non-standard finance plc capital markets day/media/files/n/non-standard-financ… · 29/11/2017...

Non-Standard Finance plc Capital Markets Day 29 November 2017

2

John van Kuffeler Founder and Group Chief Executive

NON-STANDARD FINANCE – CAPITAL MARKETS DAY 29 NOVEMBER 2017

Agenda

3

09.15 NSF Group and market overview John van Kuffeler, Group Chief Executive, NSF plc

10.00 Branch-based lending Miles Cresswell-Turner, CEO Everyday Loans

10.45 Guarantor loans Marc Howells, MD Guarantor Loans Division

11.30 Break

11.45 Home credit Loans at Home David Thompson, CEO Loans at Home

Jono Gillespie, CFO Loans at Home

12.30 IFRS9 and funding Nick Teunon, CFO NSF plc

12.45 Summary John van Kuffeler

13.00 Close

29 NOVEMBER 2017 NON-STANDARD FINANCE – CAPITAL MARKETS DAY

4

The vision, as set out in 2015

To be a leading participant in the

UK’s non-standard finance sector

A sector with strong growth prospects,

serving 10 million adults

5

The vision, as set out in 2015


Why are we different?

When lending direct,

we meet our customers

face-to-face

Progress so far

6

¹ Net debt as at 31 October 2017 calculated as balance sheet debt (£186.5m) minus balance sheet cash (£10.0m)

Overview

Locations

NSF is one of the UK’s leading providers of non-standard unsecured credit

Listed

Customers

>158,000

Locations

120

Net loan book

£226m

Staff

>700

Agents

>1,000

Net debt1

£176m

Market cap

£238m

Key stats

• Three acquisitions made in August 2015, April 2016 and August 2017:

• branch-based unsecured lending: Everyday Loans

• guarantor loans: George Banco and TrustTwo

• home-collected credit: Loans at Home

• Long-term funding in place

• Blue-chip shareholder base


Our three business divisions

7

Market position #1 #2 #3

Acquisition Date: April 2016 April 2016/August 2017 August 2015

Net Loan Book1 (£m): 143.7 43.8 38.1

Annual loan book growth1 20% 33% 40%

Number of staff 307 82 350

Number of customers1 45,200 16,200 96,800

Loan Size (£m): £1k - £15k £1k – £10k £100 - £1k

Duration: 1 – 5 years 1 – 5 years 24 – 75 weeks

APR Range: 24% – 299% 37% - 62% 164% - 733%

Average Customer Income: c. £30,000 c. £24,800 c. £14,500

1 As at 31 October 2017. Note loan book growth figure for guarantor loans is on a pro forma basis

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Branch-based lending Guarantor loans Home credit


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Macroeconomic backdrop

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Employment

Employment is at all time highs

Unemployment lowest since 2005

Latest ONS data:

o Headline employment rate: 75.0%

o Unemployment rate: 4.3%


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3

4

5

6

7

8

9

Jul to Sep2012

Jul to Sep2013

Jul to Sep2014

Jul to Sep2015

Jul to Sep2016

Jul to Sep2017

UK unemployment rate % al people that are active

70

71

72

73

74

75

76

Jul to Sep2012

Jul to Sep2013

Jul to Sep2014

Jul to Sep2015

Jul to Sep2016

Jul to Sep2017

Employment rate %

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Adults on low pay has dropped from 20.5% of the population in

2015 to 18.4% in 20171

Since 2013 the income of the lowest 10% of earners has

increased by 16.2% - twice the rate of the top 10%

1 low pay is defined as the value that is two-thirds of median hourly earnings and high pay is defined

as the value that is 1.5 times median hourly earnings.

Source Annual Survey of Hours and Earnings (ASHE) – Office of National Statistics

Earnings


Annual growth in gross earnings

2013 2014 2015 2016 2017p

Lowest 10% 2.6% 1.0% 3.7% 8.4% 2.2%

Note 2017 figures are provisional

11

Inflation

Inflation has been increasing – 3% in September 2017

Transport, and food and non-alcoholic drink prices have

been important factors in driving the changes in the rate

Food inflation is at its highest for four years, driven by the

drop in Sterling following the EU referendum

But, inflation is expected to peak at 3.2% in October before

falling back


Source Inflation report, November 2017 - Bank of England

1 based on constant nominal interest rates at 0.5%, other policy

measures as announced

CPI inflation projection1

12

Income versus inflation

Tenth percentile of earners have seen incomes rise strongly in recent years – up over 16% since 2013

Inflation over the same period is up c6%

These consumers are therefore well-placed to cope with current level of inflation

No signs of increased financial stress in any of our business divisions

All three divisions are experiencing reduced levels of impairment


13


Brexit – threat or opportunity?

We are a UK-focused business

We are not unduly exposed to the international migrant community

There has been no impact on our business to-date

Uncertainty not good for business or the economy

We already have long-term funding in place

14

Key drivers of demand


Low paid

Low credit status

Credit impaired

Self-employed

Recently arrived immigrants

Risk appetite of mainstream lenders

Low credit status

Credit impaired

Low paid

2.9m Recently arrived migrants5

Over 912,000 consumer County Court

Judgements4

c.1% of total work force at or below minimum wage²

c.15% of total work force

self-employed³

1 LEK consulting – Executive Insights April 2016 2 ONS: Low Pay in the UK: April 2016 3 ONS: UK Labour market, May 2017 4 Registry Trust Limited – Press release, 1 February 2017 5 Migrants to the UK from Sept 2012 to Sept 2016 – ONS: Overview of the UK population, February 2017

