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Colm CareyTIBCO NOW 201804-06 Sep 2018 – Las Vegas, Nevada

AA Ireland - Combining Advanced Data Analytics and Complex Event Processing using TIBCO

1910AA begins service in Ireland

1924Service revived in Ireland after ‘troubles’ end

1911AA signposting of Irish main roads

1950Membership reaches 19.5k

1945AA handling Int. driving licenses for Irish State

1983AA launches Home Start – 81k Members

1977AA Launches Car & Home Insurance

1989AA Roadwatchservice launched

2000AA launches aaireland.ie & aaroadwatch.ie.– 300k customer base

AA Ireland – A Short History

2016AA Ireland separates from parent company

2010AA turns 100 – 600k customer base

AAI Vision Statement & Data Value Optimization Phases

“Optimise business efficiency and customer engagement, whilst maximising data value with real time business insights by ensuring data is compliant, clean, accurate and trusted with easy access and readily available for all.”

DATA VALUE

DataCollection Reactive

Post Event

Analysis

PredictiveAnalyses(Machine Learning)

Self-Learning

Algorithms (AI)

BusinessOptimization

(Optimization/Neural Network)

Phase 1

Phase 2

Phase 3

1.4 Data Quality

1.1 Vision and Strategy

1.5 Data Security

1.2 Data Governance

2.1 Fraud Engine

1.3 Price Optimisation

2.2 Segmentation

3.2 MDM

2.3 Lifecycle Management

3.1 Capacity Prediction

2.4 Reporting & Analytics

2.5 Data Infrastructure

Real Time PricingTrusted

Data

Compliance

2.2 CRM

Customer InsightsTrusted

Data

Compliance

Business EfficiencyTrusted

Data

Compliance

1.6 Data Standardisation

AAI Data Vision Statement:

Data Value Optimization Phases

Software Options – Why TIBCO

Industry Standard Software

Industry standard – comfort & stability

Already began to build Pricing solution –staff familiar with software

Safe option – trusted software – process orientated

Out of the box software – rigid

Lack of scalability (software) – Pricing solution only

TIBCO Software

Huge opportunity– think it, build it (holistic)Very powerful/event based – Predictive MI/Fraud/Segmentation /CRM

IT Enterprise Service team building on TIBCO – big fans

TIBCO very supportiveControl – power for business people

Resource required to build – project timingsHybrid resource (Quant/Pricing/Developer/UAT)IT/Pricing/Quant responsibilities & governance

Ongoing resource requirements Uncertainty – what if goes wrong?

Implementation – Staffing and Training

How to enable a team of Quantitative Analysts to build our solutions

• Started with TIBCO Training in Spotfire and StreamBase

• Consultants were on site during the start of the project and helped with:• Architecture design, • Building the first StreamBase flows, • Writing and integrating TERR scripts,• Setting up Spotfire Reports,• … and they taught team members in the process!

• Ring-fenced team and good communication between different teams within the company is crucial

Pricing/

Analytics

IT Enter-prise

Service

UAT

Solution Design - Now

Insurer Schemes

Policy Administration

TheAA.ie

Inte

grat

ion

Plat

form

(BW

6, E

MS)

StreamBase/TERR

Datawarehouse

Data Store (Models, Reports)

Spotfire Server

Automation Services

Pricing/Analytics

team

Auto Data Banding

Optimal Pricing

e.g. age “37” becomes “30-39”

Live pricing and automatic model

performance report - re-fit once

a week

“Did the model change?”

“Which customers are affected, and

how?”

Solution Design – Optimised Pricing in Detail

Quotewith max.

