SlideShare a Scribd company logo
BFSI
TANGO
TECHNOLOGIES
AGENDA
About Tango Technologies
Fraud Analytics – An Overview
Your Business, Our Understanding
Tango's Approach
We Sow, You Reap
Why Tango?
About Tango Technologies
Founded in 2008
Helping businesses to make better decisions that drive higher levels of
growth, profitability and customer satisfaction.
With 25 locations worldwide Tango has a global presence with its head
quarters in Bangalore, India.
Area of Expertise: Fraud detection in BFSI
About Tango Technologies
Our Customers
Fraud Analytics
 What is Fraud?
 Criminal activity.
 Abuse of position, or false representation, or prejudicing someone's rights for personal
gain.
 Traditional Methods.
 "Understand not only who your customer is, but who they’re becoming“.
 FICO Falcon Fraud Assessment System is the first Fraud Detection
system using analytics.
Fraudulent Activities in BFSI
 Electronic fraud
 Identity theft
 Cheque fraud
 Credit/Debit card fraud
oSkimming
oBIN Attack
oTele Phishing
Analytics in Credit Card Fraud Detection
 Risk Scoring based on Neural Network - Risk scoring is a system of predictive fraud
detection that payment processors use to identify the highest-risk transactions to
capture patterns of fraudulent activity, and to differentiate these patterns from
legitimate purchasing activity.
 Geolocation tracking – Uses the users system information, location information,
devices used by the user, etc., to track the customer’s activities and detects fraud.
Your Business, Our Understanding
9% 11% 16%
27%7%
10%
15%
26%
3%
5%
9%
19%
4%
7%
11%
15%
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
2011 2012 2013 2014
Market position of different products
Deposits Debit card usage Mobile banking Credit Card
• Well positioned in market - huge deposits and
transactions – YOY increase rate is more than
20%.
• Corporate account & Debit card section growth
– Increased almost 70% in 2013-2014
financial year.
• Credit card section lagging behind the other
products of the bank.
• Growth rate reversed for credit card section.
Your Business, Our Understanding
Your Business, Our Understanding
14
11
13
25
47
Customers complaint against Credit
Card
Intrest charges others
Annual fees Customer relationship
Security Issues
• Major complaints - Customer Relationship,
Interest Charges and Security Issues.
• 47% fall under Security Issues. Almost 13K
complaints booked during the year 2013-
2014.
• Online frauds - a predominant issue with
the customers.
• No separate customer care section for credit
card.
• ICICI survey says 63% of people will switch
to other credit card if they feel security
issue.
Tango's Approach
Transaction Based Scoring
Real Time Decision making
Adaptive Modelling
 Global Profiling
Tango's Approach
Could fraud analytics do a better job of protecting not just Anil’s account, but his buying
experience?
Situation : Anil who is living in Kolkata, is on a vacation to J & K.
He is buying a Snow Board from a high-end sporting store.
• Bank A’s Credit Card declined the transaction (Traditional Detection System)
Anil’s Feedback on this : “Being declined was annoying, but not enough to leave
the bank. Still, if they keep bombarding me with irrelevant offers while declining the
purchases I really do want to make, I’m going to think twice about jumping ship.”
• Bank B’s Card approved the transaction (Innovative Streaming Analytics)
Tango's Approach – Techniques Incorporated
•Behaviour Sorted Lists – Using Transaction Based Scoring, Behavioural Analytics
capture the granularity of customer habitual patterns.
•Collaborative Profiles - Using Global Profiling, we determine probability based on
the behaviour patterns of other cardholders.
with similar characteristics
Tango's Approach – How it works?
• Fraud risk is lower if some aspects of the transaction matches the cardholder
favourites.
• Even with no favourites match, there is a way to anticipate new cardholder’s
behaviour.
• It maps actual individuals to multiple behavioural archetypes in real time and updates
the mapping with each new transaction.
• These archetypes are not conceptual, hand-built categories. Rather, they are machine-
learned by an algorithm that analyzes historical transactional data which can come from
multiple sources in any form.
Tango's Approach – How it works?
>>How wide is the difference <<
Actual customer behaviour
is mapped to archetypes in
real time.
The wider the change in
archetype distribution,
the riskier the
transaction.
Tango's Approach – How it works?
• As the quantity and variety of data being captured continues to expand, one
of the most important things analytics can do for us is to help us understand
change.
• Knowing ‘what is changing’ and ‘whether it’s important’ is the key in
creating vitality and value in customer relationships, while operating in a lean
and efficient manner.
Support
The Product includes one-year free Tango Care subscription.
Tango Care package includes:
One-Day Hands-on Product Training at Client’s Location.
Dedicated Support Assistant with 24 x 7 Support.
Access to Tango Ticket System for general queries.
Product Quality Inspection every 3 months.
What’s Next?
Product
Consultant
Assignment
Data Collection POC Submission Final Discussion
Contract
Signoff
Test
Implementation
Production
Implementation
Today 3-Weeks
T T + 2 Weeks T + 3 Weeks
We sow, you reap !!!
Fraud Detection to contribute
145 Cr. to the total revenue by
2022.
inCrores
We sow, you reap !!!
Merchant Acquisition is
expected to be doubled (100%
increase) upon Fraud Detection
Implementation
Why Tango?
Data Science
Offer Services in
Advanced Data Science
& Quantitative
Modelling
Usage of Mainstream Tools-
SAS, R, Python, SQL. Model
requirement Tools: GAUSS,
MATLAB. Data Visualization
Tools: Tableau & Spotfire
Experts in Econometric,
Machine Learning and
Operation Research
Experienced Research
Scientists & Patent Holders
Why Tango?
Why do you need us?
Data Science
Offer Services in
Advanced Data Science
& Quantitative
Modelling
Experts in Econometric,
Machine Learning and
Operation Research
Business
Instincts
Delivering
combination of
data & art of
business
Timely delivery
of information
using custom
reports via
Dashboards, drill-
downs, roll-ups
and score cards
Presentation of
data using
visualization and
info-graphics
Understanding
the client and
ensuring their
needs and
expectations are
met
Why Tango?
“Tango Technologies was very much like our internal team, working on several data science
and analytics problems. They worked closely with me, building cutting-edge social media campaign
management algorithms, and insights frameworks. This enhanced our offerings, helping us win some of our
biggest clients in competitive trials against prominent names in the industry.”
VP of Data Science and Products, Bank of America
“We had an extremely productive association with Tango Technologies. They brought deep
expertise in business analytics and data sciences, along with top notch professionalism. They blended
seamlessly with our operations, engineering, and sales teams. They conceptualized and implemented
advanced statistical frameworks on top of transaction data, helping us identify credit cards open to fraud. I
would strongly recommend them for any data-oriented business problems.”
VP Engineering, RBS
Success Stories
“Tango Technologies were excellent as always. Partnership is a buzz word, but Tango
Technology truly embody the concept of partnership, making sure that they understand their
client stakeholders to tailor their service accordingly.”
Global Analytics Manager (WealthCare Financial Group)
“Tango Technologies team’s commitment, dedication, team work and follow through are big
factors to ensure the success of project.”
Senior Director - Planning and Insights (ICICI)
“Tango Technologies generated many insightful slides on their own based on their analysis
of our data, which were not part of the scope/deliverable. Such slides helped us to understand our
product cross-sell and customer behaviour better and were thought provoking.”
Business Intelligence Manager, Deutsche Bank
Success Stories

