Max Life uses hi-performance analytics to drive customer engagement, improve seller performance & reduce fraud

Max Life Insurance offers comprehensive long-term savings, protection and retirement solutions through high quality advice based sales and distribution process. The company has always believed in setting new benchmarks in the quality of service and product offerings by adopting the latest in computing technology and new digital data sources that have reinvented the core disciplines of insurers.

Max Life Insurance has a country-wide diversified distribution model spread across more than 1,250 cities which provides need and risk profile based customer solutions and enables customers to take informed decisions. Max Life uses SAS solutions to embed predictive intelligence in functional processes and to raise the bar in strategic decision-making. With SAS , Max Life leverages analytics to manage seller and customer life cycle–seller acquisition and performance, underwriting, customer acquisition, engagement, retention and increasing share of wallet.

Institutionalizing and integrating analytics in the processes has been a game changer for us. This has been possible only with a confluence of leadership support, nurturing quality talent and availability of reliable technology like SAS. Our leadership team
and the functional leaders feel more empowered with the possibilities that these analytics capabilities offers.
Krisnakumar Ramasubramanian Max Life Insurance

Krishnakumar Ramasubramanian
Senior Vice-President and Head, Business Performance Measurement and Analytics

Top-line Focus: Advanced Analytical Models for Boosting Top line

With a large customer base Max Life needed a solution which can process enormous volumes of data with greater speed and reliability, deliver insights that support faster and actionable business decisions.

With SAS Enterprise Miner, Max Life is able to utilize advanced analytical techniques such as Decision trees, clustering, Linear and Logistic Regression along with Machine Learning techniques such as Gradient Boosting, Neural Networks, Random Forest to identify and engage profitable customers and agents that are best aligned with Max Life’s products and offerings. Thus eventually boosting sales performance.

Ability to attract, recruit and engage top notch agents is critical to sustaining and profitable distribution model. “With SAS solutions in place, we are utilizing a gamut of seller information including their demographics, history, current performance and future potential for running deep business analytics” says Praveen Pathak, Vice President, Business Performance Measurement and Analytics. This is aimed at improving seller productivity, retention and growth path.

SAS has also helped us in understanding, engaging and relating with our customers better by building advanced analytical cross-sell and up-sell models.” he adds.

Bottom-Line Focus: Building in Cost-efficiencies for Boosting Bottom line

Policy underwriting, servicing, customer engagement and retention are critical processes of a life insurance company. Underwriting involves determination of risks the insurer can take on and hence underwriting models need to be detailed and comprehensive. Policy servicing through welcome calls and mis-sell checks are resource-intensive processes. SAS was implemented to build automated models for above processes to take decisions quickly and drive them analytically. Using SAS Enterprise Guide and using the inbuilt nodes of EMiner, Max Life is able to carry out advanced analysis, compare various models and score them without worrying about building multiple complex algorithms. Similarly, the reporting and dash boarding processes were also automated to reduce any chances of manual errors and save time.

Using SAS we are not just blending data but are also building advanced statistical and machine learning models with equal ease. This has brought in agility, accuracy and reliability. We see substantial savings in the man-hours for our managers from mundane activities which have now been automated through SAS system” says Krishnakumar Ramasubramanian, Senior Vice-President and Head, Business Performance Measurement and Analytics.  

Comprehensive Digital Marketing Tools to connect offers to the right customers:

The challenge for most insurance companies, given their fixed marketing budgets, is to decide where to allocate resources to obtain the best marketing return on investment. One has to look at a number of psychographic, text, web-log, or survey data regarding prospects to uncover hot spots for effective selling.

With SAS Digital Marketing, Max Life is able to communicate effectively with its target segments by automated mail campaigns thereby reducing considerable manual efforts.

Max Life Insurance

Challenge

  • Deliver on the core principle of “Treating Customers Fairly” by preventing mis-selling, better policy servicing and quicker claims processing.
  • Boosting top-line by improving channel sales performance, predicting and driving customer behavior.
  • Keeping a strict focus on cost-efficiencies and profitability.
  • Validation of customer belief through improved Customer Transaction Assessment scores.

Solution

SAS® Enterprise Miner
SAS® Digital Marketing
SAS® Enterprise Guide
Base SAS

Benefits       

  • SAS solutions are easy to use with a point and click interface, offering the robust delivery capabilities ranging from exploration to machine learning algorithms with an enterprise wide support.
  • Implementing the SAS stack helped in process streamlining which in turn has resulted in improved efficiencies, significant time reduction in model creation, scoring and deployment.
  • Improved agent performance and retention, better customer targeting, effective customer retention, higher customer cross-sell/ up-sell and fraud detection.
  • Automated underwriting models have made strategic decision-making quick and reliable thereby improving profitability.
The results illustrated in this article are specific to the particular situations, business models, data input, and computing environments described herein. Each SAS customer’s experience is unique based on business and technical variables and all statements must be considered non-typical. Actual savings, results, and performance characteristics will vary depending on individual customer configurations and conditions. SAS does not guarantee or represent that every customer will achieve similar results. The only warranties for SAS products and services are those that are set forth in the express warranty statements in the written agreement for such products and services. Nothing herein should be construed as constituting an additional warranty. Customers have shared their successes with SAS as part of an agreed-upon contractual exchange or project success summarization following a successful implementation of SAS software. Brand and product names are trademarks of their respective companies.

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