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Using AI to tailor individual customer experiences at scale

Alex Kwiatkowski

Senior Industry Consultant, Global Banking Practice

SAS Institute

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“Banking is necessary,

banks are not”Bill Gates

THE NEW BANKING LANDSCAPE

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Customer FocusedProduct & Organisation Focused

▪ Operating model organised around products

▪ Siloed data sets

▪ Multi-channel approach

▪ Reactive & slow decision making

▪ Customers dictate the experience

▪ Intelligent enterprise

▪ Seamless omnichannel personalised journeys

▪ Predictive experiences

THE NEW OPERATING MODEL

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Channel?(multiple)

Campaign?(hundreds)

Customer?(thousands/millions)

Timing?(any day/time)

25,000 volume

1,200 sales

£450,000 budget

10% ROI

Offer “A”

Offer “B”

Product “C”

Product “D”

Action “E”

Action “F”

Missed opportunity?

Wrong timing?

Saturation?

Preference?Transaction

trigger

End of Term

Up-sell

opportunity

Competitor

product

renewal

Recent contact

100,000 mail

volume

Minimum

32,000 leads

Contact

frequency?

Channel

usage?

Channel

preference?

Proposition/Message

(hundreds)

Product

Advice

Recommendation

Nudge

Service

Payment

Retail Banking Customer Decision Challenge

Goals

Increase Revenue

Improve Profitability

Reduce Costs

Mitigate Risk

Reduce Complaints

(multiple)

No 1 NPS

Products

Savings

Mortgages

Unsecured Lending

Credit Cards

(multiple)

Current Accounts

Insurance

Investments

Timings

(any day/ time)

Real Time

Triggered

Scheduled

Cyclical

Propensity

Eligibility

Lifecycle state

Risk

Simple Segment

Lifetime Value

Customer/Prospect

(millions)

Direct Mail / Letter

Social

Digital

RTMs/Channels

(multiple)

Branch

Call Centre

ATM

Decisions at the speed of the customer

Decisions at the speed of the organisation

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Company Confidential - For Internal Use OnlyCopyright © 2016, SAS Institute Inc. All rights reserved.

AI & Machine Learning is refining human decision making, and automating decisions at scale through digital channels and chatbots.

Company Confidential - For Internal Use OnlyCopyright © 2016, SAS Institute Inc. All rights reserved.

Customer Decision Hub

CUSTOMER DECISION HUB

Customer Decision

Hub

Company Confidential - For Internal Use OnlyCopyright © 2016, SAS Institute Inc. All rights reserved.

Customer Decision Hub

CUSTOMER DECISION HUB

Company Confidential - For Internal Use OnlyCopyright © 2016, SAS Institute Inc. All rights reserved.

Customer Decision Hub

CUSTOMER DECISION HUB

Customer Behaviour

Machine & Deep Learning

Natural Language Processing

Company Confidential - For Internal Use OnlyCopyright © 2016, SAS Institute Inc. All rights reserved.

Customer Decision Hub

CUSTOMER DECISION HUB

Goals and Objectives

Economic Constraints

Policies, Risk & Rules

Customer Behaviour

Machine & Deep Learning

Natural Language Processing

Company Confidential - For Internal Use OnlyCopyright © 2016, SAS Institute Inc. All rights reserved.

Customer Decision Hub

CUSTOMER DECISION HUB

Next Best Action

Personalised Experiences

Intelligent Process Automation

Goals and Objectives

Economic Constraints

Policies, Risk & Rules

Customer Behaviour

Machine & Deep Learning

Natural Language Processing

Company Confidential - For Internal Use OnlyCopyright © 2016, SAS Institute Inc. All rights reserved.

Customer Decision Hub

LEARNADJUST

OPTIMIZE

Next Best Action

Personalised Experiences

Intelligent Process Automation

Goals and Objectives

Economic Constraints

Policies, Risk & Rules

Customer Behaviour

Machine & Deep Learning

Natural Language Processing

Customer Decision Hub in Action

Real Time Customer Decisions

• 241% increase in online sales

• 110% increase in engagement

• 20% reduction in cost to retain

Digital Transformation

• £10’s millions cost savings through automation of claims process

• Real-time Personalised pricing

• Reducing Customer churn

Personalised Shopping

• 40% increase in profits

• 3M personalised experiences every day

• From personalised sort orders to real time fraud detection

5 Actions for AI driven Customer Experience

Catalogue processes where decisions about customers are made frequently and consistently.

Prioritise well defined and well understood problems such as fraudulent transactions, cross sell recommendations, personalised pricing

Foster a cross functional culture and approach to customer experience

Avoid investment in siloed solutions catering for one business function or customer touchpoint

Decide on a Build versus Buy approach

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Thankyou @alexkwiatkowski