Transamerica developed a product recommender platform using big data and machine learning to increase customer satisfaction and cross-selling opportunities. The platform ingests customer data from various sources and uses Hadoop technologies like Hive, HBase, and Spark for storage, processing and predictive analytics. Models are built using H2O for tasks like binary classification to recommend burial insurance, term vs universal life insurance, and regression to predict policy face amounts and premiums. A proof of concept user interface was also developed to demonstrate personalized recommendations to customers based on their profile.

1. 1
TRANSAMERCA’S PRODUCT RECOMMENDER PLATFORM
Vishal Bamba – VP, Innovation & Architecture
Nitin Prabhu – Manager, Innovation & Architecture

2. 2
Transamerica’s Business
• Investments & Retirement
– Retirement and Benefit Plan services to employers/employees
– Mutual funds and variable annuities
– Mission to help people save and invest wisely to secure their
retirement dreams, the I&R business unit serves more than 3
million retirement plan participants across the entire spectrum of
defined benefit and defined contribution plans.
• Life & Protection
– Term and Perm insurance products
– Medicare supplement, long term care, accidental death, final
expense
– Mission to protect what you’ve built, secure what’s next.

3. 3CONFIDENTIAL & PROPRIETARY: INTERNAL USE ONLY
• Transamerica offers variety of products in Life,
Investment and Retirement space.
• Choosing/ Recommending a right fit product is
a complex decision in our Product offerings.
• Leverage Big Data + ML to make product
recommendations
• Increased customer satisfaction
• Cross sell and Upsell opportunities
Motivations

4. 4CONFIDENTIAL & PROPRIETARY: INTERNAL USE ONLY
Enterprise Big Data Hub
Datamarts
OLAP Cubes
Data
warehouses
Tableau
Datameer
SAS
Excel
VisualizationETL/Data
Integration
Informatica
Datameer
Sqoop
Interactive SQL
Cloudera Impala | Hive | Spark
Search
Cloudera Search | Apache Solr
No-SQL
Apache HBase
In Memory
Impala | Spark | H20 | Datameer
360° Customer Intermediaries
Time Series Click Stream
Predictive Analytics
H20 | Datameer | SAS-VS
Customers
Intermediaries
Prospects
Clickstream
Flat Files
CRM
Enrichment
Logs/Events
Social Media
INPUTS

5. Idenity Resolution
Data QualityIngest & Profile
Cleanse &
Transform
Standardize / cleanse
phone, email,
address
DOB
BDE
Tool: Analyst Tool
Source 1
Source n
Masking
Cleanse,
Standardize, Mask
Personal Data
BDE
Tool: Developer
BDRM
matching/linking
(assign cluster ID)
Pre BDRM
Managed ViewsPre BDRM
Managed ViewsPre BDRM
Managed Views
Pre BDRM
Hive
BDRM
Hbase
Post BDRM
Managed ViewsPost BDRM
Managed ViewsPost BDRM
Managed Views
Profile
Data Discovery
Design/Define rules
Build/Define Ref
Table
BDE
Tool: Analyst Tool
NCOA
process
Data Pipeline

6. 6CONFIDENTIAL & PROPRIETARY: INTERNAL USE ONLY
Response variable Type
Recommend burial insurance ? Binary Classification
Recommend term insurance or universal
life insurance ?
Binary Classification
What is the face amount for burial
Insurance?
Regression
What is the annual premium for Burial
insurance?
Regression
Predictor variables Type
Age of insured Int
Age of policy holder Int
Gender of insured Categorical
Applicants zip code Categorical
State of residence Categorical
Data for the Model

7. 7
Models generated in H2O
Algorithm : GBM
Model Type: Binary Classification
# of Trees : 50
Max Depth : 5
AUC on validation: 0.88
Algorithm : GBM
Model Type: Binary Classification
# of Trees : 50
Max Depth : 5
AUC on validation: 0.85
Burial Insurance Term vs Universal

8. 8
Models generated in H2O
Algorithm : GBM
Model Type: Gaussian Regression
# of Trees : 25
Max Depth : 5
R2 on validation: 0.377
Algorithm : GBM
Model Type: Gaussian Regression
# of Trees : 50
Max Depth : 5
R2 on validation: 0.515
Burial Insurance

9. CONFIDENTIAL & PROPRIETARY: INTERNAL USE ONLY
Policy Recommender
About You
Burial Coverage
Major Coverage
Your Age:
Your Gender:
Your State:
Your ZIP code:
Number of dependents:
Household size:
Annual Income:
Annual Premium:
Policy Face Value:
$1,300
$150,000
Click to Recommend
15-year Term Life Insurance Policy
$470 (25th percentile) $1500 (75th percentile)
$1300 (You)
?
?
$110k (25th percentile) $300k (75th percentile)
$150k (You)
Annual Premium:
Policy Face Value:
$350
$13,000
$204 (25th percentile) $760 (75th percentile)
$350 (You)
$7k (25th percentile) $15k (75th percentile)
$13k (You)
Proof of concept-UI
35
Male
CA
94043
2
4
75000

10. 10CONFIDENTIAL & PROPRIETARY: INTERNAL USE ONLY
Thank You!!