15

Low pay – changes to the national minimum wage and national living wage


Year 25 and

over

21 to 24 21 and

over

18 to 20 Under

18

Apprentice

2017 £7.50 £7.05 £5.60 £4.05 £3.50

Oct16 to Mar17 £7.20 £6.95 £5.55 £4.00 £3.40

Apr16 to Sept16 £7.20 £6.70 £5.30 £3.87 £3.30

2015 £6.70 £5.30 £3.87 £3.30

2014 £6.50 £5.13 £3.79 £2.73

2013 £6.31 £5.03 £3.72 £2.68

2012 £6.19 £4.98 £3.68 £2.65

2011 £6.08 £4.98 £3.68 £2.60

2010 £5.93 £4.92 £3.64 £2.50

Source – www.gov.uk; Office of Budget

Responsibility

£5.00

£5.50

£6.00

£6.50

£7.00

£7.50

£8.00

£8.50

£9.00

2013 2014 2015 2016 2017 2018 2019 2020

National minimum wage 25 and over

National living wage

OBR Forecasts

Those on low incomes have benefited from a 4.4% CAGR

in the National living wage since 2013

This rate of growth is expected to continue to 2020

16

Credit impaired


Mainstream banks tightening scorecards

Increase in County Court Judgments in England and Wales

Increased use of bailiffs by councils and others:

In 2014-15 councils passed 2.1m debts to bailiffs

In 2016-17 this had increased to 2.3m

Source: Stop The Knock - Money Advice Trust, November 2017

Change in CCJs

YoY vs 2016

Q3 17 +24%

Q2 17 +41%

Q1 17 +35%

17

Self-employed


3,500

3,700

3,900

4,100

4,300

4,500

4,700

4,900

12.0%

12.5%

13.0%

13.5%

14.0%

14.5%

15.0%

15.5%

Jan-Mar 2009 Jul-Sep 2010 Jan-Mar 2012 Jul-Sep 2013 Jan-Mar 2015 Jul-Sep 2016

Total number of self-employed % of total workforce that is self-employed

18

Immigration


The number of immigrants coming to the UK continues to

rise

Net long-term international migration was estimated to be

+246,000 in year ending (YE) March 2017, down 81,000 from

+327,000 in YE March 2016

There has been a net increase every year

Immigrants are a small proportion of our customer base

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Net migration Gross immigration

APRIL 2017 19 NON-STANDARD FINANCE – 2016 FULL YEAR RESULTS

Regulatory backdrop

20

Nick Teunon Group CFO

Heather McGregor Non-Executive Director

Niall Booker Non-Executive Director

Charles Gregson Non-Executive Chairman

Miles Cresswell-Turner Executive Director Ex

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NON-STANDARD FINANCE – CAPITAL MARKETS DAY 29 NOVEMBER 2017

Our highly experienced Board is in tune with the regulatory environment

John van Kuffeler Group CEO

What we have achieved so far

21

Established a good relationship with FCA

April 2016 – change of control for Everyday Loans

June 2016 – FCA licence for Everyday Loans and TrustTwo

May 2017 – FCA licence for Loans at Home

September 2017 – FCA licence for George Banco

Engaged with other key stakeholders

MPs/ members of House of Lords

Consumer groups (StepChange, CAB, Money Advice Trust)

Think Tanks

Appointed to National Executive of Consumer Credit Association


Key regulatory themes for NSF

22

No material issues for branch-based lending or guarantor loans

We are addressing some specific questions around home credit:

Why models of ‘predictable financial stress’ in other sectors do not apply

FCA examining refinancing…but repeat borrowing in home credit is not

the same as ‘rollovers’ in payday or other ‘running account’ products

Why APRs are so high?

o Loan amounts are small and for short periods

o High loss rates and an expensive operating model

o Actual APRs are lower as most customers pay late

Why other models are unable to service this large customer segment

Waterbedding

o CCJs/other debt default/unpaid bills/bailiff activity

o Illegal money lending


Current initiatives

23

Continuing our outreach programme in Westminster

Responding to consultations:

FCA High Cost Credit Review

HM Treasury – breathing space

Treasury Select Committee – household debt

Matthew Taylor Review and Select Committee proposals

Horizon scanning

Embedding Vision, Mission and values/behaviours

Planning for Senior Managers and Certification Regime


APRIL 2017 24 NON-STANDARD FINANCE – 2016 FULL YEAR RESULTS

Competitive landscape

25 29 NOVEMBER 2017 NON-STANDARD FINANCE – CAPITAL MARKETS DAY

The supply of alternative lending has increased since 2011

2016 (£bn) CAGR 11-16

0.2 (34%)

0.2 n/a

0.1 11%

0.2 16%

0.2 (5%)

0.5 34%

0.2 (13%)

0.8 (4%)

1.0 24%

0.5 (2%)

1.3 7%

1.6 (1%)

2.0 1%

4.0

4.1 16%

16.6 6%

Source: NSF estimates

-

2

4

6

8

10

12

14

16

18

2008 2009 2010 2011 2012 2013 2014 2015 2016

Inactive unsecured

Online unsecured lenders

Logbook loans

Branch-based lenders

Pawnbroking

Guarantor loans

HCSTC Online lenders

Home collected credit

Car finance

Rent to buy

Credit Unions

Store cards

Mail order

Point of sale loan

Sub-prime Credit Cards

£bn

Competitive landscape Loan Size

APR

£500

£1000

£5000

30% 50% 75% 100% 200% 1000%

26

(Lift)

HCSTC price cap


https://www.oakam.com/en2/why-us/lift-loan

27

Branch-based lending:

Macro economic backdrop has been positive with record levels of employment

No material issues from a regulatory perspective

Few profitable competitors

Guarantor loans:

Macro economic backdrop has been positive with record levels of employment

No material issues from a regulatory perspective

Opportunity to strengthen our #2 position further as a number of smaller players continue to make losses

Home credit:

Macro economic backdrop has been helped by above average earnings growth for low paid

FCA examining refinancing

Market opportunity: we have effectively acquired a business more than half our size, for £5m investment

