Francisco's small businesses are growing faster than those of any other big city or the nation as a whole, according to new data from payroll-processor Paychex and research firm IHS. -The Huffington Post - Business National Trend Trends with BLS

22 Positive Press Establishing yourself as an information leader creates opportunities. Building our data expertise has led to consultations with the Washington Post, Wall Street Journal, Inc. and more.

23 Any questions?