SlideShare a Scribd company logo
1 of 3
Download to read offline
Case Study
Low
Persistency
compared to
industry
standards
Low
Customer
Contactability
www.aureusanalytics.com
Improvement In Persistency Score for a large Insurer
Aureus Approach
BenefitsProducts
Deployment of AUPERA & C360
Training to Call Center team
Communication by Call Center based on Policy Risk Score
Nearly
2-3%
improvement
in persistency
score
Nearly
2-4%
improvement
in customer
contactability
THIS SEEMINGLY SMALL IMPROVEMENT IN
PERSISTENCY WILL HELP THE CLIENT ADD
NEARLY USD 3.6 MILLION TO THEIR TOP LINE.
The Challenge
The client has been in business since 2008-09. Since inception, it has grown from strength to
strength. In recent times, however, persistency rates had become a key area of concern. When
they approached Aureus, the client’s 13th
month persistency rate was less than 50%, which
was far lower than the industry average of 66%.
The persistency problem was further compounded by the fact that, customer contactability
was low due to incorrect or outdated data.
The client had customers falling into two main buckets – monthly and non-monthly premium
paying modes. For renewals, the client customer service team would call up the entire
customer base and remind them to renew their policy, which was either due for renewal, or
in grace period or had already lapsed. This blanket calling in no order of customer likelihood
to pay led to massive inefficiencies for the organization, with little benefit in persistency
improvement.
Using AUPERA, we were able to develop ‘Payment propensity” models that helped The client
bucket their customers in a Red, Amber or Green bucket based on their likelihood to pay.
Persistency Improvements using Predictive Analytics
Of the policies expected to pay in a given month, about 60% came from the lapsed portfolio
and of the rest, nearly half were monthly mode policies. We observed that the payment
behaviorof lapsed policies was quite different compared to that of active policies. Even in the
lapse bucket, there were differences in payment behavior of recently lapsed policies as
against older lapses.
Benefits to The Client
In each case, the model buckets the given set of policies into 3 buckets - red, amber and green – according to payment
propensity. Such bucketing allowed the customer service teams to prioritize which customers to call first. Themodelis
run on a monthly basis.
Comparison of model predictions versus actual results generally shows an agreement within 3-4%. Use of predictive
modeling for optimizing calling efforthas helped the client reduce the calling effort by about 50%.
In addition to this bucketing, we also ran household analytics using Customer 360 (C360) to identify customers who
were not reachable. By using a combination of NLP for matching names and addresses and as well as the proprietary
Aureus Network Analysis algorithm, we were able to identify nearly 14000 households with more than one policy.
Web: www.aureusanalytics.com Email: info@aureusanalytics.com
Stay Connected With Us: @AureusAnalytics /company/aureus-analytics
Using AUPERA and C360, we were able to improve the persistency for the client by
approximately 2-3% and the contactability improvement was about 2-4%. This seemingly
small improvement in persistency will help the client add nearly USD 3.6 million to their top
line.
About The client
The client is a mid-sized insurance company with about 400,000 customers. With over 7
million lives covered, the client offers solutions for individuals as well as corporate groups.
In addition, monthly mode policies also
displayed a different behavior as compared
to non-monthly mode policies. To account
for these differences, while keeping in sync
with business priorities, we developed 5
different models – to be used for scoring the
following 5 buckets:
Non-monthly policies in the due/grace bucket
Non-monthly policies in the first 2 months of lapse
Non-monthly policies lapsed more than 2 months ago
Monthly policies lapsed more than 2 months ago
Monthly policies in the first 2 months of lapse

More Related Content

What's hot

LMRF Healthcare - Customer Relationship Management
LMRF Healthcare - Customer Relationship ManagementLMRF Healthcare - Customer Relationship Management
LMRF Healthcare - Customer Relationship ManagementLMRF Healthcare
 
CRM Implementation in Healthcare Sector: Max Healthcare.
CRM Implementation in Healthcare Sector: Max Healthcare.CRM Implementation in Healthcare Sector: Max Healthcare.
CRM Implementation in Healthcare Sector: Max Healthcare.Siddharth Bhatnagar
 
Predictive Analytics: How This Revolutionary Technology for Strategic Marketi...
Predictive Analytics: How This Revolutionary Technology for Strategic Marketi...Predictive Analytics: How This Revolutionary Technology for Strategic Marketi...
Predictive Analytics: How This Revolutionary Technology for Strategic Marketi...Media Needle
 
Navigating to insights driven customer engagement
Navigating to insights driven customer engagementNavigating to insights driven customer engagement
Navigating to insights driven customer engagementZephyr Health
 
Predictive Analytics in Healthcare
Predictive Analytics in HealthcarePredictive Analytics in Healthcare
Predictive Analytics in HealthcareBESLER
 
CRM un pharmaceutical industry
CRM un pharmaceutical industryCRM un pharmaceutical industry
CRM un pharmaceutical industrygauravamity
 