437 agents added

40% loan book growth before peak lending season

20 new offices

90 additional staff


Summary of our marketplace

28


Conclusions on our marketplace

Loan Book Growth

Impairment: revenue

Risk-adjusted margin

Target

12m to

Oct-17

12m to

Jun-17

12m to

Oct-17

12m to

Jun-17

12m to

Oct-17

20%

20%

19.6%

17.9%

35.7%

37.30%

20%

33%

15.3%

14.6%

27.5%

30.50%

20%

40%

37.5%

32.9%

95.4%

98.20%

29

Questions


everydayloans for everydayliving

Branch-based lending

Miles Cresswell-Turner

CEO


Agenda

1. Introduction

2. History

3. Everyday Loans business model

4. Customer demographic

5. Customer waterfall

6. Strategy for growth

7. Summary


• Everyday Loans is the UK’s largest branch-based lender of unsecured loans to sub-prime borrowers

• It has a network of 53 national branches

- 5 branches opened in 2016

- 12 branches opened in 2017

• By using a face-to-face model, our USP is being able to lend profitably to those customers that others can’t or won’t

• Our loans are unsecured and distributed through three main channels:

- Brokers 33%

- Direct to brand 36%

- Own book renewals and former borrowers 31%

1. Introduction - overview


Financial crisis • Large numbers of consumer

finance businesses exited the

market including:

o Black Horse

o Citifinancial

o HFC/Beneficial

o Welcome

o London & Scottish

• Everyday Loans was the only

remaining branch based

consumer lender (not high cost,

short-term) in the UK

Founded in 2006

June 2012

Purchased by

Secure Trust Bank

26

April 2016

Acquisition

Completed

following

FCA change

of control

2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2006

August 2017

George Banco

acquired

27 31 36 34 41 26 26 No. of

branches

2. History - timeline

26 30

^ as at October 2017

December 2015

Purchase by

NSF

Announced

60 67 78 105 89 125 54 47 Receivables (£m) 41 27

53

145^

June 2016

Full FCA

Licence granted


2. History - timeline


• Delinquency continues to receive management focus as we strive to optimise growth.

• Collection policies and procedures are being continually revised and updated to take into account lessons learned.

• The business extended its customer profile further down the credit spectrum in 2016 and while impairment

increased slightly, it is within tolerance and risk adjusted margins remain strong.

2. History – timeline - Impairments as a % of average net receivables

16% 16%

18%

10% 10%

8% 8% 8% 7%

9% 8%

0%

5%

10%

15%

20%

2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 YTD 2017

1 Annualised to 31 October 2017


• Branches offer full service lending and collecting

• Off-high street retail premises and first floor offices

• National coverage - majority of customers live within five miles or 30 minutes of a branch

• Customers are able to establish/repair credit history and branches provide “money management” service for financially unsophisticated customers

• All loans are unsecured with homeowners making up approximately 20%-25% of customers

• Risk based pricing allows true full-spectrum lending for the right loan amount at the correct price

• Customers are focused on certainty of obtaining credit and monthly payment, not rate:

• £1,000 to £15,000

• 24% APR to 299% APR

• 12 months to 60 months

3. Everyday Loans business model


4. Customer demographic

• Average loan size is £3-£4,000

• 58% of loans being £4,000 or less

• Over 57% are under the age of 40

• 45% are single

• 71% earn more than £1,500 per month

• 42% earn more than £2,000 per month

• 32% of loans are at an interest rate of less than 50%

• 66% have no dependents

• 42% rent; 28% are homeowners; 23% live with parents

• 71% have been at the same address for more than

three years

• 75% have been at their job for more than three years


5. Customer waterfall – as at 30 June 2017


5. Customer waterfall – update to 31 October 2017

Central

FINANCIAL BROKERS 72% of applications

(33% of loans booked)

DIRECT 25% of applications

(36% of loans booked)

OWN BOOK RENEWALS/FORMER BORROWERS

3% of applications (31% of loans booked)

100% UK RESIDENTS, EARNING AVERAGE INCOMES,

CREDIT IMPAIRED, THIN CREDIT

Duplicates /incorrect

info

Credit score

Credit history

Customer

waterfall

65%

declined

35%

accepted

22% receive

telephone

interview

6% attend

branch and

3% get

a loan

13% no

response/decline

16% declined/fail I&E

In-branch


Annual trends positive but…

we felt that we could do more…

and needed a change of

pace and ambition

6. Strategy for growth


Miles Cresswell-Turner

CEO

Jon Wiggins

MD

Branch Network

Jason Bovington

Credit Risk

Andrew Wayland

Marketing

Steven White

CFO

Jonathan Hole

Compliance

Mareena Flint Head of HR & Training

Miles Cresswell-Turner:

33 years’ experience in Financial Services industry, 18 years in PE

Executive Director and co-Founder of Non-Standard Finance

Joined Everyday Loans as Chairman in April 2016; became Exec

Chairman in May 2017

Became CEO of Everyday Loans in September 2017

Steven White:

28 years’ experience in Financial Services industry

Arthur Andersen, UBS & Deutsche Bank

Previously at Link Financial UK

Chartered Accountant ICAEW

Andrew Wayland:

Helped set up Everyday Loans as Head of Marketing in 2006

Business owner Columbell Communications for 5 years

Previously Head of Commercial Development Tech start-up

Jon Wiggins:

28 years’ experience in Financial Services Industry

Joined Everyday Loans in May 2017

Previously at CitiFinancial and Citibank

Jason Bovington:

Helped set up Everyday Loans as Head of Risk in 2006.

