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1PKC Advisory
Advanced Analytics
2PKC Advisory
Overview
3PKC Advisory
PKC Advisory – Differentiated Value Proposition
Incepted in Kuwait and focused on the MENA region, we offer a breadth of
regional experience. We have executed 700+ assignments for 100+
clients in the region
Regional
Experience
Having worked with numerous clients across sectors, we offer a depth of
operational expertise. Our long term engagement model ensures that we
are part of client teams and support them in implementation and execution
Deep Operational
Expertise
Our advisory services are focused on helping clients make informed
decisions and perform better through people, process and
procurement related improvements. We also provide innovative solutions
with our alliance partners
Complementary
Service Offerings
Our service offerings and deliverables are tailor made to meet the specific
needs of individual clients. We work collaboratively and enhance client
capabilities through effective knowledge transfer
Customized
Approach
Our robust governance, standardized procedures and control mechanisms
lead to increased efficiency and ensure delivery of the highest quality
with utmost speed to our clients
Robust Governance
& Controls
Our unique onsite-offsite model, allows us to hire the best talent from
globally recognized institutions and organizations, offer offsite execution
prowess and pass on the cost arbitrage and productivity gains to our clients
Competitive
Positioning
4PKC Advisory
Advanced Analytics Service Offerings
5PKC Advisory
Advanced Analytics Service Offerings
Advanced Analytics has gained prominence as a key instrument to explore new business opportunities, drive efficiency and to
support faster & better decision making across functions. It amalgamates sophisticated statistical techniques, business concepts
and technology tools to predict events and behaviors in order to drive sustainable competitive advantage for an organization.
Our wide spectrum of Advanced Analytics Solutions across Customer, Social Media, Operations and Risk enable our clients to
uncover hidden patterns & correlations and take data driven decisions.
▪ Core Model
Development
▪ Model Validation
▪ Model Monitoring
▪ Model Risk
Governance &
Framework
Development
Credit Risk &
Regulatory
Analytics
▪ Customer
Identification &
Acquisition
▪ Customer Growth &
Retention
▪ Customer Value
Enhancement &
Engagement
▪ Measurement &
Analysis
Customer
Analytics
▪ Customer Digital life
cycle
▪ Campaign
Designing
▪ ROI Optimization
Web & Social Media
Analytics
▪ Optimization
Analysis
▪ Root Cause
Analysis
▪ Forecasting –
Loss/Demand/
Supply
▪ Data Analytics and
Deep Dive
Operational
Analytics
6PKC Advisory
Customer Analytics
Customer analytics generates valuable insights pertaining to Customers, Products & Distribution Channels and helps the
organization direct their efforts in maximizing revenue & enhancing profitability. PKC Advisory offers bespoke and in-depth
analysis across customer life cycle driving higher customer acquisition & wallet share, low churn and thereby significantly
enhancing customer life time value.
▪ Customer Targeting &
Segmentation
▪ Product Recommendations
▪ Customer Campaigns
▪ Cross-Sell & Up-Sell Models
▪ Customer Churn Models
▪ Channel Performance Analysis
▪ Customer Behavior Analysis
▪ KPI Identification &
Dashboard Creation
▪ Conversion and Response
Rate Enhancement
▪ Customer Satisfaction
Analysis
▪ Net Promoter Score (NPS)
▪ Customer Engagement
Programs
Customer Identification & Acquisition
Measurement & Analysis
Measurement & Analysis
Strong Branding and Customer Loyalty
Updated Information on Customer Behavior
Services Offerings Benefits
Customer Growth & Retention
Higher Growth in New Customers across
portfolios
Decreased Customer Attrition
Increased Wallet Share
7PKC Advisory
Web & Social Media Analytics
The fast paced adoption of various digital platforms by both organizations and customers has resulted in the need to study
customer digital footprints and social media behavior to grow & retain customers and increase brand awareness. PKC Advisory
helps its clients in their Digital Marketing efforts by understanding the web & social media data with visit path analysis, visitor
behavioral analysis, design and tracking of digital campaigns to increase customer base at low costs.