DMA MAC Presentation: Kajal Mukhopadhyay, Ph.D.
DMA MAC Presentation: Kajal Mukhopadhyay, Ph.D.DMA MAC Presentation: Kajal Mukhopadhyay, Ph.D.
DMA MAC Presentation: Kajal Mukhopadhyay, Ph.D.Kajal Mukhopadhyay, PhD
 
RELATIENT - brief overview - 2016
RELATIENT - brief overview - 2016RELATIENT - brief overview - 2016
RELATIENT - brief overview - 2016Sam Johnson
 
8 must haves for modern Clinical Data Integration
8 must haves for modern Clinical Data Integration8 must haves for modern Clinical Data Integration
8 must haves for modern Clinical Data IntegrationCitiusTech
 
Referral management solution is the need of the hour for large hospitals
Referral management solution is the need of the hour for large hospitalsReferral management solution is the need of the hour for large hospitals
Referral management solution is the need of the hour for large hospitalsGaryRichards30
 
Customer Management Infographic - Forrester Report
Customer Management Infographic - Forrester ReportCustomer Management Infographic - Forrester Report
Customer Management Infographic - Forrester ReportOmer Celep
 
Pharmaceutical Multi Channel Relationship Marketing
Pharmaceutical Multi Channel Relationship MarketingPharmaceutical Multi Channel Relationship Marketing
Pharmaceutical Multi Channel Relationship Marketingrlwegner
 
An Empirical Study on Customer Consumption, Loyalty and Retention on a B2C E-...
An Empirical Study on Customer Consumption, Loyalty and Retention on a B2C E-...An Empirical Study on Customer Consumption, Loyalty and Retention on a B2C E-...
An Empirical Study on Customer Consumption, Loyalty and Retention on a B2C E-...Monika Mishra
 
Mike brassil data-analytics-2
Mike brassil data-analytics-2Mike brassil data-analytics-2
Mike brassil data-analytics-2MikeBrassil1
 

What's hot (18)

LMRF Healthcare - Customer Relationship Management
LMRF Healthcare - Customer Relationship ManagementLMRF Healthcare - Customer Relationship Management
LMRF Healthcare - Customer Relationship Management
 
CRM Implementation in Healthcare Sector: Max Healthcare.
CRM Implementation in Healthcare Sector: Max Healthcare.CRM Implementation in Healthcare Sector: Max Healthcare.
CRM Implementation in Healthcare Sector: Max Healthcare.
 
Predictive Analytics: How This Revolutionary Technology for Strategic Marketi...
Predictive Analytics: How This Revolutionary Technology for Strategic Marketi...Predictive Analytics: How This Revolutionary Technology for Strategic Marketi...
Predictive Analytics: How This Revolutionary Technology for Strategic Marketi...
 
Navigating to insights driven customer engagement
Navigating to insights driven customer engagementNavigating to insights driven customer engagement
Navigating to insights driven customer engagement
 
Predictive Analytics in Healthcare
Predictive Analytics in HealthcarePredictive Analytics in Healthcare
Predictive Analytics in Healthcare
 
CRM un pharmaceutical industry
CRM un pharmaceutical industryCRM un pharmaceutical industry
CRM un pharmaceutical industry
 
MA Sales Presentation
MA Sales PresentationMA Sales Presentation
MA Sales Presentation
 
DMA MAC Presentation: Kajal Mukhopadhyay, Ph.D.
DMA MAC Presentation: Kajal Mukhopadhyay, Ph.D.DMA MAC Presentation: Kajal Mukhopadhyay, Ph.D.
DMA MAC Presentation: Kajal Mukhopadhyay, Ph.D.
 
RELATIENT - brief overview - 2016
RELATIENT - brief overview - 2016RELATIENT - brief overview - 2016
RELATIENT - brief overview - 2016
 
8 must haves for modern Clinical Data Integration
8 must haves for modern Clinical Data Integration8 must haves for modern Clinical Data Integration
8 must haves for modern Clinical Data Integration
 
Referral management solution is the need of the hour for large hospitals
Referral management solution is the need of the hour for large hospitalsReferral management solution is the need of the hour for large hospitals
Referral management solution is the need of the hour for large hospitals
 
Customer Management Infographic - Forrester Report
Customer Management Infographic - Forrester ReportCustomer Management Infographic - Forrester Report
Customer Management Infographic - Forrester Report
 
Pharmaceutical Multi Channel Relationship Marketing
Pharmaceutical Multi Channel Relationship MarketingPharmaceutical Multi Channel Relationship Marketing
Pharmaceutical Multi Channel Relationship Marketing
 
SMAC
SMACSMAC
SMAC
 
An Empirical Study on Customer Consumption, Loyalty and Retention on a B2C E-...
An Empirical Study on Customer Consumption, Loyalty and Retention on a B2C E-...An Empirical Study on Customer Consumption, Loyalty and Retention on a B2C E-...
An Empirical Study on Customer Consumption, Loyalty and Retention on a B2C E-...
 