20 years’ Financial Services experience

Previously Head of Risk HFC Bank PLC

Jonathan Hole:

33 years’ experience in Financial Services industry

Joined Everyday Loans in August 2017

Previously worked for Barclays, Santander and Aldermore

6. Strategy for growth - step 1: Strengthened and reinvigorated management team

Mareena Flint

25 years’ experience within HR & Training

Joined Everyday Loans in January 2017

Previously Provident Financial Group

Chartered member of the CIPD


1. Expanding the branch network and new premises • 12 new branches

• relocated/refurbished 16 branches (8 still in progress)

• Additional office space in Bourne End

2. Improved service to customers • Moved to same day Faster Payments • Introduced eSignature • Launched 12-month loan product

3. Hired additional key personnel: • New Chief Accountant and increased analytics resource • Dedicated In-House Trainer and additional training instructor • Head of Collections • Head of IT

4. Established bespoke training capabilities • Sales, Collections and Management Development

5. Improved employee communications • Launched Employee Forum • Launched videoconference in all branches • Started a regular staff newsletter “Grapevine’ • Launched intranet

6. Strategy for growth - step 2: Invested in our network and supporting infrastructure


1. Sharing of best practice • Identified best in class managers • Began a process to cross-fertilise this to other branches • Work begins on the ‘Everyday Way’

2. Increasing number of leads • Building deeper partnerships with key brokers • SEO and digital marketing

3. Increased operational efficiency • Dialler to allow outbound call campaigns and resource sharing across branches • Launched new ‘Areas’ to allow pooling of resources and extended opening hours

4. Upskilling of existing staff and management • Roll-out of training modules on Sales, Collections and Management Development

4. Product expansion • Launch of Selfy product • Launch 12-month product

6. Strategy for growth - step 3: increasing productivity


6. Strategy for growth - the results: application volumes

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110

Jan-17 Feb-17 Mar-17 Apr-17 May-17 Jun-17 Jul-17 Aug-17 Sep-17 Oct-17

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Change of gear


6. Strategy for growth - the results: new borrower applications to branches

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6. Strategy for growth - the results: new borrower conversion rates

5.5%

6.0%

6.5%

7.0%

7.5%

8.0%

8.5%

9.0%



6. Strategy for growth - the results: new borrower loan units written

1,000

1,200

1,400

1,600

1,800

2,000

2,200

2,400

2,600



6. Strategy for growth - the results: yield on new loans written

57%

58%

59%

60%

61%

62%

63%



6. Strategy for growth – the results: lower total delinquency (% of average net receivables)

7.0%

7.5%

8.0%

8.5%

9.0%

9.5%



6. Strategy for growth – further expand our branch network

• 12 locations identified and in progress; 9 branch managers

identified and in-training

• All planning to launch in H1 18

• Streamlined opening process, enhanced staff selection

methodology, new 2 week induction plan

• 3-6 branches per year thereafter

• Targeting 70-75 branches by end of 2020

Reminder of branch economics

• Pre-opening P&L costs up to £75k

• 0-12 months EBIT £(105)k

• 12-24 months EBIT £165k

• 24-36 months EBIT £300k


• More leads from new corporate relationships with lead generators and corporate affiliations

• Increase our conversion rate

• Will again remove the lowest converting brokers

• Recognise our market position by asking more of brokers

• Fully embed best practice across the network

• Branch manager conference

• Leaders conference

• Roll out of Area Manager methodology

• New courses from our Training and Collections functions

• Efficient communications via the website and VC tools

• Very proactive education, methodology and partnerships to continue our focus on collections

6. Strategy for growth - further improve our productivity


• Our fixed cost base has increased as a result

• This is a single step increase, annualising over two years and includes:

• A further 12 new branches in H1 2018

• Additional staff for existing branches

• Relocation and upgrade of existing branches

• Additional space at Bourne End for Network and Guaranteed expansion

• Upskilled Senior Management

• Installation and utilisation of network telecoms dialler

• Enhanced Training, Compliance, Credit, IT and Finance

• Total admin costs increase by £1m in FY 2017 and £3m in FY 2018

6. Strategy for growth - Enhanced performance required significant investment

The opening of the Group’s 50th branch in Bradford earlier this year


• The opportunity for growth remains significant with unsatisfied demand and few direct competitors

• Whilst an expensive service to deliver, our branch-based model is proven in delivering profitable growth

• We have made significant investment in our infrastructure : • New / relocated branches

• People

• Training

• Products

• Culture

• This investment is already yielding positive results:

• Loan book growth +20%

• Delinquency down

• Increased risk-adjusted margins

• Plan for 2018:

• 12 more branches to open

• Further productivity gains

• There is a great sense of excitement about the prospects for our business

7. Summary


Questions


NSF Guarantor Loans Division

One Division, One Team, Two Brands, Two Locations


• George Banco/TrustTwo (Guarantor Loans Division) is the clear #2 in guarantor loans

• 82 employees – Beckington, Somerset (58) and Bourne End, Berkshire (24) 1

• 16,200 Customers (and Guarantors) 1

• £43.8m loan book (before fair value adjustments)1

• Key areas of focus:

i. Execute and complete 100-Day Plan

ii. Ensure full recovery at George Banco from lending hiatus earlier in 2017 (Sept - Nov 2017)

iii. Stabilise both businesses and build momentum across both locations (Oct-Dec 2017):

• Strategy now based on:

• ‘One Division – One Team – Two Brands – Two Locations’

• Defined and agreed pathway to ‘Target Operating Model (TOM)’

• Build Business Architecture; People-Process-Technology

• Execute short-term tactics to maintain capture of market share

• Crystallise strategy based on data analytics

1. Introduction

1 As at 31 October 2017


2. Management

Marc Howells

Managing Director

James Broderick Head of Development

Neil Critchley

Chief Operations Officer

Shared Services Beckington

Jess Franklin Head of Sales

Alex Przytocki Head of Collections

Dave Beer Head of Underwriting

Bourne End

Jen Bradbury Team Manager Sales

Liisa Sabah Team Manager –

Support

Lakveer Raj Team Manager

Collections

• Highly experienced leadership team

covering two operations and locations

• Shared Central Services provided by

Everyday Loans

• Local oversight of shared central services

• Additional hires in Q1 2018:

• Operations manager – Bourne End

• Additional front-end developers


• Total receivables of c.£440m at the end of 2016 (FCA)

• Amigo dominates with 80%+ share

• Current GLD market share is c.8-10%

• Annual issuance of c.£380m

• Historic CAGR of c30% per annum

• Extrapolation of recent trends implies potential receivables of up to £1bn by year end 2019