More Related Content

What's hot

Overview of Data Analytics in Lending Business
Overview of Data Analytics in Lending BusinessOverview of Data Analytics in Lending Business
Overview of Data Analytics in Lending BusinessSanjay Kar
 
Banking & Lending AI Use Cases
Banking & Lending AI Use CasesBanking & Lending AI Use Cases
Banking & Lending AI Use CasesArtivatic.ai
 
Digital Transformation in Retail Banking
Digital Transformation in Retail BankingDigital Transformation in Retail Banking
Digital Transformation in Retail BankingFerran Garcia Pagans
 
Credit card fraud detection using machine learning Algorithms
Credit card fraud detection using machine learning AlgorithmsCredit card fraud detection using machine learning Algorithms
Credit card fraud detection using machine learning Algorithmsankit panigrahy
 
Credit card fraud detection
Credit card fraud detectionCredit card fraud detection
Credit card fraud detectionvineeta vineeta
 
Detecting fraud with Python and machine learning
Detecting fraud with Python and machine learningDetecting fraud with Python and machine learning
Detecting fraud with Python and machine learningwgyn
 
Real-Time Fraud Detection in Payment Transactions
Real-Time Fraud Detection in Payment TransactionsReal-Time Fraud Detection in Payment Transactions
Real-Time Fraud Detection in Payment TransactionsChristian Gügi
 
Model building in credit card and loan approval
Model building in credit card and loan approval Model building in credit card and loan approval
Model building in credit card and loan approval Venkata Reddy Konasani
 
Machine Learning in Banking
Machine Learning in BankingMachine Learning in Banking
Machine Learning in Bankingaccenture
 
Credit card fraud detection using python machine learning
Credit card fraud detection using python machine learningCredit card fraud detection using python machine learning
Credit card fraud detection using python machine learningSandeep Garg
 
Analysis of-credit-card-fault-detection
Analysis of-credit-card-fault-detectionAnalysis of-credit-card-fault-detection
Analysis of-credit-card-fault-detectionJustluk Luk
 
Measuring and Managing Credit Risk With Machine Learning and Artificial Intel...
Measuring and Managing Credit Risk With Machine Learning and Artificial Intel...Measuring and Managing Credit Risk With Machine Learning and Artificial Intel...
Measuring and Managing Credit Risk With Machine Learning and Artificial Intel...accenture
 
Fraud Detection presentation
Fraud Detection presentationFraud Detection presentation
Fraud Detection presentationHernan Huwyler
 
Introduction To Predictive Analytics Part I
Introduction To Predictive Analytics   Part IIntroduction To Predictive Analytics   Part I
Introduction To Predictive Analytics Part Ijayroy
 
Credit card fraud detection using python machine learning
Credit card fraud detection using python machine learningCredit card fraud detection using python machine learning
Credit card fraud detection using python machine learningSandeep Garg
 
Big data analytics in banking sector
Big data analytics in banking sectorBig data analytics in banking sector
Big data analytics in banking sectorAnil Rana
 
Data Science Use cases in Banking
Data Science Use cases in BankingData Science Use cases in Banking
Data Science Use cases in BankingArul Bharathi
 

What's hot (20)

Overview of Data Analytics in Lending Business
Overview of Data Analytics in Lending BusinessOverview of Data Analytics in Lending Business
Overview of Data Analytics in Lending Business
 
Banking & Lending AI Use Cases
Banking & Lending AI Use CasesBanking & Lending AI Use Cases
Banking & Lending AI Use Cases
 
Digital Transformation in Retail Banking
Digital Transformation in Retail BankingDigital Transformation in Retail Banking
Digital Transformation in Retail Banking
 
Credit card fraud detection using machine learning Algorithms
Credit card fraud detection using machine learning AlgorithmsCredit card fraud detection using machine learning Algorithms
Credit card fraud detection using machine learning Algorithms
 
Credit card fraud detection
Credit card fraud detectionCredit card fraud detection
Credit card fraud detection
 
Detecting fraud with Python and machine learning
Detecting fraud with Python and machine learningDetecting fraud with Python and machine learning
Detecting fraud with Python and machine learning
 
Real-Time Fraud Detection in Payment Transactions
Real-Time Fraud Detection in Payment TransactionsReal-Time Fraud Detection in Payment Transactions
Real-Time Fraud Detection in Payment Transactions
 
Model building in credit card and loan approval
Model building in credit card and loan approval Model building in credit card and loan approval
Model building in credit card and loan approval
 
Machine Learning in Banking
Machine Learning in BankingMachine Learning in Banking
Machine Learning in Banking
 
Credit card fraud detection using python machine learning
Credit card fraud detection using python machine learningCredit card fraud detection using python machine learning
Credit card fraud detection using python machine learning
 
Analysis of-credit-card-fault-detection
Analysis of-credit-card-fault-detectionAnalysis of-credit-card-fault-detection
Analysis of-credit-card-fault-detection
 
Measuring and Managing Credit Risk With Machine Learning and Artificial Intel...
Measuring and Managing Credit Risk With Machine Learning and Artificial Intel...Measuring and Managing Credit Risk With Machine Learning and Artificial Intel...
Measuring and Managing Credit Risk With Machine Learning and Artificial Intel...
 