Adherence product plan v6.1
Adherence product plan v6.1Adherence product plan v6.1
Adherence product plan v6.1
 
Marketing
MarketingMarketing
Marketing
 
Mike brassil data-analytics-2
Mike brassil data-analytics-2Mike brassil data-analytics-2
Mike brassil data-analytics-2
 

Similar to Improvement in Persistency Score for Large Insurer

QWE Inc Report_Group 2
QWE Inc Report_Group 2QWE Inc Report_Group 2
QWE Inc Report_Group 2Xinyu Liu
 
Accenture maximizing-customer-retention
Accenture maximizing-customer-retentionAccenture maximizing-customer-retention
Accenture maximizing-customer-retentionAmer Sayed
 
Bank churn with Data Science
Bank churn with Data ScienceBank churn with Data Science
Bank churn with Data ScienceCarolyn Knight
 
The Future Of Billing Exploring Subscription-.pdf
The Future Of Billing Exploring Subscription-.pdfThe Future Of Billing Exploring Subscription-.pdf
The Future Of Billing Exploring Subscription-.pdfInvoicera
 
OurBank Customer Retention Strategy Q1 2021
OurBank Customer Retention Strategy Q1 2021OurBank Customer Retention Strategy Q1 2021
OurBank Customer Retention Strategy Q1 2021Mitch Leung
 
ANALYTICS PLAN TO REDUCE CUSTOMER CHURN AT YORE BLENDS Himabin.docx
ANALYTICS PLAN TO REDUCE CUSTOMER CHURN AT YORE BLENDS Himabin.docxANALYTICS PLAN TO REDUCE CUSTOMER CHURN AT YORE BLENDS Himabin.docx
ANALYTICS PLAN TO REDUCE CUSTOMER CHURN AT YORE BLENDS Himabin.docxdaniahendric
 
ANALYTICS PLAN TO REDUCE CUSTOMER CHURN AT YORE BLENDS Himabin.docx
ANALYTICS PLAN TO REDUCE CUSTOMER CHURN AT YORE BLENDS Himabin.docxANALYTICS PLAN TO REDUCE CUSTOMER CHURN AT YORE BLENDS Himabin.docx
ANALYTICS PLAN TO REDUCE CUSTOMER CHURN AT YORE BLENDS Himabin.docxgreg1eden90113
 
Analytics retention must-have analytics for your retention tool kit
Analytics retention must-have analytics for your retention tool kitAnalytics retention must-have analytics for your retention tool kit
Analytics retention must-have analytics for your retention tool kitBullsEye Internet Marketing
 
What are Subscription Business Models.pdf
What are Subscription Business Models.pdfWhat are Subscription Business Models.pdf
What are Subscription Business Models.pdfMr. Business Magazine
 
Mckesson payor conf implementing a pred. model
Mckesson payor conf implementing a pred. modelMckesson payor conf implementing a pred. model
Mckesson payor conf implementing a pred. modelDrFACHE
 
Multichannel Retention Strategies: A Steady Diet of Low Hanging Fruit
Multichannel Retention Strategies: A Steady Diet of Low Hanging FruitMultichannel Retention Strategies: A Steady Diet of Low Hanging Fruit
Multichannel Retention Strategies: A Steady Diet of Low Hanging FruitVivastream
 
Prepaid customer segmentation in telecommunications: An overview of common pr...
Prepaid customer segmentation in telecommunications: An overview of common pr...Prepaid customer segmentation in telecommunications: An overview of common pr...
Prepaid customer segmentation in telecommunications: An overview of common pr...Exacaster
 
Application of predictive analytics
Application of predictive analyticsApplication of predictive analytics
Application of predictive analyticsPrasad Narasimhan
 
Telecom analytics brochure
Telecom analytics brochure Telecom analytics brochure
Telecom analytics brochure Daniel Thomas
 
Customer Service: Achieving excellence through a company-wide approach
Customer Service: Achieving excellence through a company-wide approachCustomer Service: Achieving excellence through a company-wide approach
Customer Service: Achieving excellence through a company-wide approachValue Partners
 
Churn in the Telecommunications Industry
Churn in the Telecommunications IndustryChurn in the Telecommunications Industry
Churn in the Telecommunications Industryskewdlogix
 
Introduction to crm
Introduction to crmIntroduction to crm
Introduction to crmolenyxa
 
Customer insight presentation s houston - boston march 2014
Customer insight presentation   s houston - boston march 2014Customer insight presentation   s houston - boston march 2014
Customer insight presentation s houston - boston march 2014Stuart Houston
 

Similar to Improvement in Persistency Score for Large Insurer (20)

QWE Inc Report_Group 2
QWE Inc Report_Group 2QWE Inc Report_Group 2
QWE Inc Report_Group 2
 
Accenture maximizing-customer-retention
Accenture maximizing-customer-retentionAccenture maximizing-customer-retention
Accenture maximizing-customer-retention
 
Bank churn with Data Science
Bank churn with Data ScienceBank churn with Data Science
Bank churn with Data Science
 
