Customer Centric Decisioning at Lloyds Banking Group
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Customer Centric Decisioning at Lloyds Banking Group

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Customer Centric Decisioning at Lloyds Banking Group




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Presentation on theme: "Customer Centric Decisioning at Lloyds Banking Group"— Presentation transcript:

Slide1

Customer Centric Decisioning at Lloyds Banking Group

Chris KeelingHead of Risk Programmes, Risk InfrastructureLloyds Banking Group

Jeremy Bryson Head of Architecture and Risk SystemsLloyds Banking Group

Slide2

Lloyds Banking Group is on a journey to develop Customer Centric Decisioning to support their Risk process for personal customers across retail products. Jeremy and Chris will provide an insight into their drivers for this and progress to date which is underpinned by the implementation of FICO® Origination Manager and FICO® TRIAD® Customer Manager.

2

Slide3

Lloyds Banking Group and Our Risk Transformation ProgrammeThe context of Lloyds Banking Group and its credit functionOur vision for risk transformation and investment rationaleWhy we picked FICO and what influenced our choiceImplementation of Acquisition Decisioning Using FICO® Origination Manager Scope and ObjectivesDelivery Experience and Lessons LearnedCreating a Customer Centric Organisation Using FICO® TRIAD® Customer Manager 9.1.1Our strategy and approachClosing Comments and Questions

3

Slide4

Chris KeelingHead of Risk Programmes, Risk InfrastructureLloyds Banking Group

Lloyds Banking Group and Our Risk Transformation Programme

4

Slide5

LBG Is the United Kingdom’s Largest Consumer Bank

5

LBG formed 2009… dates back to

1695

Relationship banking model

UK focused, Retail, SME & Corporate

MODEL

30m customers, 22m current

accounts

2300 branches, 98,000 staff

Provides 1 in 5 of all UK mortgages

SCALE

Critical to UK Economy and communities

Supports home buyers, SMEs, social inclusion

25% UK government

stake

CSR

Slide6

Plus 10 more major brands addressing specific products and market segments

We Operate Three Strategic “Relationship” Brands

6

Slide7

Today, Parts of Our IT Estate Are Complex and

Organically Derived…

Target LBG

HBOS Legacy

Fraud

Manual

Underwriting

Acquire

YourFinances

PBS

CLP

I/B

T/B

MSP+

WinXcel

FEBS

LSP

MSP

PLP

CEMS/SCEMS

OpenAccount

B2B

ManualUnderwriting

SAS Analytics

LeMans

Acquisition Decisioning

FraudHunterSIRA

CRAs

Acquisition Decisioning

SAS Analytics

APPSCORE

ASM

Caps

SM v2

CreditScore DB

CDSResults DB

Experian

Call Credit

Equifax

SW

v2

SWv1.5

SWv2

CapSv3.34

SMG3

SMv3

CapSV3.33

CapSV3.34

RDI

ME

Provisioning

CBS

Debt Manager

Bank CMF

CLP

Bank Letters

GDW

Lifecycle Decisioning

RegulatoryReporting

TDO1

FTC

CPC

LDO2

BD02

Lifecycle Decisioning

Regulatory

Reporting

BASEL 5

CMTOverrides

CMT

AMT

RetailBASEL(via CDS)

AssetImpairment

CDS

EM

DARIL

Credit CardsAMT

DynamicDecisioning

7

Slide8

Or Put Another Way…

8

Slide9

Retail Credit Risk Transformation Programme

9

Trailing to industry best practiceSustainable business growthSimplify architecture and processesSignificant new business capabilitiesStrengthen the control environmentDeliver material income and impairment benefits throughout the lifecycle

Focus on Strategic End State:Early quick winsContinuous delivery

Benefits Delivered:Benefits overtook investment Q3 2013Income GrowthReduced ImpairmentsEnhanced Productivity

Slide10

The Programme Is Delivering through Investment in Four Key Capability Blocks

Outstanding Breadth,

Depth and Recency ofCustomer Data

All relevant internal data available at all significant decision pointsBroad use of external data such as credit referencing, income verification, housing equity, and fraud indicatorsToday’s data today (and real time in selected instances)

1

Powerful, Agile

and Fully IntegratedDecisioning Capability

Able to accommodate high bandwidth of change at low costOvernight decision review where customer circumstances change Capable of taking customer-level decisionsJoined up across credit, fraud, collections and marketing

2

Slick, Highly Automated

Enactment

of Decisions

Individual customer decisions hit operating systems quicklyStrategy changes can be deployed without lead timesNeed for human intervention removed wherever practicableMulti-channel technology used to deliver customer experience

3

Underpinned

by

Great

Analytics and Insight Capability and Robust Control Environment

Train of thought analysis enabled and improved analyst throughputRapid scorecard and model developmentExecutive information systems and automated performance monitoring