Fraud Detection presentation
Fraud Detection presentationFraud Detection presentation
Fraud Detection presentation
 
Data analytics
Data analyticsData analytics
Data analytics
 
Introduction To Predictive Analytics Part I
Introduction To Predictive Analytics   Part IIntroduction To Predictive Analytics   Part I
Introduction To Predictive Analytics Part I
 
Credit card fraud detection using python machine learning
Credit card fraud detection using python machine learningCredit card fraud detection using python machine learning
Credit card fraud detection using python machine learning
 
Fraud detection
Fraud detectionFraud detection
Fraud detection
 
Big data analytics in banking sector
Big data analytics in banking sectorBig data analytics in banking sector
Big data analytics in banking sector
 
Predictive Analytics - An Introduction
Predictive Analytics - An IntroductionPredictive Analytics - An Introduction
Predictive Analytics - An Introduction
 
Data Science Use cases in Banking
Data Science Use cases in BankingData Science Use cases in Banking
Data Science Use cases in Banking
 

Viewers also liked

Credit card fraud detection
Credit card fraud detectionCredit card fraud detection
Credit card fraud detectionkalpesh1908
 
Credit card fraud detection methods using Data-mining.pptx (2)
Credit card fraud detection methods using Data-mining.pptx (2)Credit card fraud detection methods using Data-mining.pptx (2)
Credit card fraud detection methods using Data-mining.pptx (2)k.surya kumar
 
Credit card fraud detection
Credit card fraud detectionCredit card fraud detection
Credit card fraud detectionanthonytaylor01
 
Real-time fraud detection in credit card transactions
Real-time fraud detection in credit card transactionsReal-time fraud detection in credit card transactions
Real-time fraud detection in credit card transactionsMariusz Rafało
 
Presentation on fraud prevention, detection & control
Presentation on fraud prevention, detection & controlPresentation on fraud prevention, detection & control
Presentation on fraud prevention, detection & controlDominic Sroda Korkoryi
 
Credit Card Fraud Detection System: A Survey
Credit Card Fraud Detection System: A SurveyCredit Card Fraud Detection System: A Survey
Credit Card Fraud Detection System: A SurveyIJMER
 
Anomaly detection- Credit Card Fraud Detection
Anomaly detection- Credit Card Fraud DetectionAnomaly detection- Credit Card Fraud Detection
Anomaly detection- Credit Card Fraud DetectionLipsa Panda
 
Example-Dependent Cost-Sensitive Credit Card Fraud Detection
Example-Dependent Cost-Sensitive Credit Card Fraud DetectionExample-Dependent Cost-Sensitive Credit Card Fraud Detection
Example-Dependent Cost-Sensitive Credit Card Fraud DetectionAlejandro Correa Bahnsen, PhD
 
A Survey of Online Credit Card Fraud Detection using Data Mining Techniques
A Survey of Online Credit Card Fraud Detection using Data Mining TechniquesA Survey of Online Credit Card Fraud Detection using Data Mining Techniques
A Survey of Online Credit Card Fraud Detection using Data Mining TechniquesIJSRD
 
2013 credit card fraud detection why theory dosent adjust to practice
2013 credit card fraud detection why theory dosent adjust to practice2013 credit card fraud detection why theory dosent adjust to practice
2013 credit card fraud detection why theory dosent adjust to practiceAlejandro Correa Bahnsen, PhD
 
Adaptive Machine Learning for Credit Card Fraud Detection
Adaptive Machine Learning for Credit Card Fraud DetectionAdaptive Machine Learning for Credit Card Fraud Detection
Adaptive Machine Learning for Credit Card Fraud DetectionAndrea Dal Pozzolo
 
7 Keys to Fraud Prevention, Detection and Reporting
7 Keys to Fraud Prevention, Detection and Reporting7 Keys to Fraud Prevention, Detection and Reporting
7 Keys to Fraud Prevention, Detection and ReportingBrown Smith Wallace
 
Credit Card Fraud Detection - Anomaly Detection
Credit Card Fraud Detection - Anomaly DetectionCredit Card Fraud Detection - Anomaly Detection
Credit Card Fraud Detection - Anomaly DetectionLalit Jain
 
Introduction to Neural Networks - Perceptron
Introduction to Neural Networks - PerceptronIntroduction to Neural Networks - Perceptron
Introduction to Neural Networks - PerceptronHannes Hapke
 
India; Rain Water Harvesting, Conservation and Management Strategies for Urb...
India;  Rain Water Harvesting, Conservation and Management Strategies for Urb...India;  Rain Water Harvesting, Conservation and Management Strategies for Urb...
India; Rain Water Harvesting, Conservation and Management Strategies for Urb...D5Z
 
Rain water harvesting - Need of the era
Rain water harvesting - Need of the eraRain water harvesting - Need of the era
Rain water harvesting - Need of the eraNitin Chhaperwal
 

Viewers also liked (20)

Credit card fraud detection
Credit card fraud detectionCredit card fraud detection
Credit card fraud detection
 
Credit card fraud detection methods using Data-mining.pptx (2)
Credit card fraud detection methods using Data-mining.pptx (2)Credit card fraud detection methods using Data-mining.pptx (2)
Credit card fraud detection methods using Data-mining.pptx (2)
 
Credit card fraud detection
Credit card fraud detectionCredit card fraud detection
Credit card fraud detection
 
Credit card fraud
Credit card fraudCredit card fraud
Credit card fraud
 
Real-time fraud detection in credit card transactions
Real-time fraud detection in credit card transactionsReal-time fraud detection in credit card transactions
Real-time fraud detection in credit card transactions
 
Presentation on fraud prevention, detection & control
Presentation on fraud prevention, detection & controlPresentation on fraud prevention, detection & control
Presentation on fraud prevention, detection & control
 
Credit Card Fraud Detection System: A Survey
Credit Card Fraud Detection System: A SurveyCredit Card Fraud Detection System: A Survey
Credit Card Fraud Detection System: A Survey
 