The Future Of Billing Exploring Subscription-.pdf
The Future Of Billing Exploring Subscription-.pdfThe Future Of Billing Exploring Subscription-.pdf
The Future Of Billing Exploring Subscription-.pdf
 
OurBank Customer Retention Strategy Q1 2021
OurBank Customer Retention Strategy Q1 2021OurBank Customer Retention Strategy Q1 2021
OurBank Customer Retention Strategy Q1 2021
 
ANALYTICS PLAN TO REDUCE CUSTOMER CHURN AT YORE BLENDS Himabin.docx
ANALYTICS PLAN TO REDUCE CUSTOMER CHURN AT YORE BLENDS Himabin.docxANALYTICS PLAN TO REDUCE CUSTOMER CHURN AT YORE BLENDS Himabin.docx
ANALYTICS PLAN TO REDUCE CUSTOMER CHURN AT YORE BLENDS Himabin.docx
 
ANALYTICS PLAN TO REDUCE CUSTOMER CHURN AT YORE BLENDS Himabin.docx
ANALYTICS PLAN TO REDUCE CUSTOMER CHURN AT YORE BLENDS Himabin.docxANALYTICS PLAN TO REDUCE CUSTOMER CHURN AT YORE BLENDS Himabin.docx
ANALYTICS PLAN TO REDUCE CUSTOMER CHURN AT YORE BLENDS Himabin.docx
 
Analytics retention must-have analytics for your retention tool kit
Analytics retention must-have analytics for your retention tool kitAnalytics retention must-have analytics for your retention tool kit
Analytics retention must-have analytics for your retention tool kit
 
What are Subscription Business Models.pdf
What are Subscription Business Models.pdfWhat are Subscription Business Models.pdf
What are Subscription Business Models.pdf
 
Mckesson payor conf implementing a pred. model
Mckesson payor conf implementing a pred. modelMckesson payor conf implementing a pred. model
Mckesson payor conf implementing a pred. model
 
Multichannel Retention Strategies: A Steady Diet of Low Hanging Fruit
Multichannel Retention Strategies: A Steady Diet of Low Hanging FruitMultichannel Retention Strategies: A Steady Diet of Low Hanging Fruit
Multichannel Retention Strategies: A Steady Diet of Low Hanging Fruit
 
Prepaid customer segmentation in telecommunications: An overview of common pr...
Prepaid customer segmentation in telecommunications: An overview of common pr...Prepaid customer segmentation in telecommunications: An overview of common pr...
Prepaid customer segmentation in telecommunications: An overview of common pr...
 
TDP Case Studies
TDP Case StudiesTDP Case Studies
TDP Case Studies
 
The three pillars of successful debt collection
The three pillars of successful debt collectionThe three pillars of successful debt collection
The three pillars of successful debt collection
 
Application of predictive analytics
Application of predictive analyticsApplication of predictive analytics
Application of predictive analytics
 
Telecom analytics brochure
Telecom analytics brochure Telecom analytics brochure
Telecom analytics brochure
 
Customer Service: Achieving excellence through a company-wide approach
Customer Service: Achieving excellence through a company-wide approachCustomer Service: Achieving excellence through a company-wide approach
Customer Service: Achieving excellence through a company-wide approach
 
Churn in the Telecommunications Industry
Churn in the Telecommunications IndustryChurn in the Telecommunications Industry
Churn in the Telecommunications Industry
 
Introduction to crm
Introduction to crmIntroduction to crm
Introduction to crm
 
Customer insight presentation s houston - boston march 2014
Customer insight presentation   s houston - boston march 2014Customer insight presentation   s houston - boston march 2014
Customer insight presentation s houston - boston march 2014
 

More from Aureus Analytics

Using Machine Learning to Find a needle in a haystack Aureus Analytics
Using Machine Learning to Find a needle in a haystack  Aureus AnalyticsUsing Machine Learning to Find a needle in a haystack  Aureus Analytics
Using Machine Learning to Find a needle in a haystack Aureus AnalyticsAureus Analytics
 
Big Data and Analytics Trends 2018
Big Data and Analytics Trends 2018Big Data and Analytics Trends 2018
Big Data and Analytics Trends 2018Aureus Analytics
 
Improving Marketing Campaigns
Improving Marketing CampaignsImproving Marketing Campaigns
Improving Marketing CampaignsAureus Analytics
 
Net Promoter Score Pitfalls to Avoid
Net Promoter Score Pitfalls to AvoidNet Promoter Score Pitfalls to Avoid
Net Promoter Score Pitfalls to AvoidAureus Analytics
 
The Art Of Net Promoter Score
The Art Of Net Promoter ScoreThe Art Of Net Promoter Score
The Art Of Net Promoter ScoreAureus Analytics
 
Big data-analytics-trends-2016
Big data-analytics-trends-2016Big data-analytics-trends-2016
Big data-analytics-trends-2016Aureus Analytics
 
Point of Decision Analytics in Insurance
Point of Decision Analytics in InsurancePoint of Decision Analytics in Insurance
Point of Decision Analytics in InsuranceAureus Analytics
 