Data Gathering
Customer Behavior
Segmentation
Gathering customer level data – digital (Social Media)
and offline data (Client’s data)
Study customer behavior, payment, preference and
purchase pattern
Undertaking customer segmentation to maximize ROI of
campaign
Campaign Design
Campaign
Optimization
Tracking
Design campaign as per the customer segments and
preferences
Studying campaigns through Design of Experiments
(DOE) and selecting the best campaign on basis of ROI
Identifying KPI and tracking customer behavior and ROI
Approach Benefits
Higher ROI per
Campaign
Higher
Customer
Engagement
Increased
Customer
Acquisition
Brand
Awareness
ROI and Conversion Rate OptimizationCampaign Designing Customer Digital life Cycle
▪ Customers Digital Visit Analysis
▪ Visitor Behaviour Analysis
▪ Campaign Design as per Customer
Segments and Targets
▪ Digital Ads Design as per Customer
Preferences
▪ Optimizing Campaigns to maximize ROI
on each Campaign
▪ Increase Hit / Conversion rate
Service Offerings
8PKC Advisory
Operational Analytics
Advanced Operations Analytics can help in solving problems pertaining to optimization of distribution network and offer solutions
for sales prediction, simulation and comparison. PKC Advisory assists its clients to process and convert data into useful analysis
and models through Advanced Analytics tools & technologies and bring out actionable insights across the value chain.
Service Offerings Benefits
Higher Profits by
Targeting Key
Pain Areas
Better Decision
Making
Early Prediction
of Future Demand
and Supply
Competitive
Advantage in
Market
Higher Customer
Satisfaction through
Root Cause Analysis (e.g. TAT, Complaints etc.)
Analytical
Approach
Objective
Setting
Data
Gathering Analyses Insights Action Plan
▪ Future Profit & Loss
forecasting
▪ Demand and Supply
Forecasting
▪ Data Gathering and
Transformation
▪ Deep dive and Actionable
insights on operations
▪ Utilization Analysis of
existing resources
▪ Cross Channel Cost and
Sales Practice Analysis
▪ Data driven Root Cause
Analysis on business
problems
▪ Findings solutions and
developing action plan
Optimization Analysis Root Cause Analysis
Forecasting Data Analytics and
Deep Dive
9PKC Advisory
Credit Risk and Regulatory Analytics
PKC Advisory assists its clients in developing customized and robust Credit Risk Models for Acquisition, Accounts Management
and Collection and Regulatory Models including PD, LGD & EAD Models. We also assists in Calibrations, Monitoring, Validation
and Annual reviews of existing and new models specific to each Client‘s internal policies & procedures in-line with industry best
practices & regulatory requirements.
▪ Acquisition/Applications
Scorecards
▪ Behavior/Accounts
Management Scorecards
▪ Collections & Fraud Models
▪ IFRS 9/CECL Development
▪ PD, LGD & EAD Models
▪ Insurance Fraud Claim
Analysis
Core Model
Development
Model
Validation
Model
Monitoring &
Annual Reviews
Model Risk
Governance
▪ Out of Time/ Out of Sample
Validations
▪ K fold Cross-
Validation/Bootstrapping
▪ Back Testing
▪ Documentation and
Submission
▪ Quarterly Model Monitoring
▪ Monthly Data Risk/ Early
Warning Indicators reports
▪ Annual Reviews of Models
▪ Analysis on Model
Performance
▪ Governance Program
Development
▪ Process Design as per
Governance rules
▪ Risk Ranking of Models
▪ Development, Validation &
Execution of Governance
Framework
Approach
▪ Data Mapping
▪ Variable Selection
▪ Model Development
Development
▪ Generating insights
▪ Findings areas of
improvement
▪ Recommendations
▪ Quarterly Model review
▪ Performance tracking
▪ Governance submission
Validation
▪ Cross Validation
▪ Model Comparison
▪ Calibration
Monitoring & Annual
Reviews
Insights &
Recommendations
Service Offerings
10PKC Advisory
Case Studies
11PKC Advisory
Case Studies – Customer Analytics
Behavior & Lifestyle Data
Demographic Data
Cross Product
Previous
Response Data
Final Model Development Dataset
Predictive Modeling : Target Variable Response Rate
(1= Responded Positively , 0 = No response)
Predictive Modeling for Cross Sell Campaign
Model Performance & Results
Model Implementation & Campaign Design
SegmentsScore
Range
Response
RateResponder Total
%
Response% Total Strategy Contact Strategy
1 > 2 % 6.80% 2400 30,000 8.0% 30% PriorityTele Call, Mail,
Email, Mobile
2 1 % - 2 % 1.30% 1250 40,000 3.1% 40% Cross-SellEmail & Mobile
Only
3 < 1 % 0.40% 350 30,000 1.2% 30%Do Not Cross
SellDo not Contact
Total 4000 100,000 4.0% 100%
Cross Sell Modeling
0
20
40
60
80
100
1 2 3 4 5 6 7 8 9 10C
um
ula
tiv
e %
Resp
on
ders
Deciles
Lift Charts
% Cum Responders Baseline
Our Client
A Retail Hub selling products through stores and online channels
The Business Situation
The Client wanted to improve cross-sell to existing customers.