4

10

Slide11

The Retail Credit Risk Investment Vision Creates a Simple, Modern, Agile Technology Landscape

Customer Acquisition

Fraud Screening

CRA Data

Collections

Analytics & Reporting

Capital & Impairment

FICO® Origination Manager

Application Fraud Prevention/Falcon v6

Agile Bureau Hub

FICO® TRIAD® Customer Manager v9.1 + FICO® Debt Manager™ solution v9

SAS Analytics

SAS Analytics

2017 Vision

Customer Management

FICO® TRIAD® Customer Manager v9.1

Personal Current Accounts (PCA)

Cards

Loans

MortgageCore

MortgageBuy To Let

Small Business Banking

AssetFinance

Wealth

11

Slide12

Selection Criteria for Our Solutions: Product and Supplier

The Product

Meets all our functional requirements

Compatible with our existing architectureScalable to our size/customer baseEasy to implementEasy to use/maintain/improveEnable rapid speed to market when live

The Supplier

A strong implementation track recordA large, skilled team to support usA team we can trust when the going gets toughA partner who will stretch our thinkingA clear roadmap on the future product strategyA competitive price!

12

Slide13

Ability to deliverPassionClear articulation how systems work with our key processesProactive demonstration of benefits short- and long-termCompetitive priceStrong FICO executive commitment

We Selected FICO for Both Acquisition and Customer Management…Here’s Why

13

Slide14

Chris KeelingHead of Risk Programmes

Implementing Acquisition Decisioning

14

Slide15

Our Initial Plans Were Ambitious—and Evolved!

Mobilisation, Selection of FICO and Ambitious Scope

Review of Scope/

Plans and Budget

Define and Build for Unsecured Acquisition

Testing and

Implementation

Key Events

H1 2012

H2 2012

H1 2013

H2 2013

15

Slide16

Clear Success Criteria Established—and Achieved

16

Success CriteriaRAGExamplesRobust platform delivered which can handle LBG volumes/response timesGreenOM now supporting all core brand Unsecured Acquisition DecisioningZero unplanned downtime since liveOver 1m applications/month processed (c500k new accounts and 500k limit increases)Improved Quality of Credit Decisions and increased cross-sale opportunitiesGreenImproved portfolio performance across all productsInitial uplift in credit card cross sales from Current Account applicationsImproved speed to market/response times for strategy changesGreenSignificant reduction achieved, average turnaround has gone from months to days46 OM releases and 128 scorecard & strategy changes implemented (31/10/2014)More consistent and simpler credit strategies developedAmberCurrent account and Credit Card policy rules alignedCross heritage scorecards implemented160k fewer referral to underwriting per annum260k fewer bureau calls per annumGood progress made but more opportunities to takeImproved ability to support other LBG initiatives and reduce regulatory costsGreen12 instances of legacy engine replaced by single solutionEnabled business programme to provide unsecured loans to non franchised customersSignificantly reduced complexity and costs of achieving Consumer Credit Reform complianceClear advocacy amongst stakeholders and users for new systemGreenStrong advocacy with usersImproved cross team knowledge and collaborationIntense demand from stakeholders to deliver Mortgage Acquisition, SME lending etc.Tangible Financial return on InvestmentGreenIncome, Impairment and efficiency benefits interlockedOn track for 2 year payback on investment

Slide17

Jeremy Bryson Head of Architecture and Risk SystemsLloyds Banking Group

Creating a Customer—Centric Organization

17

Slide18

The Architecture We Are Working to

Credit Risk Insight:Consolidate on a single analytical solution as the preferred solution for use of insight

Credit Risk Operations:FICO® Origination Manager, FICO® TRIAD® Customer Manager, underwriting and fraud solutions

Risk Data Management Layer: to actively manage data used in retail credit risk

Group Data Management Layer: acting as the master for customer and our source of transactions

Internal source system level data

Core source system data

Integrated

reporting layer

Derived level data

Data Layer

Separate layer

Operational collections andrecoveries/scorecard/fraud/underwriting layer

External source level data

CapitalSystem

Data Accuracy System

Impairment System

Credit Risk Analytics System

Operational Underwriting System

Operational Collections and Recoveries System

Fraud System

Real-time Decisioning System

Batch DecisioningSystem

Credit Risk Analytics System

Risk Operation Data Store (RODS)

Data Service

Risk Service

Model Repository

Bureaux Hub

Model Repository

Credit Reference Agencies

Valuations

Source Systems

AcquisitionSystems

Operational Application

Analytics System

Customer System

Workflow System

Operational Collections and Recoveries System

DerivedSource Data

TransactionalOperational Data Store(TODS)

