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CUSTOMER OFFER OPTIMIZATION

DEJAN DONEV – HEAD OF RISK MANAGEMENT ERSTE HRJIRI NOSAL – SAS PARTNER

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WHAT CAN BE SOLVED BY OUR APPROACH

Customer loyalty toolNo reason to leave

Time to cash shorteningLoans always ready even before the customer asks for it

Loans become commodity for everyone not exclusive VIP productLoans available for more customers with less risk

Lending process efficiency – digitalizationSingle click lending processes in all channels

Profit margins are decreasingCustomer sensitivity based pricing

Competition from FinTech companiesBeat them with more precise decisions and simpler and faster processes

Usage of Internet based data – big dataFully utilize in-house data first, then fine tune based on Internet info

Competition of Telco & Social technology companiesFortify existing customer‘s portfolio while there is still time

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WHAT WE NEED TO SOLVED IT

To know everything about all of your customers at any time (their income, costs, product preferences, price willing to pay etc.) ,not just for “cream of the crop” customers

Have all loans preapproved prior to the customer asking for them

Offer products customer is planning to ask for in the near future

Improve decision preciseness to be able to approve more loans with less credit risk

Switch you Sales KPIs from product to customer centric

and Love your customers, because they bring you money

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WHAT WE DELIVERED?

Bank‘sHistoricaldata

New business

Processed by CO2

What is the salary?

Is risk acceptable?

For what product customer will ask for?

What are acceptable product parameters?

Pre-approvedproduct

mix

• Technology – SAS analytical and optimization software

• Know how – model and optimization methodology

• A lot of new business• Additional profit• Customer satisfaction

• Existing data only

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REAL BENEFITS

Exploitation of existing customer base Easy access to new business

Enhance your knowledge of the customer Sales boost

Improve risk decisioning Decreased risk

Make your sales processes simple and digital Improved profitability

Double digit sales growth

even on highly

competitive markets

accompanied by low risk

Copyr igh t © 2015, SAS Ins t i tu te Inc . A l l r igh ts reserved.

THE APPROACH

Customer static data

Product data

Behavioral data

Internet footprint

Offer acceptance through any channel by customer

Direct deal booking

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FRAMEWORK FOR RETAIL

Income estimation

Probability of default

Propensity to buy

Product utilization

Client pre-approval

Product mix selection

Portfolio risk setting

Data understanding Advance Analytics Optimization based decisions

Customer static data

Product data

Behavioral data

Only already existing data Optimization based decisioning Analytics in use

Price sensitivity

Spending estimation

Copyr igh t © 2015, SAS Ins t i tu te Inc . A l l r igh ts reserved.

SOLUTION EXTENSIONS

Probability of default

Customer need

Customer behavior estimation

Customer selection and preapproval

Product mix selection

Portfolio risk assessment

Customer data

Product data

Behavioral data

Sales channels data

Income estimation

Portfolio business assessment

Only already existing data Analytics in use Optimization based decisioning

Data understanding Advance Analytics Optimization based decisions

Insurance risk estimation

Framework for Insurance

Framework for TelcoData understanding Advance Analytics Optimization based

decisions

Income estimation

Probability of default

Propensity to buy

Product utilization

Client pre-approval

Product mix selection

Portfolio risk setting

Billing data

Device info

Communication behavior

Only already existing data Optimization based decisioning Analytics in use

Price sensitivity

Geo records

Framework for SMEData understanding Advance Analytics Optimization based

decisions

Repayment cap. estimation

Probability of default

Propensity to buy

Product utilization

Client pre-approval

Product mix selection

Portfolio risk setting

Customer static data

Product data

Behavioral data

Only already existing data Optimization based decisioning Analytics in use

Financial data

Early warning checkProduct impact

Copyr igh t © 2015, SAS Ins t i tu te Inc . A l l r igh ts reserved.

LESSONS LEARNED

Even on saturated markets there could still be a hidden truly huge space for new business

The solution brings strong benefits even for banks with sound preapproval practice already in place

Uplift you can reach with existing data is much bigger then with web data

Analytics could bring you new business in a very direct way

You do not have to level up to FinTech lenders, you can overcome them

With right prerequisites digitalization could be a simple and cheap process

Its not true that you can not do more business with less risk

Copyr igh t © 2015, SAS Ins t i tu te Inc . A l l r igh ts reserved.

THE ROAD MAP - RETAIL

1-2weeks

1-2weeksStep 1

Business case calculation Project plan preparation

Step 2Existing model assessmentRisk & Business model developmentPilot optimization set up

Step 3Pilot evaluation & Optimization tuningModel scoring and optimization automationGo Live

Up to 5monthsUp to 5months

Up to 5monthsUp to 5months

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THANK YOU FOR YOUR ATTENTION