2. Market opportunity

Provider Loan book (£m) 1

+

1 Based on latest public filings

476

43.8

23.0

20.1

15.0

6.6

Guarantor loans outstanding across the industry (£m)1

440

55 78

106 139

184

248

294

345

2008 2009 2010 2011 2012 2013 2014 2015 2016


• Capitalise on strong underlying market demand

• Strengthen our position as the clear #2

• Share best practice

• Optimise key performance metrics at each point of the customer journey

• Focus on combined market share - relaxed as to growth split between brands

• Targets:

• double loan origination by the end of 2019

• 2019 year-end receivables of >£80m

• c.20% return on asset by end of 2019

3. Headline objectives

This ambitious target will be achieved

through the transition to our

Target Operating Model

Targeted loan book growth for Guarantor Loans Division

£0

£20

£40

£60

£80

£100

£120

£ m

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TT net loan book GB net loan book Combined

Acquisition by NSF


4. Our Target Operating Model

• Focus will be on four acquisition channels across two brands

• Both brands have clear strengths but in different channels:

• Financial brokers – George Banco

• Price comparison websites – TrustTwo

• Direct – TrustTwo

• Branch-referrals – TrustTwo

• Single operating system:

• Move to a single platform in 2018

• New management information portal based on GB tech

• Targeting launch within 12 months

• Attract and retain the best talent

• Common underwriting approach and dashboard

• Two collections teams (0-90 days and >90 days)

• Launch of “Customer Stratification”

Financial

brokers PCWs Direct

Branch

referrals

Consumer demand

Common underwriting and dashboard

Centralised collections > 90 days

Collections for up to 90 days

Single loan management system

Centralised risk management


4.1 Leveraging our two brands

• Both brands already have clearly identified and different market positions

• TrustTwo known as a significant and competitive guarantor loan product on comparison websites

• George Banco is known to brokers as a core provider of guarantor loans with a good conversion rate

• Continuing to operate both brands will maximise market coverage and provide multiple capture points

• Customer segments vary by source, quality, profile, price - a guarantor loan IS NOT a simple product

• Current data deficit on interaction between both brands – need detailed analysis on:

• Side-by-side comparisons; in direct competition

• Hierarchical; GB processes TT declines

• Blend of above

• Marketing spend to be focused at TrustTwo while George Banco will remain broker-driven.


NSF GLD

• A single platform leveraging the market positioning of both brands:

• Take the best of both

• New infrastructure for the Guaranteed Loans Division

• Basic back office with ELL front-end build

• ELL own front-end IP

• Reduce reliance on 3rd party dependencies

• Enable a straight-through-processing (‘STP’) approach for standard applicant

• allowing time to be spent on applications where personalised analysis would benefit the process

• significant efficiencies and economies of scale to be realised

• One system – Multiple (4) journeys

4.2 Two brands, one operating system

Ryland

PanCredit

SuperUser

Nostrum

SuperUser

2

TBA

+


• Define ‘Operational Architecture’ including a clear strategy for two operational locations (Jan 2018)

• Develop shared Vision, Mission, Values

• Clearly defined management structure (Local & Central)

• Harmonised incentive programs (Meritocracy)

• Succession planning – introduced ‘Senior CAM role’

• Stronger requirements on recruitment – ‘Fit-for-purpose’

• Robust Training program – ‘Cradle-to-grave’ – Introduced 5-day induction program for new employees

• Management Training;

• Sales Process

• Underwriting

• Collections

• Performance Management

• Time Management

• Develop GLD Academy

• Management incentive on people turnover (“regretted”)

4.3 Attract and retain the best talent


• Aspirational channel mix development: to improve balance further with growth in all channels

• Leverage exiting Group leads and existing customers to optimise acquisition costs

• Seek to diversify from overweight broker position

• Spread risk of margin compression from price comparison websites

4.4 Acquisition channels

68%

26%

6%

Current GB loan mix

Broker

Top-ups

Organic

15%

16%

9%

36%

5%

9%

10%

Current TT loan mix

Broker

Top-ups

Organic

Price comparison

ELL online decline

ELL Branch decline

Lead generator

53%

23%

7%

10%

2% 2%

3%

Current combined loan mix

Broker

Top-ups

Organic

Price comparison

ELL online decline

ELL Branch decline

Lead generator


• Map customer profiles journeys across both brands

• 120,000 GB leads + 82,000 TT leads

• Modify customer journey for both brands:

• Common entry point enables profiling, ‘passporting’ and bespoke communication to each lead – value creation

• Re-define de-duplication process across Division / Group

• Live-tracking of leads across operational areas

• Live waterfall; trigger points mapped to customer journey

• Develop ‘levers’ to impact trigger points

• New communications test platform: ‘Test-Learn-Invest’

• Implement basic communications tool

• SMS, email, What’sApp

• Credit quotation search against filtered, accepted leads

• Two-way SMS communication

• Live chat

4.5 Customer ‘Stratification’

Financial

brokers PCWs Direct

Branch

referrals

Consumer demand

Common underwriting and dashboard

Centralised collections > 90 days

Single loan management system

Centralised risk management

Customer profiles mapped, live tracking, duplicates

removed and leads distributed

Collections for up to 90 days


• Develop common underwriting platform

• Two teams of highly trained underwriters (ACEJPSIII)

• Proven cycle of development for underwriters: (i) Customer Services (ii) Collections (iii) Underwriting (iv) First-Instalment-Defaulters

• Incentives linked to balanced scorecard, good customer outcomes/customer service, volume and delinquency

• Automated data capture and scoring

• Risk-based pricing

• 2019 target: 20% straight-through-processing, 80% subjective

Illustrative George Banco Pricing Model

Trust Two Pricing Model

4.6 Underwriting

TrustTwo Pricing APR

Price comparison websites 37.90%

Price comparison websites > £4,500 37.40%

Standard - Guarantor homeowner 43.80%

Standard - Guarantor non-homeowner 48.90%

Score A

or less

Score B

or less

Score C

or less

Score D

or less

Score E

or less

Score F

or less Total

Score G or less Decline Decline Decline Decline Decline Decline

Score H or lessDecline 61.8% 61.8% 61.8% 61.8% 61.8%

Score I or lessDecline 61.8% 61.8% 61.8% 49.7% 49.7%

Score J or lessDecline 61.8% 49.7% 49.7% 49.7% 49.7%

Score K or less61.8% 49.7% 49.7% 49.7% 49.7% 49.7%

Score L or less61.8% 49.7% 49.7% 49.7% 49.7% 49.7%

Total

Guaranator - Gauge

Ap

plic

ant

- G

auge

Decision


• Harmonised Lending Manuals (December 2017)