Commission

SegmentData

(GLM)

Randomised Discount Flex

Set Base Discount

Final Price

Output

ONLINE

Re-fit Predictive Model and Send

Segmented Report

Create Optimal Price Table based on targeted outcomes and limited parameters

- Max. Income (1 yr.)- Max. Income (3 yr.)- Max. Sales Volume

- …

OFFLINE*

*On a schedule and manually adjustable via

Spotfire

Spotfire as a Generalised Linear Model (GLM) Builder

• No coding required, easy to learn for analysts from varied backgrounds

• Easy feature engineering with Spotfire visualisations and marking (see demo video)

Define GLM type

Coefficient table

Visualisations of the selected

factor

Select factors to include in

model

Spotfire as a Generalised Linear Model (GLM) Builder

Direct link to data that has been consistently

banded by the StreamBase banding engine

(age “37” becomes “30-39”)

No more data formatting woes

Time consistency and factor exclusion testsTools to improve and evaluate the model

Model diagnostic page (ROC, AUC, Lift curve,

Confusion Matrix,…)

Cramer’s V correlation test

Logging Audit proof

Deployment of model objects to database

→ accessible by StreamBase application

Streamlined process for launching a new model into

the live flow

Automated Intelligent Reports

• Model gets updated by a TERR script on a schedule set in StreamBase (e.g. once/week)

• Automation Services sends Spotfire report by email

• Decision to promote or not promote the new model to test (→ live) can be made

• Insights can be gained from model changes

Beyond GLMs

• TERR/Spotfire/StreamBase can be used to implement other Machine Learning techniques, e.g. for clustering/segmentation

• Flexibility to modify or build solutions suiting our business needs

• Our teams have built up significant expertise over the last year and are now mostly independent from consultant support

• … our imagination is the limit

Solution Design - Future

Insurer Schemes

Policy Administration

TheAA.ie

Inte

grat

ion

Plat

form

(BW

6, E

MS)

Datawarehouse

Data Store (Models, Reports)

Spotfire Server

Automation Services

Automated Reporting

Pricing/Analytics

team

Auto Data Banding

Optimal Pricing

Fraud

CRM Models

Segmentation

Live X-Sell

Call Centre

Marketing

“When can we expect capacity and which

customers should we contact?”

Predictive Capacity

Embedded Customer Value

StreamBase/TERR

Intelligent Cross-Product Indicative Quotes – Seamless Premium Predictions…

Home Insurer Schemes

Inte

grat

ion

Plat

form

(BW

6, E

MS)

StreamBase/TERR

AA Home Data

Geo-LocationExternal Data

Auto Data Banding

Optimal Pricing

Live X-Sell AB

• AAI Motor Ins. Journey has 79 questions – 14 overlapping with Home Ins. Journey

• Home Ins. quotes expensive – average CPQ c€60

• Challenge: Give every AAI Motor quote a Home Insurance quote

• Home Quote to be as accurate as possible with no latency impact to Motor Journey – large computation challenge

• TIBCO StreamBase perfect tool to address challenge

Intelligent X-Sell:

Web

Agent

Live Fraud Prevention – Identify Application Fraud in Live Environment…

Insurer SchemesIn

tegr

atio

n Pl

atfo

rm (B

W6,

EM

S)

StreamBase/TERR

Fuzzy Customer Matching

Previous Quote Details

Auto Data Banding

Optimal Pricing

Fraud

• Fraud adds c€60 to the average Motor Ins. Premium

• Application fraudsters are higher claims risk – up to 55% increase in Claims Cost

• Challenge: Ø Block multiple QuotersØ Block previous Bad DebtØ Target quote manipulation (Application Fraud)Ø No latency impact on Motor journey

Live Fraud Prevention:

Web

Agent

Live X-Sell

0%6%

13%

27%

55%

0%

10%

20%

30%

40%

50%

60%

0 1 2 3 4+

Incr

ease

in C

laim

s Cos

t(v

. 0 M

anip

ulat

ed Q

uote

s)

Number of Manipulated Quotes

Increase in Claims Cost by Number Manipulated Quotes

Spotfire Reporting – B2B BI

Tailored reports of breakdown causes similar to the below can be made available to B2B customersThe next step is Predictive Management Information (MI) – immediate insight into what is causing the trend

Positive Business Outcomes

• Optimize Trading PerformanceØ continually analyze for opportunities/risks and automatically

report/react

• Real-Time Predictive AnalyticsØ live business insights – democratize Data/MI/Insight

• Complex Event Processing PlatformØ Low code environment, enabling rapid build and deploymentØ Highly responsive and scalable environment