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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:

1 Customer Centric Decisioning at Lloyds Banking Group
Chris Keeling Head of Risk Programmes, Risk Infrastructure Lloyds Banking Group Jeremy Bryson Head of Architecture and Risk Systems Lloyds Banking Group

2 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.

3 Lloyds Banking Group and Our Risk Transformation Programme
The context of Lloyds Banking Group and its credit function Our vision for risk transformation and investment rationale Why we picked FICO and what influenced our choice Implementation of Acquisition Decisioning Using FICO® Origination Manager Scope and Objectives Delivery Experience and Lessons Learned Creating a Customer Centric Organisation Using FICO® TRIAD® Customer Manager 9.1.1 Our strategy and approach Closing Comments and Questions

4 Chris Keeling Head of Risk Programmes, Risk Infrastructure Lloyds Banking Group
Lloyds Banking Group and Our Risk Transformation Programme

5 LBG Is the United Kingdom’s Largest Consumer Bank
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

6 We Operate Three Strategic “Relationship” Brands
Plus 10 more major brands addressing specific products and market segments

7 Today, Parts of Our IT Estate Are Complex and Organically Derived…
Target LBG HBOS Legacy Fraud Manual Underwriting Acquire Your Finances PBS CLP I/B T/B MSP+ WinXcel FEBS LSP MSP PLP CEMS/ SCEMS Open Account B2B Manual Underwriting SAS Analytics Acquisition Decisioning Caps CRAs Acquisition Decisioning SW v2 SW v1.5 CapS v3.34 SMG3 SM v3 CapS V3.33 CapS V3.34 SAS Analytics APPSCORE ASM LeMans Experian RDI Credit Score DB CDS Results DB Call Credit ME Fraud Hunter SIRA SM v2 Equifax Provisioning Lifecycle Decisioning Regulatory Reporting TDO1 FTC CPC LDO2 BD02 Lifecycle Decisioning Regulatory Reporting CDS DARIL Retail BASEL (via CDS) CMT BASEL 5 CBS CMT Overrides Debt Manager Dynamic Decisioning AMT Bank CMF Asset Impairment CLP EM Credit Cards AMT GDW Bank Letters

8 Or Put Another Way…

9 Retail Credit Risk Transformation Programme
Trailing to industry best practice Sustainable business growth Simplify architecture and processes Significant new business capabilities Strengthen the control environment Deliver material income and impairment benefits throughout the lifecycle Focus on Strategic End State: Early quick wins Continuous delivery Benefits Delivered: Benefits overtook investment Q3 2013 Income Growth Reduced Impairments Enhanced Productivity

10 Decisioning Capability Slick, Highly Automated Enactment of Decisions
The Programme Is Delivering through Investment in Four Key Capability Blocks Outstanding Breadth, Depth and Recency of Customer Data All relevant internal data available at all significant decision points Broad use of external data such as credit referencing, income verification, housing equity, and fraud indicators Today’s data today (and real time in selected instances) 1 Powerful, Agile and Fully Integrated Decisioning Capability Able to accommodate high bandwidth of change at low cost Overnight decision review where customer circumstances change Capable of taking customer- level decisions Joined up across credit, fraud, collections and marketing 2 Slick, Highly Automated Enactment of Decisions Individual customer decisions hit operating systems quickly Strategy changes can be deployed without lead times Need for human intervention removed wherever practicable Multi-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 throughput Rapid scorecard and model development Executive information systems and automated performance monitoring 4

11 The Retail Credit Risk Investment Vision Creates a Simple, Modern, Agile Technology Landscape
Personal Current Accounts (PCA) Cards Loans Mortgage Core Mortgage Buy To Let Small Business Banking Asset Finance Wealth Customer Acquisition FICO® Origination Manager Fraud Screening Application Fraud Prevention/Falcon v6 CRA Data Agile Bureau Hub Customer Management FICO® TRIAD® Customer Manager v9.1 Collections FICO® TRIAD® Customer Manager v9.1 + FICO® Debt Manager™ solution v9 Analytics & Reporting SAS Analytics Capital & Impairment SAS Analytics

12 Selection Criteria for Our Solutions: Product and Supplier
The Product Meets all our functional requirements Compatible with our existing architecture Scalable to our size/customer base Easy to implement Easy to use/maintain/improve Enable rapid speed to market when live The Supplier A strong implementation track record A large, skilled team to support us A team we can trust when the going gets tough A partner who will stretch our thinking A clear roadmap on the future product strategy A competitive price!