Statistical model infographic.compressed (2)
Statistical model infographic.compressed (2)Statistical model infographic.compressed (2)
Statistical model infographic.compressed (2)Aureus Analytics
 
Infographic: Big Data and Analytics trends for 2015
Infographic: Big Data and Analytics trends for 2015Infographic: Big Data and Analytics trends for 2015
Infographic: Big Data and Analytics trends for 2015Aureus Analytics
 
Infographic: Steps to Building a Statistical Model
Infographic: Steps to Building a Statistical ModelInfographic: Steps to Building a Statistical Model
Infographic: Steps to Building a Statistical ModelAureus Analytics
 
Ten Commandments of Statistical Modelling - Infographic
Ten Commandments of Statistical Modelling - InfographicTen Commandments of Statistical Modelling - Infographic
Ten Commandments of Statistical Modelling - InfographicAureus Analytics
 
67 years of Steering Innovation
67 years of Steering Innovation67 years of Steering Innovation
67 years of Steering InnovationAureus Analytics
 
Demystifying A Data Scientist
Demystifying A Data ScientistDemystifying A Data Scientist
Demystifying A Data ScientistAureus Analytics
 
FIFA World Cup 2014 in Numbers
FIFA World Cup 2014 in NumbersFIFA World Cup 2014 in Numbers
FIFA World Cup 2014 in NumbersAureus Analytics
 
Big Data and Analytics Trends in 2014
Big Data and Analytics Trends in 2014Big Data and Analytics Trends in 2014
Big Data and Analytics Trends in 2014Aureus Analytics
 
Implementation challenges in Big Data - Dr. Nilesh Karnik
Implementation challenges in Big Data - Dr. Nilesh KarnikImplementation challenges in Big Data - Dr. Nilesh Karnik
Implementation challenges in Big Data - Dr. Nilesh KarnikAureus Analytics
 

More from Aureus Analytics (16)

Using Machine Learning to Find a needle in a haystack Aureus Analytics
Using Machine Learning to Find a needle in a haystack  Aureus AnalyticsUsing Machine Learning to Find a needle in a haystack  Aureus Analytics
Using Machine Learning to Find a needle in a haystack Aureus Analytics
 
Big Data and Analytics Trends 2018
Big Data and Analytics Trends 2018Big Data and Analytics Trends 2018
Big Data and Analytics Trends 2018
 
Improving Marketing Campaigns
Improving Marketing CampaignsImproving Marketing Campaigns
Improving Marketing Campaigns
 
Net Promoter Score Pitfalls to Avoid
Net Promoter Score Pitfalls to AvoidNet Promoter Score Pitfalls to Avoid
Net Promoter Score Pitfalls to Avoid
 
The Art Of Net Promoter Score
The Art Of Net Promoter ScoreThe Art Of Net Promoter Score
The Art Of Net Promoter Score
 
Big data-analytics-trends-2016
Big data-analytics-trends-2016Big data-analytics-trends-2016
Big data-analytics-trends-2016
 
Point of Decision Analytics in Insurance
Point of Decision Analytics in InsurancePoint of Decision Analytics in Insurance
Point of Decision Analytics in Insurance
 
Statistical model infographic.compressed (2)
Statistical model infographic.compressed (2)Statistical model infographic.compressed (2)
Statistical model infographic.compressed (2)
 
Infographic: Big Data and Analytics trends for 2015
Infographic: Big Data and Analytics trends for 2015Infographic: Big Data and Analytics trends for 2015
Infographic: Big Data and Analytics trends for 2015
 
Infographic: Steps to Building a Statistical Model
Infographic: Steps to Building a Statistical ModelInfographic: Steps to Building a Statistical Model
Infographic: Steps to Building a Statistical Model
 
Ten Commandments of Statistical Modelling - Infographic
Ten Commandments of Statistical Modelling - InfographicTen Commandments of Statistical Modelling - Infographic
Ten Commandments of Statistical Modelling - Infographic
 
67 years of Steering Innovation
67 years of Steering Innovation67 years of Steering Innovation
67 years of Steering Innovation
 
Demystifying A Data Scientist
Demystifying A Data ScientistDemystifying A Data Scientist
Demystifying A Data Scientist
 
FIFA World Cup 2014 in Numbers
FIFA World Cup 2014 in NumbersFIFA World Cup 2014 in Numbers
FIFA World Cup 2014 in Numbers
 
Big Data and Analytics Trends in 2014
Big Data and Analytics Trends in 2014Big Data and Analytics Trends in 2014
Big Data and Analytics Trends in 2014
 
Implementation challenges in Big Data - Dr. Nilesh Karnik
Implementation challenges in Big Data - Dr. Nilesh KarnikImplementation challenges in Big Data - Dr. Nilesh Karnik
Implementation challenges in Big Data - Dr. Nilesh Karnik
 