Anomaly detection- Credit Card Fraud Detection
Anomaly detection- Credit Card Fraud DetectionAnomaly detection- Credit Card Fraud Detection
Anomaly detection- Credit Card Fraud Detection
 
Example-Dependent Cost-Sensitive Credit Card Fraud Detection
Example-Dependent Cost-Sensitive Credit Card Fraud DetectionExample-Dependent Cost-Sensitive Credit Card Fraud Detection
Example-Dependent Cost-Sensitive Credit Card Fraud Detection
 
Credit Card Frauds
Credit Card FraudsCredit Card Frauds
Credit Card Frauds
 
A Survey of Online Credit Card Fraud Detection using Data Mining Techniques
A Survey of Online Credit Card Fraud Detection using Data Mining TechniquesA Survey of Online Credit Card Fraud Detection using Data Mining Techniques
A Survey of Online Credit Card Fraud Detection using Data Mining Techniques
 
2013 credit card fraud detection why theory dosent adjust to practice
2013 credit card fraud detection why theory dosent adjust to practice2013 credit card fraud detection why theory dosent adjust to practice
2013 credit card fraud detection why theory dosent adjust to practice
 
Credit card fraud
Credit card fraudCredit card fraud
Credit card fraud
 
Adaptive Machine Learning for Credit Card Fraud Detection
Adaptive Machine Learning for Credit Card Fraud DetectionAdaptive Machine Learning for Credit Card Fraud Detection
Adaptive Machine Learning for Credit Card Fraud Detection
 
7 Keys to Fraud Prevention, Detection and Reporting
7 Keys to Fraud Prevention, Detection and Reporting7 Keys to Fraud Prevention, Detection and Reporting
7 Keys to Fraud Prevention, Detection and Reporting
 
Deep Learning for Fraud Detection
Deep Learning for Fraud DetectionDeep Learning for Fraud Detection
Deep Learning for Fraud Detection
 
Credit Card Fraud Detection - Anomaly Detection
Credit Card Fraud Detection - Anomaly DetectionCredit Card Fraud Detection - Anomaly Detection
Credit Card Fraud Detection - Anomaly Detection
 
Introduction to Neural Networks - Perceptron
Introduction to Neural Networks - PerceptronIntroduction to Neural Networks - Perceptron
Introduction to Neural Networks - Perceptron
 
India; Rain Water Harvesting, Conservation and Management Strategies for Urb...
India;  Rain Water Harvesting, Conservation and Management Strategies for Urb...India;  Rain Water Harvesting, Conservation and Management Strategies for Urb...
India; Rain Water Harvesting, Conservation and Management Strategies for Urb...
 
Rain water harvesting - Need of the era
Rain water harvesting - Need of the eraRain water harvesting - Need of the era
Rain water harvesting - Need of the era
 

Similar to Credit Card Fraud Detection Client Presentation

Finlytica Solutions Brief​
Finlytica Solutions Brief​Finlytica Solutions Brief​
Finlytica Solutions Brief​PegasusKnowledge
 
Data mining and their applications
Data mining and their applicationsData mining and their applications
Data mining and their applicationsShashwat Shankar
 
Capgemini Consulting: All-Channel-Experience
Capgemini Consulting: All-Channel-ExperienceCapgemini Consulting: All-Channel-Experience
Capgemini Consulting: All-Channel-ExperienceSamir Selimi
 
Data Analytics Brochure - Cockpit
Data Analytics Brochure - CockpitData Analytics Brochure - Cockpit
Data Analytics Brochure - CockpitLera Technologies
 
Relation of Big Data and E-Commerce
Relation of Big Data and E-CommerceRelation of Big Data and E-Commerce
Relation of Big Data and E-CommerceAnkita Tiwari
 
Digital foresight whitepaper
Digital foresight whitepaperDigital foresight whitepaper
Digital foresight whitepaperNIIT Technologies
 
InData Labs. How we leverage Big Data - 5 use cases
InData Labs. How we leverage Big Data - 5 use casesInData Labs. How we leverage Big Data - 5 use cases
InData Labs. How we leverage Big Data - 5 use casesInData Labs
 
Understanding and winning your customers in the big data era ( retail industry)
Understanding and winning your customers in the big data era ( retail industry)Understanding and winning your customers in the big data era ( retail industry)
Understanding and winning your customers in the big data era ( retail industry)Kim Ming Teh
 
Monitoring Analytics To Create Customer Value And Experience
Monitoring Analytics To Create Customer Value And ExperienceMonitoring Analytics To Create Customer Value And Experience
Monitoring Analytics To Create Customer Value And ExperienceeTailing India
 
EY + Neo4j: Why graph technology makes sense for fraud detection and customer...
EY + Neo4j: Why graph technology makes sense for fraud detection and customer...EY + Neo4j: Why graph technology makes sense for fraud detection and customer...
EY + Neo4j: Why graph technology makes sense for fraud detection and customer...Neo4j
 
Data Science - Part I - Sustaining Predictive Analytics Capabilities
Data Science - Part I - Sustaining Predictive Analytics CapabilitiesData Science - Part I - Sustaining Predictive Analytics Capabilities
Data Science - Part I - Sustaining Predictive Analytics CapabilitiesDerek Kane
 
The role of ai in indian banking and retail
The role of ai in indian banking and retailThe role of ai in indian banking and retail
The role of ai in indian banking and retailBalaji C Shankar
 
Cognitive Automation Solutions are Enhancing Business Strategy—Here's How! (1...
Cognitive Automation Solutions are Enhancing Business Strategy—Here's How! (1...Cognitive Automation Solutions are Enhancing Business Strategy—Here's How! (1...
Cognitive Automation Solutions are Enhancing Business Strategy—Here's How! (1...E42 (Light Information Systems Pvt Ltd)
 
Digital trends: AI in marketing
Digital trends: AI in marketingDigital trends: AI in marketing
Digital trends: AI in marketingasthajain100
 
Application of Artificial Intelligence in E-commerce
Application of Artificial Intelligence in E-commerceApplication of Artificial Intelligence in E-commerce
Application of Artificial Intelligence in E-commercekarakavalasa Durga Akhil
 
How GetNinjas uses data to make smarter product decisions
How GetNinjas uses data to make smarter product decisionsHow GetNinjas uses data to make smarter product decisions
How GetNinjas uses data to make smarter product decisionsBernardo Srulzon
 
