ensuring big data is supporting financial analytics gaining a thorough understanding of big data in...

Ensuring big data is supporting financial analytics

• Gaining a thorough understanding of big data in order to understand analytics

• Transforming unstructured data into structured intelligence

• Using big data to predict client behaviour

Bhavani Raskutti @ Pacific Brands

Agenda

• Big data

• Unstructured data

• Framework for embedding financial analytics – data analysis leading to decisions that

– impact company financials

Bhavani Raskutti @ Pacific Brands

Big Data“Big data” is high-volume, -velocity and -variety information assets that demand cost-effective, innovative forms of information processing for enhanced insight and decision making.

-- Gartner Inc. 2001

• Volume: Number of entries (rows) – NOT attributes (columns)

• Velocity: Rate of change, usually rate of arrival of rows– Impacts volume

• Variety: attributes (columns) of entries– Structured:

• Transaction data: value, timestamp, type, location, …• Customer data: gender, age, occupation, …

– Unstructured: • Text: Customer interactions, blogs & twitters about the company …• Image: Customer signature, photo, ….

Big Data

Predictive Analytics to Make DecisionsPredict fraudulent credit card transactions

1. Learn a model from historical data

Know

n Ca

tego

ries

NO

Kno

wn

Cate

gorie

s

Classification

Clustering Classification

2. Categorise new data to make decisions

Back-end process Time consuming Built from sampled data

Volume NOT an issue

Models simple Quick process

Velocity & Volume NOT an issueN

ew d

ata

Big Data

Impact of Variety on AnalyticsIndustry Structured Data Unstructured Data Analytics

MaturityFinance • Transactions

• Customer & Product• Call centre

• Twitter/blogs/complaints

Wholesale / Retail

• Inventory, sales, POS• Customer & Product• Sourcing & supply chain


Utilities (gas, electricity, …)

• Usage data• Customer & Product• Sensor data


Telecom • Call records• Customer & Product• Call centre

• Twitter/blogs/complaints• Inbound emails/SMS• GPS data

Web services • Usage• Product & subscriber• Call centre

• Twitter/blogs/complaints• Inbound emails• Click stream transactions

Benchmark

Big Data

Structuring Unstructured Data Unstructured Data

Get freeform

source text

Load sentiment word list

love, best, … hate, worst, …

Score sentiment:+1 for positive words-1 for negative words Normalise if needed

1. Sentiment Analysis 2. Topic Detection

Use in Business:For model buildingCompetitor comparisonsMood change over timeAddressing negative scores

Get freeform

source text

Load stop words list:the , on, of, a, an, by, …

Create clusters with term frequency matrix

Use in Business:For model buildingMajor customer issuesImpact of initiatives

Determine clusters of interest and label

Learn cluster models for classification

Business input

Sentiment Analysis OutputUnstructured Data

No sarcasm detection

Topic Detection OutputUnstructured Data





Wholesale / Retail










Benchmark

Big Data

Variety NOT an issue Financial Analytics NOT impacted by Big Data





Wholesale / Retail










Benchmark

Big Data





Wholesale / Retail










Benchmark

Big Data

Do BIG analytics with enough data!!

Decision

• Big $ impact• Many people• Timely

Framework for Embedding Analytics Initiative

Insight

Pilot

Data

Deploy

• Just the facts needed for decision making

• Prioritise entries• Support actioning

• Sell to whom, what & $$• Ordered by $$

Framework

Right People

$

Decision Support Initiative for Wholesale Sales

Demand

In-s

tock

%

· R1· R2

Demand

Sell

Rate

Example of Additional Support for ActioningFramework

Sell rate vs Consumer Demand plot • Each point is a store• R1 & R2 are comparable retailers• Values for the same product

Possible reasons for difference• Competing product at R2• Pricing at R2 vs R1• Lack of stock at R2

Decision

• Big $ impact• Many people• Timely

Framework for Embedding Analytics Initiative

Insight

Pilot

Data

Deploy

• Just the facts needed for decision making

• Prioritise entries• Support actioning

• Sell to whom, what & $$• Ordered by $$

Framework

• Automated feed• Objective Data• Most specific • Complete

• POS feed from retailers• SKU & store master

• Pick champions early in the process

• Develop pilot• Validate outputs from

pilot• Iterate pilot with

champions until it is accepted

• Automate • Helpdesk• Training

Right People

$

Decision Support Initiative for Wholesale Sales

Conclusion• Big data is not an impediment to analytics

• Unstructured data can be structured using sentiment analysis & topic detection

• Key success factors for doing BIG analytics is to have the right people to choose–Right decisions–Right insights–Right data –Right process to pilot & deploy

Questions?

ensuring big data is supporting financial analytics gaining a thorough understanding of big data in...

Documents