Adopting Analytics in BFSI

Adopting Analytics for Decision Making

in Coman Bank of India

ByAnkush RoyAshitha VSAtanu MaityKrishna BollojulaShikha Rani Deo

Agenda• Business background

• Business requirements

• Organization preparedness for analytics

• Your scope of work

• Defining and measuring success

• The next step

History Headquartered in Kolkata.

Incorporated on 11 January 1983 at Kolkata, West Bengal.

Operations include retail banking, private banking, corporate/wholesale banking and agriculture banking.

Business Overview Private banking solutions for individuals and

businesses

Deposits, loans, investment solutions, payments and cards

275 branches and 474 ATM’s across India.

200 Asset Sales Centers operating out of 15 cities with standardized appraisal and oversight mechanisms.

Vision To be the preferred financial solutions provider

excelling in customer delivery through insight, empowered employees and smart use of technology.

Mission To become a strong and innovative bank with

integrity and social responsibility to maximize customer satisfaction as well as that of the employees, shareholders and the society.


• Business Requirements




• The next step

Business Requirements

• Customer Retention

• Cross selling/Up selling

• Risk assessment and fraud detection

Customer Retention

• Management of customer churn– Target churn rate of less than 2% in the next 2

years from current level of 4%• Characteristics of churn

– Moving Away from a particular product OR– Moving Away from a particular channel

• Branches• Digital Channels

Customer Retention

• Opportunities – Improving Operational Efficiency– Improving Product Design

Cross selling/Up selling• Cash-in the existing customers

• Target single product customers to 40% of customer base from current level of 50%.

• Pre-requisite : Single view of the customers with all their characteristics well defined.

• Alert with the prospects details while launching/campaigning suitable products

Risk Assessment/Fraud Detection

• Revenue loss of 4% due to bad debts/fraud– Target less than 2% in the next financial year

• Risk Profiling– Segment based on repaying capacity

• Existing Customers – Flag the customer portfolios with characteristics of default

Risk Assessment/Fraud Detection

• Prevent Account Takeover transactions in case of digital channels

• Balance between point of detection and false positives






• The next step

Organization PreparednessTechnology• FINACLE - Centralized Banking Solution

– Connect all branches for day-to-day operations• Enterprise Data Warehouse(EDW)

– Store current and historical data used for reporting and data analysis

• Information Security Management System (ISMS)– Comply with the standards of ISMS for Data

Centre

• Bill Desk and CC Avenues – Payment gateway– Providing payment gateway services.

• Data centre – Maintaining the networked system– Operating round the clock

• Disaster recovery centre – Operating for meeting various contingencies.

• CRM– Personalizing information to retain customers

and market products.

Culture of Analytics• Analytics knowledge

– Creating analytics awareness.– Improving skills and resources.

• In-house training– Designing analytics program to know and fill

the gaps.• Analytics Adoption

– Planning to implement in the following areas:• Data Management & Integration• Integrated Risk Analytics• Customer Analytics






• The next step

Your Scope of WorkCustomer Segmentation

Understand the customer needs and sentiments regarding banking

Create customer profiles according to each segment

Identify new cross-sell and up-sell opportunities

Focus on the needs of the most profitable customers

Your Scope of WorkCustomer Churn

Identify the segments where retention programs must be practiced

Identify the reasons behind customer switching to a competing institution

Track the changes in customer behaviour so products can be tailored accordingly

Your Scope of WorkRisk and Fraud Management

Analyse credit portfolios enabling us to quickly identify potential delinquency cases

Estimate the risk of customer loans based on the earning capacity of the borrowers accurately

Determine the probability of loan default and expected recovery of loan default

Detect and prevent frauds






• The next step

Defining and Measuring SuccessThe analytics solution provided should address our pain points. This will be based on the degree of yardsticks achieved.

Yardstick RemarksROI Increase in revenue or decrease in cost or both, over the cost

of implementation of analytics solution

Loading time of data Faster extraction of data ,real time data extraction will be preferred

Solution Scalability and Robustness The ability to handle growing amount of data in future which in our case may be exponential , ability to cope with erroneous data. Avoidance of network traffic congestion

Data Integrity Assuring the accuracy and consistency of data over its entire life-cycle by a series of integrity constraints or rules

Implementation Complexity User friendly not exaggerated complex technical solutions which would require effort and time from our management

Data Security Keeping data protected from corruption and unauthorized access by disk encryption,backups,data masking and data erasure

Evaluation Approach for Measuring SuccessRegular reviews and degree of yardsticks achieved will be evaluated for each phase which are mentioned below

Agenda• Business background• Business Requirements• Organization preparedness for analytics• Your scope of work• Defining and measuring success• The next step

• Functional Requirements Document :Detailed, measurable, consistent and comprehensive system requirements.

• Proof Of Concept:Prototype of analytics solution to be designed.

• Business Sign off:Development sign off by the business owner after reviewing all documents.

• Final Contract:Issuance of formal contract to the team providing the best proof of concept.

The Next Step

Any questions ??