Unicsoft - Business Presentation
Unicsoft - Business PresentationUnicsoft - Business Presentation
Unicsoft - Business PresentationUnicsoft
 

Similar to Credit Card Fraud Detection Client Presentation (20)

Finlytica Solutions Brief​
Finlytica Solutions Brief​Finlytica Solutions Brief​
Finlytica Solutions Brief​
 
Data mining and their applications
Data mining and their applicationsData mining and their applications
Data mining and their applications
 
Capgemini Consulting: All-Channel-Experience
Capgemini Consulting: All-Channel-ExperienceCapgemini Consulting: All-Channel-Experience
Capgemini Consulting: All-Channel-Experience
 
Data Analytics Brochure - Cockpit
Data Analytics Brochure - CockpitData Analytics Brochure - Cockpit
Data Analytics Brochure - Cockpit
 
Relation of Big Data and E-Commerce
Relation of Big Data and E-CommerceRelation of Big Data and E-Commerce
Relation of Big Data and E-Commerce
 
Digital foresight whitepaper
Digital foresight whitepaperDigital foresight whitepaper
Digital foresight whitepaper
 
InData Labs. How we leverage Big Data - 5 use cases
InData Labs. How we leverage Big Data - 5 use casesInData Labs. How we leverage Big Data - 5 use cases
InData Labs. How we leverage Big Data - 5 use cases
 
Understanding and winning your customers in the big data era ( retail industry)
Understanding and winning your customers in the big data era ( retail industry)Understanding and winning your customers in the big data era ( retail industry)
Understanding and winning your customers in the big data era ( retail industry)
 
Monitoring Analytics To Create Customer Value And Experience
Monitoring Analytics To Create Customer Value And ExperienceMonitoring Analytics To Create Customer Value And Experience
Monitoring Analytics To Create Customer Value And Experience
 
EY + Neo4j: Why graph technology makes sense for fraud detection and customer...
EY + Neo4j: Why graph technology makes sense for fraud detection and customer...EY + Neo4j: Why graph technology makes sense for fraud detection and customer...
EY + Neo4j: Why graph technology makes sense for fraud detection and customer...
 
Data Science - Part I - Sustaining Predictive Analytics Capabilities
Data Science - Part I - Sustaining Predictive Analytics CapabilitiesData Science - Part I - Sustaining Predictive Analytics Capabilities
Data Science - Part I - Sustaining Predictive Analytics Capabilities
 
The role of ai in indian banking and retail
The role of ai in indian banking and retailThe role of ai in indian banking and retail
The role of ai in indian banking and retail
 
Predictive analytics 2025_br
Predictive analytics 2025_brPredictive analytics 2025_br
Predictive analytics 2025_br
 
Architecting A Platform For Big Data Analytics
Architecting A Platform For Big Data AnalyticsArchitecting A Platform For Big Data Analytics
Architecting A Platform For Big Data Analytics
 
Cognitive Automation Solutions are Enhancing Business Strategy—Here's How! (1...
Cognitive Automation Solutions are Enhancing Business Strategy—Here's How! (1...Cognitive Automation Solutions are Enhancing Business Strategy—Here's How! (1...
Cognitive Automation Solutions are Enhancing Business Strategy—Here's How! (1...
 
Unlock the Value of Usage Data
Unlock the Value of Usage DataUnlock the Value of Usage Data
Unlock the Value of Usage Data
 
Digital trends: AI in marketing
Digital trends: AI in marketingDigital trends: AI in marketing
Digital trends: AI in marketing
 
Application of Artificial Intelligence in E-commerce
Application of Artificial Intelligence in E-commerceApplication of Artificial Intelligence in E-commerce
Application of Artificial Intelligence in E-commerce
 
How GetNinjas uses data to make smarter product decisions
How GetNinjas uses data to make smarter product decisionsHow GetNinjas uses data to make smarter product decisions
How GetNinjas uses data to make smarter product decisions
 
Unicsoft - Business Presentation
Unicsoft - Business PresentationUnicsoft - Business Presentation
Unicsoft - Business Presentation
 

More from Ayapparaj SKS

ECM Regression Analysis
ECM Regression AnalysisECM Regression Analysis
ECM Regression AnalysisAyapparaj SKS
 
Ecm time series forecast
Ecm time series forecastEcm time series forecast
Ecm time series forecastAyapparaj SKS
 
My First Hadoop Program !!!
My First Hadoop Program !!!My First Hadoop Program !!!
My First Hadoop Program !!!Ayapparaj SKS
 
SAS Ron Cody Solutions for even Number problems from Chapter 16 to 20
SAS Ron Cody Solutions for even Number problems from Chapter 16 to 20SAS Ron Cody Solutions for even Number problems from Chapter 16 to 20
SAS Ron Cody Solutions for even Number problems from Chapter 16 to 20Ayapparaj SKS
 
SAS Ron Cody Solutions for even Number problems from Chapter 7 to 15
SAS Ron Cody Solutions for even Number problems from Chapter 7 to 15SAS Ron Cody Solutions for even Number problems from Chapter 7 to 15
SAS Ron Cody Solutions for even Number problems from Chapter 7 to 15Ayapparaj SKS
 

More from Ayapparaj SKS (7)

ECM Regression Analysis
ECM Regression AnalysisECM Regression Analysis
ECM Regression Analysis
 
Ecm time series forecast
Ecm time series forecastEcm time series forecast
Ecm time series forecast
 
Apache hive
Apache hiveApache hive
Apache hive
 
Pig
PigPig
Pig
 
My First Hadoop Program !!!
My First Hadoop Program !!!My First Hadoop Program !!!
My First Hadoop Program !!!
 