They were already running direct marketing campaigns but the
incremental gains observed were marginal. They required PKC
Advisory’s assistance to improve the effectiveness and efficiency
of the campaign.
Our Role
PKC Advisory undertook a predictive modeling to identify existing
customers who have high propensity to purchase another
product, determine the next best product and preferred channel of
contacting. The analysis covered:
▪ Customer Segmentation on basis of previous response rate of
campaigns, needs, transactional and behavioral data
▪ Development of propensity models based on logistic
regression to cross-sell products and determine the target
segment. This narrowed the number of customers contacted,
thereby reducing the campaign costs and increasing
conversion rates
▪ Ascertained cross-sell propensity to purchase across product
category and targeted only those account with highest
propensity to respond
The Value We Added
Using Predictive analytics, the Client was able to deliver right
product and services at right time. Cross-sell response rate
increased to 8% with reduced campaign cost and increased
customer wallet share.
12PKC Advisory
Case Studies – Customer Analytics
Hig
h P
rob
ab
ilit
y to
Ch
urn
Med
ium
to
Lo
w
Pro
bab
ilit
y
Model ROC Curve Threshold Plot for LR
Churn Probability of Existing Customers
Churn Model on Existing Customers
Our Client
A MENA focused Telecom Company
The Business Situation
The Client was experiencing high churn under different plans for
last one year and required analytics to enhance customer
retention.
Our Role
PKC Advisory developed a detailed model to identify customers
who are at high risk to churn and recommended proactive
measures to retain them. Our approach included:
▪ Analyzing 6 months of customer churn data including
customer demographics datasets, package details, transaction
history, customer satisfaction score, customer activity etc.
▪ Creation of additional variables like number of complaints in
last 6 months, data plan changes and study of behavioral
details like decrease in usage, removal of value added
services, delayed payments etc. to study additional effects
▪ Building logistic regression predictive model to score
customers on the probability to churn from business
▪ Creation of customer segments on basis of churn score for
better customer targeting and retention
The Value We Added
The predicted models helped the Client retain customers and
Identify the key factors for churn and helped develop a retention
strategy. e.g. Customers with high churn probability were offered
attractive bundles, internet data & call offers, free subscription of
entertainment packages etc.
Ascertaining Churn Probability to develop proactive
measures to enhance Customer Retention
13PKC Advisory
Case Studies – Web & Social Media Analytics
Customer Online Data
Analysis
Campaign Design (DOE)
Launching Campaign on Social
Media
Optimizing Campaigns
Tracking Conversion
Rate
Web Analytics Dashboard – Campaign Tracking
Our Client
A GCC focused large Media house
The Business Situation
The Client wanted to identify and acquire new subscription
customers for online live streaming of cricket matches through
digital campaigns across Facebook, Instagram and Google.
Our Role
PKC Advisory undertook analysis of existing customer data
including their preferences, age groups, online behavior etc..
Basis the analysis, multiple digital campaigns across segments
were designed and implemented, which were tracked and
reported using a dashboard. Analysis covered:
▪ Understanding the online behavior for both new and old
customers, their preferences & interests, viewing pattern and
previous campaign response rate
▪ Designing campaign on available data, Hypothesis testing as
per customer requirement and designing of the target ads to
be used on social media
▪ Launching of campaigns on social media, tracking their
performance and cost of campaigns
▪ Regularly optimizing the campaigns as per the higher
conversion rate & least cost and successfully generate leads
for acquisition of new customers
The Value We Added
The analysis helped Client to develop focused marketing strategy
to target identified customer segments to increase customer
acquisition and increased conversion rate.
Web campaigns to acquire new customers through social
media channelsWeb Campaign Design
14PKC Advisory
Case Studies – Operational Analytics
0
20
40
60
80
Mar-18 Jun-18 Sep-18 Dec-18 Mar-19 Jun-19 Sep-19 Dec-19
NO
OF
FO
OD
TR
UC
KS
QUARTERLY DEMAND
Forecasting Demand of Food Trucks
Food TrucksForecast(Food Trucks)Lower Confidence Bound(Food Trucks)
0
10
20
30
40
50
60
70
Mar-18 Jun-18 Sep-18 Dec-18 Mar-19 Jun-19 Sep-19 Dec-19
NO
OF
PIC
K-U
P V
AN
S
QUARTERLY DEMAND
Forecasting Demands of Pick-up Vans
Pick-up Vans
Forecast(Pick-up Vans)
Lower Confidence Bound(Pick-up Vans)
Our Client
A Logistics company with large customer base
The Business Situation
As a part of the Client’s efficiency improvement initiatives,
PKC Advisory was mandated to assist in forecasting demand and
supply of services.