• Move to common ‘Credit Reference Agency’ (CRA) – CallCredit

• Automate use of CallCredit products

• CallCredit to develop bespoke Guarantor Loan Scorecard

• Automated initial assessment of affordability (Share/TAC/ONS)

• Collection tools for underwriting (Retreiver, Lexus Nexis)

• Use of social media and web data (Facebook, LinkedIn, Google Maps)

• Use of available face-to-face communications (F2F), FaceTime / Skype

• Post-2019 use of machine learning and facial recognition

4.6 Risk management


• Harmonised Collection Manuals (December 2017)

• Merge People-Process-communications

• Implement GB processes with TT (Work queues, rewrites)

• Front-end collections up to 90 CD

• Centralise during 2018 (when able);

• Collections > 90CD

• Fraud

• IVA / Bankruptcies

• DMA

• Implement ‘First Instalment Defaulters’ in KPIs

4.7 Collections


• Combine both businesses onto a single management platform in 2018

• Common collection of data & metrics

• Common data warehousing

• Customer and process waterfalls

• Automated production of KPIs

• Forecasting based on latest trends

• Leveraging of database to analyse performance by cohort

4.7 Data management and reporting


• Strong position in a rapidly growing market

• Highly experienced management team with proven track record of delivering profitable growth

• Long-term funding in place

• Complementary positioning of two leading brands

• 100-day plan complete, now moving towards Target Operating Model:

• Single loan management platform and data analytics

• Customer stratification with single entry point across multiple brands

• Common underwriting and risk management processes

• Localised collections, supported by central collections team (>90 days)

• Real-time management information

• Tailored communications tools

• A/B testing of new products and channels

• Recent trading performance encouraging

5. Conclusion


Questions

Coffee break

72 29 NOVEMBER 2017 NON-STANDARD FINANCE – CAPITAL MARKETS DAY

29 November 2017

1

Agenda

• Market overview

• Loans at Home overview

• Key success factors

• The market opportunity

• Operational results vs 2016

• Expansion-related costs

• New technology

• Outlook and Summary

Market overview

• Stable market of around 3 million regular users of

which c1.8m historically borrow at any one time.

• Recent sharp decline in Provident customer numbers

caused c1.8m to fall to c1.6m1

• Customer incomes approximately £10k to £15k in C2,

D and E socio-economic groups

• Typical loan size £200 to £1,000

• Weekly collections from the customer's home.

• Regulated by the FCA

1 Technical Annex 1 – High Cost Credit Review - FCA

Loans at Home - history

• Established in 1938, Loans at Home has nearly 80 years of experience in the Home Collected

Credit market

• Formed from Home Collected Credit businesses of S&U PLC and acquired by NSF plc in

August 2015

• Since acquisition, the business has received significant investment:

• Management

• Training

• Technology

• Compliance infrastructure

• Office network

• No change to core agent / customer relationship-focused model

Loans at Home – business model

• Focused exclusively on Home Collected Credit

• No default fees or default interest charged on any loans

• Service delivered exclusively by self-employed agents visiting customers’ homes, supported

by a UK-wide network of offices

• Offer a simple range of four products based on term of loan:

Weeks Charges per

£100

Total

Payable Weekly Rate APR

24 £60 £160 £6.67 732.7%

33 £65 £165 £5.00 433.4%

45 £80 £180 £4.00 340.0%

75 £87.50 £187.50 £2.50 163.8%

Loans at Home – size

• Just under 100k customers in October 2017

• Service delivered by a team of over 1,000

self-employed agents

• 20 new locations added to branch network in

2017 to support strong growth. Currently 65

branches.

• c350 employees supporting the agents

Loans at Home - customer profile

• c96% have a mobile phone

• c89% have online access

• c93% have a bank account

• c35% have a PayPal account

• c5% use pre-paid debit cards

• c24% overdraft facility

• c15% have direct debit loan

• c18% have goods on credit

• c40% aged 21-39

• c25% aged 40-49

• c70% female

• c50% have employed person in household

• c92% C2, D or E

• c90% rent – 65% council, 25% private

• c72% receive benefits excl. child benefit

• Average annual household income £16,000

Loans at Home - customer profile

Use of loan

• c27% home improvement

• c13% presents

• c18% holidays

• c9% bills

• c8% car expenses

• c5% baby/child expenses

• c20% other

Loans at Home - customer satisfaction

Source: Customer research undertaken by PCP Market Research among 300 customers

Other NPS scores taken from npsbenchmarks.com – UK consumer net promoter benchmark

Key success factors

• Strong Agent/Customer relationship

• Recently captured some customer stories showing the unique relationship with their Loans at

Home agent

• Like to share a few of those stories…….

Key success factors – agent/customer relationship

Key success factors


• Open, positive culture

• Culture is an ongoing key strategic focus

• Held workshops in early 2017 with stakeholders from all levels and areas of the business

• Established what really mattered to people

• The Key cultural elements that we strive to protect and improve are:

• Team-minded – doing what’s right for the team over yourself

• Integrity – vital at all levels of the business

• Customer service – setting the highest possible standard

• Keep it simple – vital for our industry

Key success factors - our culture

• Staff and agents are treated with dignity and respect

• We are a company that listens to our people

• Senior team regularly visit branches and spend time with staff and agents

• Feedback sought and acted upon

• Significant competitive advantage in current market

• Future growth dependent on retaining the excellent team we currently have and being

able to continue to attract the best people in the industry

• Our open, positive culture allows us to do this.