SAS Ron Cody Solutions for even Number problems from Chapter 16 to 20
SAS Ron Cody Solutions for even Number problems from Chapter 16 to 20SAS Ron Cody Solutions for even Number problems from Chapter 16 to 20
SAS Ron Cody Solutions for even Number problems from Chapter 16 to 20
 
SAS Ron Cody Solutions for even Number problems from Chapter 7 to 15
SAS Ron Cody Solutions for even Number problems from Chapter 7 to 15SAS Ron Cody Solutions for even Number problems from Chapter 7 to 15
SAS Ron Cody Solutions for even Number problems from Chapter 7 to 15
 

Recently uploaded

Computer Presentation.pptx ecommerce advantage s
Computer Presentation.pptx ecommerce advantage sComputer Presentation.pptx ecommerce advantage s
Computer Presentation.pptx ecommerce advantage sMAQIB18
 
一比一原版(NYU毕业证)纽约大学毕业证成绩单
一比一原版(NYU毕业证)纽约大学毕业证成绩单一比一原版(NYU毕业证)纽约大学毕业证成绩单
一比一原版(NYU毕业证)纽约大学毕业证成绩单ewymefz
 
社内勉強会資料_LLM Agents                              .
社内勉強会資料_LLM Agents                              .社内勉強会資料_LLM Agents                              .
社内勉強会資料_LLM Agents                              .NABLAS株式会社
 
Opendatabay - Open Data Marketplace.pptx
Opendatabay - Open Data Marketplace.pptxOpendatabay - Open Data Marketplace.pptx
Opendatabay - Open Data Marketplace.pptxOpendatabay
 
Tabula.io Cheatsheet: automate your data workflows
Tabula.io Cheatsheet: automate your data workflowsTabula.io Cheatsheet: automate your data workflows
Tabula.io Cheatsheet: automate your data workflowsalex933524
 
Introduction-to-Cybersecurit57hhfcbbcxxx
Introduction-to-Cybersecurit57hhfcbbcxxxIntroduction-to-Cybersecurit57hhfcbbcxxx
Introduction-to-Cybersecurit57hhfcbbcxxxzahraomer517
 
Criminal IP - Threat Hunting Webinar.pdf
Criminal IP - Threat Hunting Webinar.pdfCriminal IP - Threat Hunting Webinar.pdf
Criminal IP - Threat Hunting Webinar.pdfCriminal IP
 
Predicting Product Ad Campaign Performance: A Data Analysis Project Presentation
Predicting Product Ad Campaign Performance: A Data Analysis Project PresentationPredicting Product Ad Campaign Performance: A Data Analysis Project Presentation
Predicting Product Ad Campaign Performance: A Data Analysis Project PresentationBoston Institute of Analytics
 
Using PDB Relocation to Move a Single PDB to Another Existing CDB
Using PDB Relocation to Move a Single PDB to Another Existing CDBUsing PDB Relocation to Move a Single PDB to Another Existing CDB
Using PDB Relocation to Move a Single PDB to Another Existing CDBAlireza Kamrani
 
Jpolillo Amazon PPC - Bid Optimization Sample
Jpolillo Amazon PPC - Bid Optimization SampleJpolillo Amazon PPC - Bid Optimization Sample
Jpolillo Amazon PPC - Bid Optimization SampleJames Polillo
 
Professional Data Engineer Certification Exam Guide  _  Learn  _  Google Clou...
Professional Data Engineer Certification Exam Guide  _  Learn  _  Google Clou...Professional Data Engineer Certification Exam Guide  _  Learn  _  Google Clou...
Professional Data Engineer Certification Exam Guide  _  Learn  _  Google Clou...Domenico Conte
 
一比一原版(UofM毕业证)明尼苏达大学毕业证成绩单
一比一原版(UofM毕业证)明尼苏达大学毕业证成绩单一比一原版(UofM毕业证)明尼苏达大学毕业证成绩单
一比一原版(UofM毕业证)明尼苏达大学毕业证成绩单ewymefz
 
Webinar One View, Multiple Systems No-Code Integration of Salesforce and ERPs
Webinar One View, Multiple Systems No-Code Integration of Salesforce and ERPsWebinar One View, Multiple Systems No-Code Integration of Salesforce and ERPs
Webinar One View, Multiple Systems No-Code Integration of Salesforce and ERPsCEPTES Software Inc
 
Investigate & Recover / StarCompliance.io / Crypto_Crimes
Investigate & Recover / StarCompliance.io / Crypto_CrimesInvestigate & Recover / StarCompliance.io / Crypto_Crimes
Investigate & Recover / StarCompliance.io / Crypto_CrimesStarCompliance.io
 
Uber Ride Supply Demand Gap Analysis Report
Uber Ride Supply Demand Gap Analysis ReportUber Ride Supply Demand Gap Analysis Report
Uber Ride Supply Demand Gap Analysis ReportSatyamNeelmani2
 
一比一原版(BU毕业证)波士顿大学毕业证成绩单
一比一原版(BU毕业证)波士顿大学毕业证成绩单一比一原版(BU毕业证)波士顿大学毕业证成绩单
一比一原版(BU毕业证)波士顿大学毕业证成绩单ewymefz
 
一比一原版(UPenn毕业证)宾夕法尼亚大学毕业证成绩单
一比一原版(UPenn毕业证)宾夕法尼亚大学毕业证成绩单一比一原版(UPenn毕业证)宾夕法尼亚大学毕业证成绩单
一比一原版(UPenn毕业证)宾夕法尼亚大学毕业证成绩单ewymefz
 
一比一原版(QU毕业证)皇后大学毕业证成绩单
一比一原版(QU毕业证)皇后大学毕业证成绩单一比一原版(QU毕业证)皇后大学毕业证成绩单
一比一原版(QU毕业证)皇后大学毕业证成绩单enxupq
 
standardisation of garbhpala offhgfffghh
standardisation of garbhpala offhgfffghhstandardisation of garbhpala offhgfffghh
standardisation of garbhpala offhgfffghhArpitMalhotra16
 
一比一原版(YU毕业证)约克大学毕业证成绩单
一比一原版(YU毕业证)约克大学毕业证成绩单一比一原版(YU毕业证)约克大学毕业证成绩单
一比一原版(YU毕业证)约克大学毕业证成绩单enxupq
 

Recently uploaded (20)

Computer Presentation.pptx ecommerce advantage s
Computer Presentation.pptx ecommerce advantage sComputer Presentation.pptx ecommerce advantage s
Computer Presentation.pptx ecommerce advantage s
 
一比一原版(NYU毕业证)纽约大学毕业证成绩单
一比一原版(NYU毕业证)纽约大学毕业证成绩单一比一原版(NYU毕业证)纽约大学毕业证成绩单
一比一原版(NYU毕业证)纽约大学毕业证成绩单
 
社内勉強会資料_LLM Agents                              .
社内勉強会資料_LLM Agents                              .社内勉強会資料_LLM Agents                              .
社内勉強会資料_LLM Agents                              .
 
