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Process Mining for the Insurance Sector

Process Mining for the Insurance Sector. ABOUT CELONIS. Celonis is an innovative, award-winning software company and the market leader for Process Mining. We make our customers more successful By improving every process throughout their organizations.

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Process Mining for the Insurance Sector

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  1. Process Mining for the Insurance Sector

  2. ABOUT CELONIS Celonis is an innovative, award-winning software company and the market leader for Process Mining. • We make our customers more successful By improving every process throughout their organizations • We work with leading customers in the world40% of Fortune 100 companies are already Celonis customers • Among fastest growing software companies in the world 4.000% over the last 4 years, 300% yoy • Backed by world class investors Accel & 83 North/ Greylock(Facebook, Dropbox, Spotify, Slack, AirBnB, LinkedIn)

  3. SELECTED CUSTOMERS Considerable experience in the FSI sector User & USAGE statistics More than 350 satisfied customers in more than 15 industries 100,000+ Users 350+enterprise customers 15+ Industries > 1 bn Activities at Once 68 Different Process Types Connected 70+ ERPs Largest Customer Landscape 30+ TB Largest Customer Installation 70+ Partners 25 Countries

  4. Do you know what really happens in your processes?

  5. How does process mining work? AI-powered root cause analysis & improvement Visualization of the actual processes EVENT LOG 2016-12-01 Create purchase order #1234 2016-06-23 Start production #5678 2016-07-14 Receive payment #1234 2016-07-14 SEND EMAIL #9012 5

  6. GET MAXIMUM TRANSPARENCY AND EFFICIENCY FOR YOUR Insurance PROCESS. Process Mining …is a SMART big data technology that analyzes and advises you ON HOW TO IMPROVE your PROCESSES based on data GENERATED IN your ORGANISATION – IN REAL TIME.

  7. OVERVIEW HOW IT WORKS ROI CALCULATION IMPACT OF PROCESS MINING ON THE INSURANCE PROCESS 100% +30% -25% +37% SAVE COSTS INCREASE SPEED BOOST EFFICIENCY ENSURE QUALITY Uncover hidden inefficiencies, deviations and bottlenecks to reduce process cost by 25% Using the fastest process paths and targeted optimization speeds up throughput times by up to 37% Improved automation and e-business rates, as well as avoiding manual rework increases efficiency by over 30% High precision in planning and execution, fewer incidents and clear responsibilities increases customer satisfaction significantly.

  8. OVERVIEW HOW IT WORKS ROI CALCULATION HOW IT WORKS EXAMPLE STEP1 STEP 2 STEP 3 PROCESS DISCOVERY & KPIs Find out how your process is executed in reality. Cycle times Automation rates Identify and eliminate weak spots. Use insights proactively to prioritize actions leading to process improvement. Benchmark INTELLIGENT ROOT CAUSE ANALYSES Find your „happy path“ and ensure continuous process efficiency, compliance, and quality. Process Automation Manual rework Throughput Time

  9. OVERVIEW HOW IT WORKS ROI CALCULATION Company Vodafone Plc “In addition to the increase in perfect purchase orders to 85%, time to market improved by 20%” Industry TELECOMMUNICATIONS Employees 14,000 EMPLOYEES Israel Exposito, Vodafone Global Process Lead for Process Mining Processes PURCHASE-TO-PAY ACCOUNTING Watch the Video Read Story

  10. OVERVIEW HOW IT WORKS ROI CALCULATION EXP PRODUCTIVE POV: 4.2 bnPOs: 143,062 POI: 2.1 m 1.5 m € Avoid Manual Payment Blocks 91k € 7.4 m € Reduce redundant process steps Slim down process variants Archive Claim File Create Claim File Verify Insurance coverage Approve Repair Processing Scan Invoice Allocate Invoice Book Invoice 280k € 3 Days Increase of Automation Rate 210 k € Reduce Rework Reduce of Manual Rework

  11. How often does rework elongate the throughput time of the whole claims process? ANALYSIS OVERVIEW HOW IT WORKS ROI CALCULATION With the Celonis Process Visualization it is easy to identify, that it takes an average of 22 days from the approval of repair processing to the scanning of an invoice. In 17,379 cases a claim is updated with new information , that adds 9 total days to the throughput time of this process. In a deep dive analyses we were able to detect the root causes for that and derived measures to reduce this rework by 35%. MEASURES & POTENTIALS OVERALL POTENTIAL RESULTS: Additional time with update: 9 days # of updated cases: 17,379 Improvement potential: 35 % SAVINGS: 9 days * 0,35 = 3 days Please note: all screenshots used are merely exemplary and have not been taken from real customer data. Hence, they do not correspond with the calculations made in this business case. 3 Days SAVED