• Major success in 2017 and opportunities still presenting themselves.


• Culture formed the “foundation” of our business

• Technology platform also vital

• Established “Pillars” of our business.

• Regularly reviewed, to ensure we’re following the right path.

• Together, the foundation and pillars form “Our Home”


Key success factors



• Sector leading technology (see later slides)

• Experienced management team – great blend of knowledge and experience

Paul Gill

Chief Risk

Officer

Jono

Gillespie

CFO

David Thompson

Chief Executive

Officer

Sam

Beardsley

Head of

Operational

Risk

Chris

Pearson

Head of FPA

Jamie Place

Head of IT

Kat Hackett

Head of

Marketing

Christine

Rangeley

HR

Director

10 Regional Managers

46 Area Managers

c160 Business Managers

c.1,000 Agents

Mike

Palmer

Chief

Operating

Officer

Sarah Day

Company

Secretary

Simon

Brown

Head of

Compliance

Clayre

Hughes

Head of

Business

Change

Asif

Nadeem

Head of

BI and

Architecture

Gordon

Withers

Head of

Operations

support

Divisional

Managers

x3

Lisa Quirke

Head of

Development

Key success factors – experienced management

Key success factors



• Sector leading technology (see later slides)

• Experienced management team – great blend of knowledge and experience

• Key focus on looking after current agents, only adding quality new agents

• Supporting agent and customer growth with investment in infrastructure:

• Training

• Compliance and oversight

• Field Managers in appropriate locations

• New offices

• Close monitoring of performance via tailored MI

• Funding

The market opportunity

• Provident’s move away from self-

employed to employed model

significantly disrupted the market

• Problems with the new model led to

sharp decrease in Provident's

customer numbers and receivables

• Provident’s ex-customers still have

lending needs

• Not what we planned for, but major

opportunity to increase market share

0

100

200

300

400

500

600

700

800

900

1,000

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1.6

1.8

2.0

2012 2013 2014 2015 2016 Oct-17

£ m

illi

on

Mil

lio

ns

of

cu

sto

me

rs

Provident Decline

Customers (m) Receivables (£m) - RH scale


• Recognised need for carefully managed approach to growth given missed-step in Summer 2016

• As previously shared, major reason for sub-optimal growth outcomes in 2016 was due to growth via

inexperienced agents

• Following Provident’s strategy change, a large number of experienced agents with proven track

records left Provident, but still wanted to be agents

• Loans at Home was less well-known to agents than others in the industry, but word quickly spread

about our culture, leading many agents to believe we were the best partner for them

• Objective was to achieve original 2017 planned level of EBIT after temporary agent support

payments…but the opportunity was even greater than expected

• To harness the opportunity and underpin further future growth, we have invested a total of £5m in

2017


• Lessons learned from 2016 led to a better understanding of risks of growth.

• Risks managed by:

• Establishing P&L’s for each agent

The market opportunity – example agent P&L


• Lessons learned from 2016 led to a better understanding of risks of growth.

• Risks managed by:

• Establishing P&Ls for each agent

• Close monitoring of collections performance at agency level

• Strict approvals process for agent support packages

• Ensure supporting infrastructure grows ahead of customer growth

• Maintain tight focus on underlying business

• We are seeing the benefits of this process…

Operational results vs 2016

600

650

700

750

800

850

900

950

1,000

1,050

Jan-17 Feb-17 Mar-17 Apr-17 May-17 Jun-17 Jul-17 Aug-17 Sep-17 Oct-17 Nov-17 Dec-17

Agencies

Total journeys Prior Year


0%

2%

4%

6%

8%

10%

12%

-

10

20

30

40

50

60

70

80

90

100

Nov-16 Dec-16 Jan-17 Feb-17 Mar-17 Apr-17 May-17 Jun-17 Jul-17 Aug-17 Sep-17 Oct-17

Vacant Agencies

Vacant Vacant %


-

1,000

2,000

3,000

4,000

5,000

6,000

7,000


New customers

Actual Prior year


80,000

85,000

90,000

95,000

100,000

105,000


Total Customers

Actual Prior Year


30,000

35,000

40,000

45,000

50,000

55,000

60,000

65,000

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Quality Customers

2017 2016

• To underpin the growth in agents

and customers, 20 new branches

were needed.

• These branches will also provide a

platform for future growth

Aberdeen Gateshead

Barnsley Havant

Basildon Kings Lynn*

Berwick upon Tweed* Leicester

Bromsgrove Milford Haven

Chelmsley Wood Newark

Corby* Pontypool

Didcot St Austell/ St Stevens*

Doncaster Wimbledon

Dundee Wood Green (Enfield)

* Opening soon

Significant network expansion

Financial results vs 2016

30,000

35,000

40,000

45,000

50,000

55,000

60,000

65,000


Quality Customers

2017 2016


40%

45%

50%

55%

60%

65%


Quality as % of Total Customers1

2017 2016

1 Customers that have made 70% of their due payments over the previous 13-week period


0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Jan-16 Apr-16 Jul-16 Oct-16 Jan-17 Apr-17 Jul-17 Oct-17

Gross loan book arrears banding % mix

A B-C D-H I-L M


0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Lending Product Mix %

24wk 33wk 42wk 45wk 50wk 75wk Other


20

22

24

26

28

30

32

34

36

38

40


Net Receivables £m

Actual Prior Year

Expansion-related costs

• Variety of costs incurred to support this one-off growth opportunity

• Temporary agent commission costs of c£3m in 2017

• needed to support new agents until round developed.

• will significantly reduce in 2018

• Additional infrastructure costs of c£2m in 2017

• management/support staff, technology and new offices

• will increase to c£3.8m in 2018 as only part-year in 2017

• New branches all heading towards profit generation in early 2018

• Collectively, agents joining established branches are contribution positive in 2017

New technology – Why?

• At acquisition, technology in branches and head office but not mobile

• All agent : customer interaction involved pen and paper

• Slow, error prone process.