Opendatabay - Open Data Marketplace.pptx
Opendatabay - Open Data Marketplace.pptxOpendatabay - Open Data Marketplace.pptx
Opendatabay - Open Data Marketplace.pptx
 
Tabula.io Cheatsheet: automate your data workflows
Tabula.io Cheatsheet: automate your data workflowsTabula.io Cheatsheet: automate your data workflows
Tabula.io Cheatsheet: automate your data workflows
 
Introduction-to-Cybersecurit57hhfcbbcxxx
Introduction-to-Cybersecurit57hhfcbbcxxxIntroduction-to-Cybersecurit57hhfcbbcxxx
Introduction-to-Cybersecurit57hhfcbbcxxx
 
Criminal IP - Threat Hunting Webinar.pdf
Criminal IP - Threat Hunting Webinar.pdfCriminal IP - Threat Hunting Webinar.pdf
Criminal IP - Threat Hunting Webinar.pdf
 
Predicting Product Ad Campaign Performance: A Data Analysis Project Presentation
Predicting Product Ad Campaign Performance: A Data Analysis Project PresentationPredicting Product Ad Campaign Performance: A Data Analysis Project Presentation
Predicting Product Ad Campaign Performance: A Data Analysis Project Presentation
 
Using PDB Relocation to Move a Single PDB to Another Existing CDB
Using PDB Relocation to Move a Single PDB to Another Existing CDBUsing PDB Relocation to Move a Single PDB to Another Existing CDB
Using PDB Relocation to Move a Single PDB to Another Existing CDB
 
Jpolillo Amazon PPC - Bid Optimization Sample
Jpolillo Amazon PPC - Bid Optimization SampleJpolillo Amazon PPC - Bid Optimization Sample
Jpolillo Amazon PPC - Bid Optimization Sample
 
Professional Data Engineer Certification Exam Guide  _  Learn  _  Google Clou...
Professional Data Engineer Certification Exam Guide  _  Learn  _  Google Clou...Professional Data Engineer Certification Exam Guide  _  Learn  _  Google Clou...
Professional Data Engineer Certification Exam Guide  _  Learn  _  Google Clou...
 
一比一原版(UofM毕业证)明尼苏达大学毕业证成绩单
一比一原版(UofM毕业证)明尼苏达大学毕业证成绩单一比一原版(UofM毕业证)明尼苏达大学毕业证成绩单
一比一原版(UofM毕业证)明尼苏达大学毕业证成绩单
 
Webinar One View, Multiple Systems No-Code Integration of Salesforce and ERPs
Webinar One View, Multiple Systems No-Code Integration of Salesforce and ERPsWebinar One View, Multiple Systems No-Code Integration of Salesforce and ERPs
Webinar One View, Multiple Systems No-Code Integration of Salesforce and ERPs
 
Investigate & Recover / StarCompliance.io / Crypto_Crimes
Investigate & Recover / StarCompliance.io / Crypto_CrimesInvestigate & Recover / StarCompliance.io / Crypto_Crimes
Investigate & Recover / StarCompliance.io / Crypto_Crimes
 
Uber Ride Supply Demand Gap Analysis Report
Uber Ride Supply Demand Gap Analysis ReportUber Ride Supply Demand Gap Analysis Report
Uber Ride Supply Demand Gap Analysis Report
 
一比一原版(BU毕业证)波士顿大学毕业证成绩单
一比一原版(BU毕业证)波士顿大学毕业证成绩单一比一原版(BU毕业证)波士顿大学毕业证成绩单
一比一原版(BU毕业证)波士顿大学毕业证成绩单
 
一比一原版(UPenn毕业证)宾夕法尼亚大学毕业证成绩单
一比一原版(UPenn毕业证)宾夕法尼亚大学毕业证成绩单一比一原版(UPenn毕业证)宾夕法尼亚大学毕业证成绩单
一比一原版(UPenn毕业证)宾夕法尼亚大学毕业证成绩单
 
一比一原版(QU毕业证)皇后大学毕业证成绩单
一比一原版(QU毕业证)皇后大学毕业证成绩单一比一原版(QU毕业证)皇后大学毕业证成绩单
一比一原版(QU毕业证)皇后大学毕业证成绩单
 
standardisation of garbhpala offhgfffghh
standardisation of garbhpala offhgfffghhstandardisation of garbhpala offhgfffghh
standardisation of garbhpala offhgfffghh
 
一比一原版(YU毕业证)约克大学毕业证成绩单
一比一原版(YU毕业证)约克大学毕业证成绩单一比一原版(YU毕业证)约克大学毕业证成绩单
一比一原版(YU毕业证)约克大学毕业证成绩单
 