  12. How to increase process efficiency by comparing the process variants of different offices? ANALYSIS OVERVIEW HOW IT WORKS ROI CALCULATION MEASURES & POTENTIALS The whole claim process should only take 50 days or less. A deep dive at different offices within the Shared Service Center, which has a considerably weak slow claims rate, uncovers an avg. throughput time (TPT) of 73 days at the Miami office. However the Detroit office has already reached the aim with an avg. of 48 days. A Benchmark comparison identifies that a claims adjuster was assigned in 11% of all cases of the Detroit Office, but in 53% cases in the Miami Office. This turned out to be the main reason for Mimi lagging in it´s performance. This finding helped to decrease the avg. TPT by 5 days for the Miami office. OVERALL POTENTIAL RESULTS: Providing alternative transportation: 100€/day Reduction potential: 5 days # of affected claims cases: 14,825 SAVINGS: 100€ * 5 days * 14,825 = 7,412,500 €/Year Please note: all screenshots used are merely exemplary and have not been taken from real customer data. Hence, they do not correspond with the calculations made in this business case. 7.4 m € SAVINGS

  13. How to avoid manual rework activities? ANALYSIS OVERVIEW HOW IT WORKS ROI CALCULATION MEASURES & POTENTIALS With Celonis we identified a high number of rejections (32%) within the low amount group (claims up to 100€). In 64% of these cases a claims adjuster was involved in the decision. By identifying these cases, we were able to derived more specific directives to ensure that the bulk of those cases could be rejected without an assignment of a claims adjuster. The assignment rate could therefore be decreased to 20%. OVERALL POTENTIAL RESULTS: # of cases per year: 24,012% of cases with claim adjuster: 64% Avg. effort per case: 30 min New rate of claim adjuster use: 20% BEFORE: (24,012 * 0,64) *30 min = 7,684 h/Year SAVINGS: 7,684h – (24,012 * 0,2) *30 min = 5,283 h/Year = 3 FTE = 210,000€ 1 FTE = 5 Days/Week * 8h * (52-5) Weeks/Year = 1880 Hours/Year = 70.000€ Please note: all screenshots used are merely exemplary and have not been taken from real customer data. Hence, they do not correspond with the calculations made in this business case. 210k € SAVINGS

  14. ANALYSIS OVERVIEW HOW IT WORKS ROI CALCULATION MEASURES & POTENTIALS With Celonis we identified that in 10,139 cases (13%) the claim files were reopened after they were archived. This significantly increases needless manual rework. By identifying the root causes it could be proofed that they could have been avoided by clear guidelines at preliminary stages. We therefore were able to reduce this process step by 95%. How to identify and eliminate redundant process steps? OVERALL POTENTIAL RESULTS: Number of cases: 10,139 Avg. rework time : 15 min Realization potential: 95% SAVINGS: 10,139 * 0,95 * 15 min = 2408 h = 1,3 FTE = 91,000€ Please note: all screenshots used are merely exemplary and have not been taken from real customer data. Hence, they do not correspond with the calculations made in this business case. 91k € SAVINGS

  15. How to analyze manual rework activities and accelerate the throughput time by increasing the automation rate ? ANALYSIS OVERVIEW HOW IT WORKS ROI CALCULATION MEASURES & POTENTIALS With deep down analyses of different process steps, we identified multiple process steps, that could be automated by robotic process automation. Such as verify insurance coverage, allocate invoice and book invoice. Thus we were able to accelerate the overall throughput time by 30% with a low effort. OVERALL POTENTIAL RESULTS: # of service orders: 143,062 Increase of automation rate: 30% Avg. time of manual effort: 10 min SAVINGS: 143,062 * 0,3 * 10min = 7153 h = 4 FTE = 280,000€ 1 FTE = 5 Days/Week * 8h * (52-5) Weeks/Year = 1880 Hours/Year = 70.000€ Please note: all screenshots used are merely exemplary and have not been taken from real customer data. Hence, they do not correspond with the calculations made in this business case. 280k € SAVINGS

  16. DE US NE Contact THERESIENSTR. 6 80333 Munich Germany T +49 89 4161596 70 F +49 89 4161596 79 164 West 25th Street, 9th Floor New York, NY 10001 United States T +1 212 847 0692 F +1 (212) 271-9382 Sint Janssingel 905211 DA ‘s-HertogenboschThe Netherlands T +31 13 590 2333 F +49 89 4161596 79 info@celonis.com

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