Our Role
PKC Advisory worked closely with the customer service
department to understand & retrieve data from the queue
management system. This included data for number of inquires,
type of inquiries, demand pattern, time taken across service
categories, time zones, demographic profile etc.
This was used to forecast the demand of services in next 6
months under different categories using the following approach;
▪ Gathering of last one year of customer, market and suppliers
data including seasonal and annual fluctuations and timings
▪ Studying historical demand trend in each of service segments
▪ Forecasting future demand including the seasoning & annual
effect and setting upper and lower limits of forecast
The Value We Added
Accurate forecasting led to optimum utilization of existing
resources, opportunistic augmentation of capacity basis demand
spike, significant drop in waiting time and cost savings.
Data analytics for improving forecasting efficiency for a
Logistics companyForecasting
15PKC Advisory
Case Studies – Regulatory Analytics
Data Quality Review
Model Methodology
Review
Variable Selection Validation
Model Evaluation of All
Models
Macro-Economic Scenarios Validation
Risk Staging
Back Testing Validation
Overall Validation
Review Submission
IFRS 9 Model Calculations
S.No COUNTRY Variable 1 Variable 2 Weightage 1 Weightage 2 Z FACTOR VAR 1 Z FACTOR VAR 2 Z-FACTOR
1 Algeria GDP Exports 0.8 0.2 -1.44 0.41 -1.07
2 Australia GDP Investments 0.8 0.2 0.00 0.00 0.00
3 Austria Unemployment rate Inflation 0.8 0.2 0.00 0.00 0.00
4 Azerbaijan Expenditure Exports 0.8 0.2 0.00 0.00 0.00
5 Bahrain Exports Net Lending 0.5 0.5 -0.23 -0.82 -0.52
6 Bangladesh Net Debt Exports 0.8 0.2 0.00 0.00 0.00
7 Belgium GDP Unemployment rate 0.8 0.2 0.00 0.00 0.00
8 Canada Inflation Investments 0.9 0.1 0.27 0.79 0.32
9 China Revenue Investments 0.4 0.6 0.00 0.00 0.00
10 Denmark Inflation Unemployment rate 0.4 0.6 0.00 0.00 0.00
Our Client
A GCC focused large Commercial Bank
The Business Situation
The Client had developed its IFRS 9 model and required
independent validation. The model validation was undertaken as
per the guidelines and calculation to measure Expected Credit
Losses (ECL).
Our Role
PKC Advisory validated the IFRS 9 model at multiple levels and
touch points to calculate ECL. The approach included:
▪ Reviewed all datasets used in different models and logics for
data set creation
▪ Methodological review of all IFRS9 credit risk models
including PD, LGD and EAD models
▪ Thoroughly reviewed the variable selection process and their
predictive power with dependent variable
▪ Undertook performance evaluation of models on various risk
measures like KS, Lifts and Accuracy level
▪ Macroeconomic variables scenarios testing and reviews
▪ Risk stage determination and staging thresholds robustness
The Value We Added
PKC Advisory identified and bridged the gaps in methodology as
per guidelines & calculation logics and validated the model
successfully. Client was able to submit the model which met all
governance requirements.
IFRS 9 Model Validation of Retail Commercial Bank IFRS 9 Model Validation Process
16PKC Advisory
Case Studies – Credit Risk Analytics
SamplingModel
Development
Reject
InferenceScorecard
Scorecard Development Process
Category Characteristics Attributes PointsCustomer
Score
Payment History
No. of Months
since most
derogatory
record
No Public
Records 70
400-5 10
"6-11 20
12-23 30
24+ 40
No of time 30+ days
Delinquent in last 6
months
Number of Time
gone 30+
delinquent
< 0 90
900-1 50
1-2 15
2-3 0
Outstanding Balance
Outstanding
balance in Dollar
($) value
No revolving trade 25
50
0 40
1-100 60
101-200 55
201-500 50
500-1000 25
1000 + 10
Month on BookNumber of
month on books
< 6 month 20
356-12 months 25
12-18 months 35
18 months + 45
Acquisition Scorecard
Our Client
A Retail focused Commercial Bank
The Business Situation
The Client intended to build Challenger Scorecard for personal
loans as current scorecard performance was deteriorating.
