Pentation Analytics Pvt. Ltd.
Contact person: Shraddha Pandey
Email address: firstname.lastname@example.org
Contact number: +91-7718015718
Asia and ANZ
The Digital Insurer Startup InsurTech Award
ABOUT PENTATION ANALYTICS –
In the journey of decades in Insurance, the founders of Pentation witnessed a specific need of quick turnaround solutions to add value to the organization. This is the point when analytics had a stronger marriage with domain specialization, artificial intelligence and machine learning. Hence, Pentation Analytics was created and marked – an Insurtech, unbundling its offerings with a heavy focus on domain knowledge assets.
PROBLEM STATEMENT -
The industry need was vendors wearing the business hat as well as being skilled in data sciences and technology; vendors with adequate industry knowledge and skills in Data Sciences. Today, Artificial Intelligence and Machine Learning continue to radically transform the worldwide insurance industry, forcing insurance CIOs to think strategically about how new business models and emerging technologies can be applied for market success. CIOs clearly understand the business value of emerging technologies and the use cases, risks and opportunities of each technology across the insurance value chain.
With years of firsthand experience in handling renewals and cross-sales, the founders of Pentation Analytics identified this pressing need of quick turn-around solutions within these processes, which could be better catered to via a productized solution than siloed solutions for overall profitability from processes.
Pertaining to the use-cases of retention and cross-sales, Insurers and Insurance intermediaries spend considerable time and money to acquire their customers, and then run large processes to retain them; however, retaining a profitable customer portfolio remains a challenge. According to the 2017 JD Power Insurance Shopping Study, the top 3 reasons for customer attrition are: Price sensitivity, Channel preferences and service levels, and Communication gaps. These affect renewals and further future sales in P&C, Health and Life Insurance.
Also, there is a variance in the retention and cross-sell rates across the insurance industry, ranging from 25% to 95%. The insurers with retention and cross-sell rates on the lower side form a major chunk, facing lower retention due to the lack of resources and operations to drive retention and cross-sales. Hence, there is a great opportunity in the market for insurers for revenue growth and attaining competitive advantage by leveraging machine learning.
Today, customer value is being handled in silos depending on managers, business segments as well as preferences. Processes pan out on a long-term basis to deliver value over a long period of time. This typically involves large teams of data sciences along with multiple tools for data management, analytics, and related sources.
There is a need for process efficiencies geared towards maximizing customer value – processes which are adaptive to specific use-cases and are transparent in various levels in the organization. Also, the need is to leverage structured and unstructured data, especially customer data from both insurance carriers and intermediaries, and make the most out of it.
Pentation Analytics mitigates customer attrition by leveraging customer data (both Structured and Unstructured) and Artificial intelligence. The solution is Insurance Analytics Suite® - an All-in-one AI-based cloud application. Insurance Analytics Suite® combines predictive renewal insights (renewal risk), conversion optimisation and profitability into an all-in-one self-service platform, covering insights to planning to execution monitoring.
Insurance Analytics Suite® has three layers – Data Model, ML Scoring engine, and Use-cases via dashboards with actionable insights. The three composite layers make the Suite highly scalable for more functionalities and propel collaboration with multiple technology sources to improve usability as per the market needs.
The first layer is the Insurance Data Model, which in itself presents an enriched entity of data source for the insurer, making the organization analytics-ready. Its components are Data Input, Data Quality via Data Imputation Rules, Automated Variable Mapping, Statistical Inferences and Visualization on Raw Data Columns. Data is sourced from multiple sources - policy transaction records, customer interaction data, customer service records, campaign call records for renewals, cross-sell, claims; and policy purchase records.
The next layer is the AI/ML-based scoring engine, which generates scores for retention and cross-sell propensity of the customers.
The third layer comprises of Use-Cases – the results of the scoring engine are viewed via intuitive
Dashboards, which are updated on a real-time basis to provide overview of the entire business as well as a deep dive into specific areas of retention and cross-sells via premium count, business view and sentiment analysis, addressing short-term and long-term business problems. Dashboards enable action support by providing an overall business view through Distribution charts. They provide with visualization of current state (including recent business trends, if applicable) via risk scores and propensity scores for existing customers and new prospects and segment-wise distribution.
What Insurance Analytics Suite® brings to insurers and intermediaries is usage-specific curation of data for processes in the insurance space. The insurer’s data is presented in specialized form via Risk Scores, Score Charts, Distribution Charts, Risk Segmentation and Optimised allocation, and customization of the data-view thus presented.
Insurance Analytics Suite brings into the organization a data-driven culture – its impact is not limited to a specific department, but ranges through IT, operations, sales, underwriting – maximizing its reach to an enterprise scale.
Insurance Analytics Suite® incorporates the following AI/ML techniques –
1. Custom Data Curation specific to insurance – This involves preparation of data via Data speed processing libraries/functions in R.
2. Implementation involves application of machine learning functions using open source libraries available in R, with flexibility to change algorithm parameters.
3. This is followed by Visualization that transforms output scores and input data into informative visualization data structures specific for insurance.
Insurance Analytics Suite® is deploy-able on premise or on cloud.
Phase 1 – Pre-execution preparation
- Resourcing allocation for the Project and List of Needs for on-boarding given to Insurer
- Project Kick-off and Deployment of Resources required on-site or as needed
- Local Machine and Facility Resources allocated for use with the Insurance Analytics Suite®
- Specify Data Tables and Variables to fetch from the Insurer’s Databases
- Migrate Data onto Broker’s local machine and pre-process based on Cleaning rules, given by Insurer
Phase 2 – Execution
- Install the Insurance Analytics Suite® onto client’s local machine
- Load and Execute the Insurance Analytics Suite® for Model Building
- Analyze Insurance Analytics Suite® Model output for validation and Final Outputs for Roll-outs
Phase 3 – Post-execution
- Roll-out the Outputs and support the Insurer on Business Execution of new Campaigns
- Present Business Insights and Impact to Sr. Leadership of Insurer.
Insurance Analytics Suite has seen quick wins in the market. Pentation Analytics was selected among the top 10 Insurtechs globally (among 4000 applicants) for Startupbootcamp’s Hartford Insurtech Hub inaugural accelerator program.
Post the completion of accelerator, Pentation Analytics launched operations at Hartford, CT. http://www.courant.com/business/hc-biz-hartford-insurtech-accelerator-20180418-story.html
Pentation also secured 2 pilots post IGNITE- Hartford Insurtech Hub Demo Day 2018.
This apart, we have contracts with 4 leading insurers, with increase in retention rates ranging from 3% to 12% depending on the risk segment.
Pentation Analytics was also selected among the 40 tech companies for the fifth edition of NASSCOM’s flagship project InnoTrek 2018 in Silicon Valley. Post participation in InnoTrek, we have formed an official member of the NASSCOM 10,000 Startup Program.