• Transaction details manually entered onto system weekly

• Slowed down MI and analysis

• Wanted the agent to hold and collect data at source

• Much faster and far less error prone

• Ensures regulatory compliance

• Removes need for manual data-input. Near real-time system updates.

• Significantly speeds up MI for agents and managers

• Better experience for agents and customers

New technology – Phase 1 objectives

• Foundations – Build a new platform for the new technology

• Stage 1 – Collections app: All info needed for agent to collect and record outcomes

• Stage 2 – Lending app – Paperless loan origination process

• Stage 3 – Balancing: Removes the need for data input and labour intensive weekly

reconciliations

• Stage 4 – Provide managers with mobile devices to increase time spent with customer

New technology – Platform

• The new platform was vital for our technology journey.

• Partnered with boutique cloud data experts – DataShed

• After a careful selection process, chose Microsoft Azure:

• Secure – Take advantage of Microsoft’s heavy investment in security

• Flexible – Allows us to integrate all our existing and new technology

• Scalable – Started small and added components as developed. Don’t need to pay for

peak power until needed

• Robust – Cloud technology, multiple instances in multiple locations.

• Very pleased with performance and economics

New technology – Apps Demo

• We’d like to share more details with you about our apps

• They’re available for you to play with at the back of the room

• Short video showing apps in action……

• 6 weeks after rollout began, over 80% of all loans are processed through the lending app

New technology – Phase 1 objectives review

Stage 1 – Collections All info will be entered directly into systems by agents via mobile apps

Increased efficiency

Instant access to customer data

Reduce manual errors

Remove paper collecting lists

Stage 3 - Balancing Centralisation of remaining administrative

tasks into CRC

Removal of unnecessary balancing and reconciliation tasks undertaken by agents and

performance managers

Stage 2 - Lending Ability to lend via mobile device

Electronic agreements, request to call forms and affordability assessment forms

Greatly enhanced agent and customer experience

Processes built to ensure regulatory compliance

Stage 4 – Mobile MI iPads for all Managers

Full mobile access to all MI whilst outside of the office with agents or customers

Secure and Robust

Foundation Cloud based platform for secure, scalable hosting of technology.

All fully integrated with application process via web and Customer Relationship Centre (CRC)

New technology – Phase 2

• Phase 2 will be agent and customer-led

• Continue embedding and improving core apps, based on feedback from

• Agents

• customers

• Customer portal

• Gateway for customers to view account

• See balance and transactions

• Make a payment via card

• See what further lending options are available

• All to support, not replace, the agent/customer relationship

Outlook and Summary

• Strong progress already made:

• Significant expansion of network and business volumes – loan book up 40%

• Much improved quality – impairment falling

• Outlook for 2018:

• Full-year benefit from new agents hired in 2017

• Support payments will reduce significantly as agencies become established

• Investment in infrastructure provides excellent platform for further growth

• Will continue to drive efficiency through technology

• Will seek to maintain cultural advantage

Loans at Home is well-placed to deliver additional growth in 2018

116

Nick Teunon Chief Financial Officer


Funding

117

Refinanced our bank facilities in August 2017:

£175m of six-year funding

Additional £50m committed facility

Provided by Alcentra, Beachpoint and Cairn

All-in cost of 9%

Plus £35m RCF from RBS (LIBOR+3.5%)

Ample funding through to mid-2019

0

50

100

150

200

250

300£m


IFRS 9

118


Effective 1 January 2018 with no restatement of FY17 results

Moves from incurred loss to expected loss basis

Impact most pronounced in NSF Home credit division:

Seasonality drives substantial lending in November and December of each year with minimal incurred loss

IFRS 9 will move impairment from Q1 of any year to Q4 of previous year – minimal impact if loan book not

growing but NSF Home credit growing fast

No impact on lifetime profitability of any individual loan or cash flows from that loan

No impact on debt covenants

IFRS 9 – estimated impact on 2016 closing balance sheet

We have made good progress with IFRS 9 implementation and the methodology to be used. Based on this work we

estimate that reported receivables at the end of 2016 would have been approximately 3%-7% lower under IFRS 9.

As an illustration, the table below shows the impact of a 5% decrease in reported receivables together with the impact on

the group's reported net assets at the same date after taking account of the deferred tax impact of the receivables

adjustment.

29 NOVEMBER 2017 NON-STANDARD FINANCE – CAPITAL MARKETS DAY 119

£’m 2016 as reported 2016 with 5%

adjustment

Changes

Net loan book 165 156 -5%

Net assets 249 242 -3%

120

John van Kuffeler Founder and Group Chief Executive


121

Summary

NSF has already achieved most of its initial objectives:

Leading market positions in each of its chosen segments

Strong balance sheet supported by blue chip shareholders and lenders

A good regulatory track record

Financial performance:

annual loan book growth of 20%+

progressing towards 20% return on asset

paying dividends for shareholders with 50% payout as short-term target

strong growth in Q4 17

future growth plans underpinned by investment

We remain confident in the outlook


Non-Standard Finance plc Capital Markets Day Appendices

123

Blue-chip shareholder base


Long-term institutional holders

43% of employees are holders via SAYE scheme

Rank Fund Holding (m) % Cum %

1 Invesco 86.5 27.3 27.3

2 Woodford 83.9 26.5 53.8

3 Marathon 34.1 10.8 64.5

4 Aberforth Partners 26.2 8.3 72.8

5 Quilter Cheviot 12.5 3.9 76.7

6 West Yorkshire PF 8.4 2.6 79.3

7 J O Hambro 6.4 2.0 81.3

8 BofA Merrill Lynch 6.1 1.9 83.3

9 Toscafund 6.0 1.9 85.2

10 Carmignac Gestion 5.7 1.8 87.0

124

Credit Facilities


Total £260m comprising

£175m facility provided by:

Alcentra

Beachpoint

Cairn

Additional £50m committed facility (currently undrawn)

£35m Super Senior RCF

non-standard finance plc capital markets day/media/files/n/non-standard-financ… · 29/11/2017...

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