Our Role
PKC Advisory developed a retail acquisition credit scoring model
based on multi-Logit regression model. The approach included:
▪ Detailed study of existing customers’ one year development
data and 18 months performance data containing Customer
behavior data, Portfolio data, Bureau and Delinquency data
▪ Data wrangling including – Missing Value imputation, Outlier
treatments and Customer segmentation
▪ Variable selection through Clustering, IV and Correlation
analysis and finding relevant variables and Reject inference
▪ Developing and selecting the best model out of various
models that had the highest Accuracy, KS and ROC to predict
default probability of applicants
▪ Identification of default cut-off rate for model based on
management discussion
▪ Validation of model & further calibration
The Value We Added
The Client embedded the scoring model in its existing retail credit
appraisal process to ascertain credit worthiness of prospective
retail clients.
Development of Retail Acquisition Scorecard for a
Commercial Bank
17PKC Advisory
Our
Esteemed
Clients
18PKC Advisory
Our Esteemed Clients
19PKC Advisory
PKC
Advisory
Team
20PKC Advisory
Team Profile
Payal Soni - Chief Operating Officer
Bhupinder Singh - Senior Director
Vinay Gupta - Director Amit Chandra - Principal Consultant
Payal has a total work experience of over 18 years (including 14
years at PKC Advisory). Payal is a CFA Charter holder from CFA
Institute, USA and holds Masters in Finance from Delhi University,
India.
At PKC Advisory, Payal is actively involved in business development
and client engagement She has led projects related to strategy
consulting, risk & rating advisory, feasibility study, business &
financial due diligence, debt advisory, equity raising support and
transaction support services in Bahrain, Kuwait, UAE, UK and USA.
She has been involved in assignments in the financial services,
insurance, real estate and diversified sectors.
Bhupinder has a total work experience of over 15 years (including 9
years at PKC Advisory). He is a Chartered Accountant and has
cleared CFA Level III from CFA Institute, USA.
He leads the Financial Services practice at PKC Advisory. Bhupinder
is actively involved in business development, client relationship
management and project management. He has vast experience in
risk advisory, strategy consulting, financial planning, ratings advisory
and transaction support. Bhupinder has led numerous mandates in
these areas for leading banks and insurance companies in MENA
region.
Vinay has over 15 years of experience (including seven years at
PKC Advisory) in banking & financial services sector. Vinay is a CFA
Charter holder from CFA Institute, USA and holds Masters in
Business Administration from ICFAI Business School, India.
At PKC Advisory, he has handled various mandates in area of risk
advisory including risk appetite framework development,
standardized risk reporting, and ICAAP & Stress testing across
MENA region. Additionally, Vinay has worked on various assignment
related to capital planning, strategy consulting, financial planning,
and transaction support.
Amit has a total work experience of over 13 years in Advanced
analytics. He is a Bachelor of Economics and holds a Post Graduate
Diploma in Management from IIFT, India.
At PKC Advisory, he has been involved in a variety of mandates in
the areas of Advanced analytics including customer, operational and
web analytics. Besides, he has worked on various assignments
related to PD, LGD and EAD modeling for Basel and IFRS9.
Prior to PKC Advisory, he worked with Wells Fargo Bank, Royal
Bank of Scotland and GE capital in their Modeling & Analytics
Practice.
Sanjeev has a total work experience of over 17 years, in diverse
areas including strategy consulting, process consulting, market
study, feasibility study, business & financial due diligence,
performance enhancement, etc. He is Bachelor in Engineering and
holds a Masters in Business Administration from Indira Gandhi
Institute, New Delhi, India.
He oversees the Business & Financial Advisory, Process
Consulting and HR Consulting practice lines at PKC Advisory. His
experiences spans across education, real estate & infrastructure,
industrial, healthcare and hospitality sectors.
Zarvan Tafti – Director
Zarvan has a total work experience of around 15 years spanning
practice areas in business advisory/ consulting, investment banking
and private equity. He is a CFA Charter holder and MBA Finance
from Ohio University
He leads the Business & Financial Advisory practice and has
successfully managed engagements related to strategy, portfolio
evaluation, valuation, feasibility studies, business plan preparation,
transaction support across diverse sectors.
Sanjeev Arora – Senior Director
21PKC AdvisoryEmail : [email protected] Website : www.pkcadvisory.com