Recently uploaded

SMOTE and K-Fold Cross Validation-Presentation.pptx
SMOTE and K-Fold Cross Validation-Presentation.pptxSMOTE and K-Fold Cross Validation-Presentation.pptx
SMOTE and K-Fold Cross Validation-Presentation.pptxHaritikaChhatwal1
 
English-8-Q4-W3-Synthesizing-Essential-Information-From-Various-Sources-1.pdf
English-8-Q4-W3-Synthesizing-Essential-Information-From-Various-Sources-1.pdfEnglish-8-Q4-W3-Synthesizing-Essential-Information-From-Various-Sources-1.pdf
English-8-Q4-W3-Synthesizing-Essential-Information-From-Various-Sources-1.pdfblazblazml
 
Decoding the Heart: Student Presentation on Heart Attack Prediction with Data...
Decoding the Heart: Student Presentation on Heart Attack Prediction with Data...Decoding the Heart: Student Presentation on Heart Attack Prediction with Data...
Decoding the Heart: Student Presentation on Heart Attack Prediction with Data...Boston Institute of Analytics
 
Data Analysis Project : Targeting the Right Customers, Presentation on Bank M...
Data Analysis Project : Targeting the Right Customers, Presentation on Bank M...Data Analysis Project : Targeting the Right Customers, Presentation on Bank M...
Data Analysis Project : Targeting the Right Customers, Presentation on Bank M...Boston Institute of Analytics
 
why-transparency-and-traceability-are-essential-for-sustainable-supply-chains...
why-transparency-and-traceability-are-essential-for-sustainable-supply-chains...why-transparency-and-traceability-are-essential-for-sustainable-supply-chains...
why-transparency-and-traceability-are-essential-for-sustainable-supply-chains...Jack Cole
 
Student profile product demonstration on grades, ability, well-being and mind...
Student profile product demonstration on grades, ability, well-being and mind...Student profile product demonstration on grades, ability, well-being and mind...
Student profile product demonstration on grades, ability, well-being and mind...Seán Kennedy
 
NO1 Certified Black Magic Specialist Expert Amil baba in Lahore Islamabad Raw...
NO1 Certified Black Magic Specialist Expert Amil baba in Lahore Islamabad Raw...NO1 Certified Black Magic Specialist Expert Amil baba in Lahore Islamabad Raw...
NO1 Certified Black Magic Specialist Expert Amil baba in Lahore Islamabad Raw...Amil Baba Dawood bangali
 
World Economic Forum Metaverse Ecosystem By Utpal Chakraborty.pdf
World Economic Forum Metaverse Ecosystem By Utpal Chakraborty.pdfWorld Economic Forum Metaverse Ecosystem By Utpal Chakraborty.pdf
World Economic Forum Metaverse Ecosystem By Utpal Chakraborty.pdfsimulationsindia
 
Data Analysis Project Presentation: Unveiling Your Ideal Customer, Bank Custo...
Data Analysis Project Presentation: Unveiling Your Ideal Customer, Bank Custo...Data Analysis Project Presentation: Unveiling Your Ideal Customer, Bank Custo...
Data Analysis Project Presentation: Unveiling Your Ideal Customer, Bank Custo...Boston Institute of Analytics
 
Networking Case Study prepared by teacher.pptx
Networking Case Study prepared by teacher.pptxNetworking Case Study prepared by teacher.pptx
Networking Case Study prepared by teacher.pptxHimangsuNath
 
Semantic Shed - Squashing and Squeezing.pptx
Semantic Shed - Squashing and Squeezing.pptxSemantic Shed - Squashing and Squeezing.pptx
Semantic Shed - Squashing and Squeezing.pptxMike Bennett
 
The Power of Data-Driven Storytelling_ Unveiling the Layers of Insight.pptx
The Power of Data-Driven Storytelling_ Unveiling the Layers of Insight.pptxThe Power of Data-Driven Storytelling_ Unveiling the Layers of Insight.pptx
The Power of Data-Driven Storytelling_ Unveiling the Layers of Insight.pptxTasha Penwell
 
Cyber awareness ppt on the recorded data
Cyber awareness ppt on the recorded dataCyber awareness ppt on the recorded data
Cyber awareness ppt on the recorded dataTecnoIncentive
 
Bank Loan Approval Analysis: A Comprehensive Data Analysis Project
Bank Loan Approval Analysis: A Comprehensive Data Analysis ProjectBank Loan Approval Analysis: A Comprehensive Data Analysis Project
Bank Loan Approval Analysis: A Comprehensive Data Analysis ProjectBoston Institute of Analytics
 
modul pembelajaran robotic Workshop _ by Slidesgo.pptx
modul pembelajaran robotic Workshop _ by Slidesgo.pptxmodul pembelajaran robotic Workshop _ by Slidesgo.pptx
modul pembelajaran robotic Workshop _ by Slidesgo.pptxaleedritatuxx
 
Real-Time AI Streaming - AI Max Princeton
Real-Time AI  Streaming - AI Max PrincetonReal-Time AI  Streaming - AI Max Princeton
Real-Time AI Streaming - AI Max PrincetonTimothy Spann
 