CustomerOperational Data Store (CODS)

Credit risk dataEvent level dataTransaction level dataCustomer level data

Core

Non-

Core

18

Slide19

We Have Wrestled with the Customer/Product Dilemma…

PCA

Cards

Loans

Mortgage

LBG currently operates independent

product strategies

Each product has independent scorecards, policy rules, segmentation, and decision rules

Changes can be made without impacting other products

Common logic is not

supported

The FICO solution offers the opportunity to embrace a customer-level approach

One tree using common rule blocks to segment & filter

Contains scorecards and decision logic for each product

Supports different

decisions/limits

per product

Introduces interdependency in strategy

design

Customer

19

Slide20

…And This Is a Significant Decision for Us

Drives

consistent, coherent customer treatment

Facilitates re-use of common logic

Forces simplification of strategy and elimination of arbitrary

complexityAvoids technology overhead of executing multiple Triad runs

Demands additional work to align and simplify current product risk strategiesNeed to avoid mutual co-dependence blocking agile product changes Need to preserve legitimate product differences and value-adding sophistication

Aligned to strategic direction of LBG, ‘Best bank for customers’FICO case studies highlight broad client aspirations to customer approach, but reality often lags

Needs to preserve the multi brand approachNeed to leverage FICO® TRIAD® Customer Manager 8.5 capabilities (e.g. FICO® Blaze Advisor® logic) fully to achieve modular, manageable outcome & avoid exponential complexityChallenges today’s operating model

Customer strategy drives significant benefits…

…but requires several design challenges to be solved

20

Slide21

Evolving Towards a Customer Strategy

Product credit decisioning strategies

Customer enabled product credit decisioning strategies

Customer strategies

Common rulesCommon data

Single rule setOne data source

Unique product rulesUnrelated data

21

Slide22

Customer Enabled Product Credit Decisioning Strategies!

22

Loans

Credit cards

Personal Current Accounts (PCA)

4

4

7

2

1

15

Lloyds Bank

Loans

Credit cards

PCA

8

5

11

7

7

Halifax, Bank of Scotland

Credit Policy Decline

Customer Less Than 18 Years Old

Customer Is Not A UK Resident

Decline: Level Of Indebtedness

Adverse Credit Bureau (With Noc)

Adverse Credit Bureau (Without Noc)

Fraud

Customer Less Than 18 Years Old

Adverse Credit Bureau (Without Noc)

Customer Is Not A UK Resident

Adverse Credit Card Performance

Customer Is Unemployed

Adverse Mortgage PerformanceEmployment StatusProduct InappropriateDecline: Level Of IndebtednessFraudAccount On Repayment PlanPrevious LoansAdverse Credit Bureau (With Notice of Correction (Noc))

Slide23

Our Vision for a Genuinely Customer-Centric Approach to Lending Decisions

Qualify for all lending products—customer needs determine take up

Eligibility extended through product specific tailoring

Detailed customer assessment required to determine eligibility

Customers considered ineligible based on risk appetite—“no-go” area

Fully

Eligible

Fully

Eligible

Limited

Eligibility

Further

Review

Ineligible

Increasing Credit Worthiness And Affordability

23

Slide24

Customer Strategy Hierarchy

5. Product Risk Profile

All Customers

1. Risk appetite & common rules

2. Relationship Strength

3. Affordability Assessment

4. Customer-level Risk Profile

No-Go

Further

Review

Low

Core Eligible

Enhanced Eligibility

Fail

Weak

Fail

High

Medium

Unclear

6. Limit Calculations

7. Limit Management (increase/reduction)

24

Slide25

Jeremy Bryson Head of Architecture and Risk SystemsLloyds Banking Group

Closing Comments

25

Slide26

Changes to product profitability measuresChanges to the customer experienceChanges to the customer proposition by brandTesting ‘as is’ product decisions against ‘to be’ customer decisions is not that easyA healthy tension to implement customer scores early on current systemsCustomer strategy segmentation may not align to marketing segmentation

The Law of Unintended Consequences

26

Slide27

Lessons learnedStakeholders extend beyond the risk functionRegulatorsProduct ownersCollections and recoveriesFraud managementSenior managementMarketingLook at the current operation and see if you are doing elements of customer decisioning alreadyA need for common data definitions and common credit decisioning rules

In Conclusions

27

Slide28

Thank You!

Chris KeelingHead of Risk Programmes, Risk InfrastructureLloyds Banking Group

Jeremy Bryson Head of Architecture and Risk SystemsLloyds Banking Group

Slide29

Please rate this session online!

Chris KeelingHead of Risk Programmes, Risk InfrastructureLloyds Banking Group

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Jeremy Bryson Head of Architecture and Risk SystemsLloyds Banking Group

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