13 We Selected FICO for Both Acquisition and Customer Management…Here’s Why
Ability to deliver Passion Clear articulation how systems work with our key processes Proactive demonstration of benefits short- and long-term Competitive price Strong FICO executive commitment

14 Chris Keeling Head of Risk Programmes
Implementing Acquisition Decisioning

15 Our Initial Plans Were Ambitious—and Evolved!
H1 2012 H2 2012 H1 2013 H2 2013 Key Events Mobilisation, Selection of FICO and Ambitious Scope Review of Scope/ Plans and Budget Define and Build for Unsecured Acquisition Testing and Implementation

16 Clear Success Criteria Established—and Achieved
RAG Examples Robust platform delivered which can handle LBG volumes/response times Green OM now supporting all core brand Unsecured Acquisition Decisioning Zero unplanned downtime since live Over 1m applications/month processed (c500k new accounts and 500k limit increases) Improved Quality of Credit Decisions and increased cross-sale opportunities Improved portfolio performance across all products Initial uplift in credit card cross sales from Current Account applications Improved speed to market/response times for strategy changes Significant reduction achieved, average turnaround has gone from months to days 46 OM releases and 128 scorecard & strategy changes implemented (31/10/2014) More consistent and simpler credit strategies developed Amber Current account and Credit Card policy rules aligned Cross heritage scorecards implemented 160k fewer referral to underwriting per annum 260k fewer bureau calls per annum Good progress made but more opportunities to take Improved ability to support other LBG initiatives and reduce regulatory costs 12 instances of legacy engine replaced by single solution Enabled business programme to provide unsecured loans to non franchised customers Significantly reduced complexity and costs of achieving Consumer Credit Reform compliance Clear advocacy amongst stakeholders and users for new system Strong advocacy with users Improved cross team knowledge and collaboration Intense demand from stakeholders to deliver Mortgage Acquisition, SME lending etc. Tangible Financial return on Investment Income, Impairment and efficiency benefits interlocked On track for 2 year payback on investment

17 Jeremy Bryson Head of Architecture and Risk Systems Lloyds Banking Group
Creating a Customer—Centric Organization

18 The Architecture We Are Working to
Credit Risk Operations: FICO® Origination Manager, FICO® TRIAD® Customer Manager, underwriting and fraud solutions Credit Risk Insight: Consolidate on a single analytical solution as the preferred solution for use of insight Internal source system level data Core source system data Integrated reporting layer Derived level data Data Layer Separate layer Operational collections and recoveries/scorecard/fraud/underwriting layer External source level data Capital System Data Accuracy System Impairment System Credit Risk Analytics System Operational Underwriting System Operational Collections and Recoveries System Fraud System Real-time Decisioning System Batch Decisioning System Risk Operation Data Store (RODS) Data Service Risk Service Model Repository Bureaux Hub Credit Reference Agencies Valuations Source Systems Acquisition Systems Operational Application Analytics System Customer System Workflow System Derived Source Data Transactional Operational Data Store (TODS) Customer Operational Data Store (CODS) Credit risk data Event level data Transaction level data Customer level data Core Non- Core 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

19 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

20 …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 complexity Avoids technology overhead of executing multiple Triad runs Demands additional work to align and simplify current product risk strategies Need 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 approach Need to leverage FICO® TRIAD® Customer Manager 8.5 capabilities (e.g. FICO® Blaze Advisor® logic) fully to achieve modular, manageable outcome & avoid exponential complexity Challenges today’s operating model Customer strategy drives significant benefits… …but requires several design challenges to be solved

21 Evolving Towards a Customer Strategy
Customer strategies Customer enabled product credit decisioning strategies Product credit decisioning strategies Single rule set One data source Common rules Common data Unique product rules Unrelated data

22 Customer Enabled Product Credit Decisioning Strategies!
Personal Current Accounts (PCA) PCA Lloyds Bank Halifax, Bank of Scotland 4 8 2 1 7 7 15 7 4 11 5 Loans Credit cards Loans Credit cards 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 Performance Employment Status Product Inappropriate Decline: Level Of Indebtedness Fraud Account On Repayment Plan Previous Loans Adverse Credit Bureau (With Notice of Correction (Noc)) 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

23 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

24 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 High Medium Unclear 6. Limit Calculations 7. Limit Management (increase/reduction)

25 Jeremy Bryson Head of Architecture and Risk Systems Lloyds Banking Group
Closing Comments

26 The Law of Unintended Consequences
Changes to product profitability measures Changes to the customer experience Changes to the customer proposition by brand Testing ‘as is’ product decisions against ‘to be’ customer decisions is not that easy A healthy tension to implement customer scores early on current systems Customer strategy segmentation may not align to marketing segmentation

27 In Conclusions Lessons learned
Stakeholders extend beyond the risk function Regulators Product owners Collections and recoveries Fraud management Senior management Marketing Look at the current operation and see if you are doing elements of customer decisioning already A need for common data definitions and common credit decisioning rules

28 Thank You! Chris Keeling
Head of Risk Programmes, Risk Infrastructure Lloyds Banking Group Jeremy Bryson Head of Architecture and Risk Systems Lloyds Banking Group

29 Please rate this session online!
Chris Keeling Head of Risk Programmes, Risk Infrastructure Lloyds Banking Group Jeremy Bryson Head of Architecture and Risk Systems Lloyds Banking Group

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