What To Do For World Nature Conservation Day by Slidesgo.pptx
What To Do For World Nature Conservation Day by Slidesgo.pptxWhat To Do For World Nature Conservation Day by Slidesgo.pptx
What To Do For World Nature Conservation Day by Slidesgo.pptxSimranPal17
 
Student Profile Sample report on improving academic performance by uniting gr...
Student Profile Sample report on improving academic performance by uniting gr...Student Profile Sample report on improving academic performance by uniting gr...
Student Profile Sample report on improving academic performance by uniting gr...Seán Kennedy
 
Learn How Data Science Changes Our World
Learn How Data Science Changes Our WorldLearn How Data Science Changes Our World
Learn How Data Science Changes Our WorldEduminds Learning
 
Digital Marketing Plan, how digital marketing works
Digital Marketing Plan, how digital marketing worksDigital Marketing Plan, how digital marketing works
Digital Marketing Plan, how digital marketing worksdeepakthakur548787
 

Recently uploaded (20)

SMOTE and K-Fold Cross Validation-Presentation.pptx
SMOTE and K-Fold Cross Validation-Presentation.pptxSMOTE and K-Fold Cross Validation-Presentation.pptx
SMOTE and K-Fold Cross Validation-Presentation.pptx
 
English-8-Q4-W3-Synthesizing-Essential-Information-From-Various-Sources-1.pdf
English-8-Q4-W3-Synthesizing-Essential-Information-From-Various-Sources-1.pdfEnglish-8-Q4-W3-Synthesizing-Essential-Information-From-Various-Sources-1.pdf
English-8-Q4-W3-Synthesizing-Essential-Information-From-Various-Sources-1.pdf
 
Decoding the Heart: Student Presentation on Heart Attack Prediction with Data...
Decoding the Heart: Student Presentation on Heart Attack Prediction with Data...Decoding the Heart: Student Presentation on Heart Attack Prediction with Data...
Decoding the Heart: Student Presentation on Heart Attack Prediction with Data...
 
Data Analysis Project : Targeting the Right Customers, Presentation on Bank M...
Data Analysis Project : Targeting the Right Customers, Presentation on Bank M...Data Analysis Project : Targeting the Right Customers, Presentation on Bank M...
Data Analysis Project : Targeting the Right Customers, Presentation on Bank M...
 
why-transparency-and-traceability-are-essential-for-sustainable-supply-chains...
why-transparency-and-traceability-are-essential-for-sustainable-supply-chains...why-transparency-and-traceability-are-essential-for-sustainable-supply-chains...
why-transparency-and-traceability-are-essential-for-sustainable-supply-chains...
 
Student profile product demonstration on grades, ability, well-being and mind...
Student profile product demonstration on grades, ability, well-being and mind...Student profile product demonstration on grades, ability, well-being and mind...
Student profile product demonstration on grades, ability, well-being and mind...
 
NO1 Certified Black Magic Specialist Expert Amil baba in Lahore Islamabad Raw...
NO1 Certified Black Magic Specialist Expert Amil baba in Lahore Islamabad Raw...NO1 Certified Black Magic Specialist Expert Amil baba in Lahore Islamabad Raw...
NO1 Certified Black Magic Specialist Expert Amil baba in Lahore Islamabad Raw...
 
World Economic Forum Metaverse Ecosystem By Utpal Chakraborty.pdf
World Economic Forum Metaverse Ecosystem By Utpal Chakraborty.pdfWorld Economic Forum Metaverse Ecosystem By Utpal Chakraborty.pdf
World Economic Forum Metaverse Ecosystem By Utpal Chakraborty.pdf
 
Data Analysis Project Presentation: Unveiling Your Ideal Customer, Bank Custo...
Data Analysis Project Presentation: Unveiling Your Ideal Customer, Bank Custo...Data Analysis Project Presentation: Unveiling Your Ideal Customer, Bank Custo...
Data Analysis Project Presentation: Unveiling Your Ideal Customer, Bank Custo...
 
Networking Case Study prepared by teacher.pptx
Networking Case Study prepared by teacher.pptxNetworking Case Study prepared by teacher.pptx
Networking Case Study prepared by teacher.pptx
 
Semantic Shed - Squashing and Squeezing.pptx
Semantic Shed - Squashing and Squeezing.pptxSemantic Shed - Squashing and Squeezing.pptx
Semantic Shed - Squashing and Squeezing.pptx
 
The Power of Data-Driven Storytelling_ Unveiling the Layers of Insight.pptx
The Power of Data-Driven Storytelling_ Unveiling the Layers of Insight.pptxThe Power of Data-Driven Storytelling_ Unveiling the Layers of Insight.pptx
The Power of Data-Driven Storytelling_ Unveiling the Layers of Insight.pptx
 
Cyber awareness ppt on the recorded data
Cyber awareness ppt on the recorded dataCyber awareness ppt on the recorded data
Cyber awareness ppt on the recorded data
 