Credit Card Fraud Detection Client Presentation

  • 2. AGENDA About Tango Technologies Fraud Analytics – An Overview Your Business, Our Understanding Tango's Approach We Sow, You Reap Why Tango?
  • 3. About Tango Technologies Founded in 2008 Helping businesses to make better decisions that drive higher levels of growth, profitability and customer satisfaction. With 25 locations worldwide Tango has a global presence with its head quarters in Bangalore, India. Area of Expertise: Fraud detection in BFSI
  • 5. Fraud Analytics  What is Fraud?  Criminal activity.  Abuse of position, or false representation, or prejudicing someone's rights for personal gain.  Traditional Methods.  "Understand not only who your customer is, but who they’re becoming“.  FICO Falcon Fraud Assessment System is the first Fraud Detection system using analytics.
  • 6. Fraudulent Activities in BFSI  Electronic fraud  Identity theft  Cheque fraud  Credit/Debit card fraud oSkimming oBIN Attack oTele Phishing
  • 7. Analytics in Credit Card Fraud Detection  Risk Scoring based on Neural Network - Risk scoring is a system of predictive fraud detection that payment processors use to identify the highest-risk transactions to capture patterns of fraudulent activity, and to differentiate these patterns from legitimate purchasing activity.  Geolocation tracking – Uses the users system information, location information, devices used by the user, etc., to track the customer’s activities and detects fraud.
  • 8. Your Business, Our Understanding 9% 11% 16% 27%7% 10% 15% 26% 3% 5% 9% 19% 4% 7% 11% 15% 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% 2011 2012 2013 2014 Market position of different products Deposits Debit card usage Mobile banking Credit Card • Well positioned in market - huge deposits and transactions – YOY increase rate is more than 20%. • Corporate account & Debit card section growth – Increased almost 70% in 2013-2014 financial year. • Credit card section lagging behind the other products of the bank. • Growth rate reversed for credit card section.
  • 9. Your Business, Our Understanding
  • 10. Your Business, Our Understanding 14 11 13 25 47 Customers complaint against Credit Card Intrest charges others Annual fees Customer relationship Security Issues • Major complaints - Customer Relationship, Interest Charges and Security Issues. • 47% fall under Security Issues. Almost 13K complaints booked during the year 2013- 2014. • Online frauds - a predominant issue with the customers. • No separate customer care section for credit card. • ICICI survey says 63% of people will switch to other credit card if they feel security issue.
  • 11. Tango's Approach Transaction Based Scoring Real Time Decision making Adaptive Modelling  Global Profiling
  • 12. Tango's Approach Could fraud analytics do a better job of protecting not just Anil’s account, but his buying experience? Situation : Anil who is living in Kolkata, is on a vacation to J & K. He is buying a Snow Board from a high-end sporting store. • Bank A’s Credit Card declined the transaction (Traditional Detection System) Anil’s Feedback on this : “Being declined was annoying, but not enough to leave the bank. Still, if they keep bombarding me with irrelevant offers while declining the purchases I really do want to make, I’m going to think twice about jumping ship.” • Bank B’s Card approved the transaction (Innovative Streaming Analytics)
  • 13. Tango's Approach – Techniques Incorporated •Behaviour Sorted Lists – Using Transaction Based Scoring, Behavioural Analytics capture the granularity of customer habitual patterns. •Collaborative Profiles - Using Global Profiling, we determine probability based on the behaviour patterns of other cardholders. with similar characteristics
  • 14. Tango's Approach – How it works? • Fraud risk is lower if some aspects of the transaction matches the cardholder favourites. • Even with no favourites match, there is a way to anticipate new cardholder’s behaviour. • It maps actual individuals to multiple behavioural archetypes in real time and updates the mapping with each new transaction. • These archetypes are not conceptual, hand-built categories. Rather, they are machine- learned by an algorithm that analyzes historical transactional data which can come from multiple sources in any form.
  • 15. Tango's Approach – How it works? >>How wide is the difference << Actual customer behaviour is mapped to archetypes in real time. The wider the change in archetype distribution, the riskier the transaction.
  • 16. Tango's Approach – How it works? • As the quantity and variety of data being captured continues to expand, one of the most important things analytics can do for us is to help us understand change. • Knowing ‘what is changing’ and ‘whether it’s important’ is the key in creating vitality and value in customer relationships, while operating in a lean and efficient manner.
  • 17. Support The Product includes one-year free Tango Care subscription. Tango Care package includes: One-Day Hands-on Product Training at Client’s Location. Dedicated Support Assistant with 24 x 7 Support. Access to Tango Ticket System for general queries. Product Quality Inspection every 3 months.
  • 18. What’s Next? Product Consultant Assignment Data Collection POC Submission Final Discussion Contract Signoff Test Implementation Production Implementation Today 3-Weeks T T + 2 Weeks T + 3 Weeks
  • 19. We sow, you reap !!! Fraud Detection to contribute 145 Cr. to the total revenue by 2022. inCrores
  • 20. We sow, you reap !!! Merchant Acquisition is expected to be doubled (100% increase) upon Fraud Detection Implementation
  • 21. Why Tango? Data Science Offer Services in Advanced Data Science & Quantitative Modelling Usage of Mainstream Tools- SAS, R, Python, SQL. Model requirement Tools: GAUSS, MATLAB. Data Visualization Tools: Tableau & Spotfire Experts in Econometric, Machine Learning and Operation Research Experienced Research Scientists & Patent Holders
  • 22. Why Tango? Why do you need us? Data Science Offer Services in Advanced Data Science & Quantitative Modelling Experts in Econometric, Machine Learning and Operation Research
  • 23. Business Instincts Delivering combination of data & art of business Timely delivery of information using custom reports via Dashboards, drill- downs, roll-ups and score cards Presentation of data using visualization and info-graphics Understanding the client and ensuring their needs and expectations are met Why Tango?
  • 24. “Tango Technologies was very much like our internal team, working on several data science and analytics problems. They worked closely with me, building cutting-edge social media campaign management algorithms, and insights frameworks. This enhanced our offerings, helping us win some of our biggest clients in competitive trials against prominent names in the industry.” VP of Data Science and Products, Bank of America “We had an extremely productive association with Tango Technologies. They brought deep expertise in business analytics and data sciences, along with top notch professionalism. They blended seamlessly with our operations, engineering, and sales teams. They conceptualized and implemented advanced statistical frameworks on top of transaction data, helping us identify credit cards open to fraud. I would strongly recommend them for any data-oriented business problems.” VP Engineering, RBS Success Stories
  • 25. “Tango Technologies were excellent as always. Partnership is a buzz word, but Tango Technology truly embody the concept of partnership, making sure that they understand their client stakeholders to tailor their service accordingly.” Global Analytics Manager (WealthCare Financial Group) “Tango Technologies team’s commitment, dedication, team work and follow through are big factors to ensure the success of project.” Senior Director - Planning and Insights (ICICI) “Tango Technologies generated many insightful slides on their own based on their analysis of our data, which were not part of the scope/deliverable. Such slides helped us to understand our product cross-sell and customer behaviour better and were thought provoking.” Business Intelligence Manager, Deutsche Bank Success Stories

Editor's Notes

  1. this heterogeneous data is combined into a single mixed-bag “document,” which the algorithm examines as a whole to find similarities in customer behavior that support the discovery of archetypes. This document is unstructured—we can add data to it without having to know what predictive characteristics the various data sources contain or specify relationships between them. In other words, no data model is required. An advantage of this approach is flexibility to work with whatever transactional data becomes available. We also gain speed, since once the data has been assembled, analytic deployment is straightforward.