Bank Loan Approval Analysis: A Comprehensive Data Analysis Project
Bank Loan Approval Analysis: A Comprehensive Data Analysis ProjectBank Loan Approval Analysis: A Comprehensive Data Analysis Project
Bank Loan Approval Analysis: A Comprehensive Data Analysis Project
 
modul pembelajaran robotic Workshop _ by Slidesgo.pptx
modul pembelajaran robotic Workshop _ by Slidesgo.pptxmodul pembelajaran robotic Workshop _ by Slidesgo.pptx
modul pembelajaran robotic Workshop _ by Slidesgo.pptx
 
Real-Time AI Streaming - AI Max Princeton
Real-Time AI  Streaming - AI Max PrincetonReal-Time AI  Streaming - AI Max Princeton
Real-Time AI Streaming - AI Max Princeton
 
What To Do For World Nature Conservation Day by Slidesgo.pptx
What To Do For World Nature Conservation Day by Slidesgo.pptxWhat To Do For World Nature Conservation Day by Slidesgo.pptx
What To Do For World Nature Conservation Day by Slidesgo.pptx
 
Student Profile Sample report on improving academic performance by uniting gr...
Student Profile Sample report on improving academic performance by uniting gr...Student Profile Sample report on improving academic performance by uniting gr...
Student Profile Sample report on improving academic performance by uniting gr...
 
Learn How Data Science Changes Our World
Learn How Data Science Changes Our WorldLearn How Data Science Changes Our World
Learn How Data Science Changes Our World
 
Digital Marketing Plan, how digital marketing works
Digital Marketing Plan, how digital marketing worksDigital Marketing Plan, how digital marketing works
Digital Marketing Plan, how digital marketing works
 

Improvement in Persistency Score for Large Insurer

  • 1. Case Study Low Persistency compared to industry standards Low Customer Contactability www.aureusanalytics.com Improvement In Persistency Score for a large Insurer Aureus Approach BenefitsProducts Deployment of AUPERA & C360 Training to Call Center team Communication by Call Center based on Policy Risk Score Nearly 2-3% improvement in persistency score Nearly 2-4% improvement in customer contactability THIS SEEMINGLY SMALL IMPROVEMENT IN PERSISTENCY WILL HELP THE CLIENT ADD NEARLY USD 3.6 MILLION TO THEIR TOP LINE.
  • 2. The Challenge The client has been in business since 2008-09. Since inception, it has grown from strength to strength. In recent times, however, persistency rates had become a key area of concern. When they approached Aureus, the client’s 13th month persistency rate was less than 50%, which was far lower than the industry average of 66%. The persistency problem was further compounded by the fact that, customer contactability was low due to incorrect or outdated data. The client had customers falling into two main buckets – monthly and non-monthly premium paying modes. For renewals, the client customer service team would call up the entire customer base and remind them to renew their policy, which was either due for renewal, or in grace period or had already lapsed. This blanket calling in no order of customer likelihood to pay led to massive inefficiencies for the organization, with little benefit in persistency improvement. Using AUPERA, we were able to develop ‘Payment propensity” models that helped The client bucket their customers in a Red, Amber or Green bucket based on their likelihood to pay. Persistency Improvements using Predictive Analytics Of the policies expected to pay in a given month, about 60% came from the lapsed portfolio and of the rest, nearly half were monthly mode policies. We observed that the payment behaviorof lapsed policies was quite different compared to that of active policies. Even in the lapse bucket, there were differences in payment behavior of recently lapsed policies as against older lapses.
  • 3. Benefits to The Client In each case, the model buckets the given set of policies into 3 buckets - red, amber and green – according to payment propensity. Such bucketing allowed the customer service teams to prioritize which customers to call first. Themodelis run on a monthly basis. Comparison of model predictions versus actual results generally shows an agreement within 3-4%. Use of predictive modeling for optimizing calling efforthas helped the client reduce the calling effort by about 50%. In addition to this bucketing, we also ran household analytics using Customer 360 (C360) to identify customers who were not reachable. By using a combination of NLP for matching names and addresses and as well as the proprietary Aureus Network Analysis algorithm, we were able to identify nearly 14000 households with more than one policy. Web: www.aureusanalytics.com Email: info@aureusanalytics.com Stay Connected With Us: @AureusAnalytics /company/aureus-analytics Using AUPERA and C360, we were able to improve the persistency for the client by approximately 2-3% and the contactability improvement was about 2-4%. This seemingly small improvement in persistency will help the client add nearly USD 3.6 million to their top line. About The client The client is a mid-sized insurance company with about 400,000 customers. With over 7 million lives covered, the client offers solutions for individuals as well as corporate groups. In addition, monthly mode policies also displayed a different behavior as compared to non-monthly mode policies. To account for these differences, while keeping in sync with business priorities, we developed 5 different models – to be used for scoring the following 5 buckets: Non-monthly policies in the due/grace bucket Non-monthly policies in the first 2 months of lapse Non-monthly policies lapsed more than 2 months ago Monthly policies lapsed more than 2 months ago Monthly policies in the first 2 months of lapse