The SME Z-Score: a new powerful tool to assess the riskiness of SMEs

London, March 29, 2017

Our Company

We develop unique, powerful credit risk models for SMEs and make our risk assessment available to companies, lenders and investors on a subscription basis.

Unique and powerful risk models

World leading experts

100% focused on SMEs

Our Team

Dr. Edward Altman Dr. Gabriele Sabato Dr. Nick Wilson

• Dr. Altman was named to the Max L. Heine endowed professorship at Stern in 1988.

• He chaired the Stern School's MBA Program for 12 years.

• He is the Director of Research in Credit and Debt Markets at the NYU Salomon Center for the Study of Financial Institutions.

• His article in 1968 on the Z-Score model opened the way to the current rating methodologies.

• Dr. Sabato has worked in the Risk Management department of several international banks for more than 15 years.

• He has authored several academic papers on how to model credit risk for SMEs.

• He has a proven track record on helping SMEs to select the best source of funding.

• He is the CEO and co-founder of Wiserfunding Ltd.

• Dr. Wilson helds the Chair in Credit Risk and Finance at Leeds University Business School since 1998 and is Director of the Credit Management Research Centre (CMRC).

• He has recently led the development of the Leeds Institute of Data Analytics, a cross faculty initiative on ‘Big data’.

• In September 2001 Professor Wilson set up CreditScorer Ltd, a Leeds University spin-out company.

Our Solution

Bond Rating Equivalent Debt capacity PD and LGD Commercial credit limit Peer comparison Funding options Pricing range

Get better pricing for their funding

Select the most appropriate source of funding

SMEs

Select the best companies to lend to/ invest in

Optimise risk/return strategy

Lenders/investors

SME Z-Score

SME Z-Score Model: Italy

More than 14.000 Italian SMEs with financial data covering from 2004 to 2014.

Unique mix of financial and non-financial information.

Type I error

rate Type II error

rate 1- Average Error Rate

Accuracy ratio

Manufacturing Model 6.92% (8.23%)

26.57% (27.64%)

83.26% (82.07%)

93.08% (92.21%)

Retail Model 16.77% (18.54%)

27.78% (28.89%)

77.73% (76.29%)

83.23% (81.76%)

Services Model 12.05% (14.88%)

24.54% (26.43%)

81.70% (79.35%)

87.94% (84.12%)

Constructions and Real Estate

8.89% (10.12%)

26.02% (28.24%)

82.55% (80.82%)

91.11% (89.86%)

SME Z-Score Model: Italy

Our SME Z-Score is a Point-in-Time (PiT) assessment of a company’s creditworthiness providing a more responsive short term view than a Rating

The Italian Stock Exchange has chosen Wiserfunding to provide a risk assessment for all SMEs issuing mini-bonds.

Source: Firms listed on Italian Stock Exchange Extra MOT, calculations by the authors

Bond Rating Equivalent # SMEs % SMEs Avg. Coupon YieldAA 2 2% 0,057A 4 4% 0,062

BBB 24 25% 0,065BB 18 19% 0,055B 31 32% 0,059

CCC 14 14% 0,065CC 2 2% 0,030C 2 2% 0,060

Date Moody's Fitch Wiserfunding

28/11/2014 B2 B- CC

10/12/2015 Caa3 CC C

15/05/2016

19/05/2016 Caa3 C C

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WASTE Italia S.p.a. - €200m, 5 years, 10.5%

SME Z-Score Model: UK

The models have been developed on a sample including more than 14m of SMEs that filed abridged accounts and more than 3m of SMEs that filed full accounts from 1998 to 2015, covering more than 2 economic cycles.

We have developed a total of 9 models: one generic for SMEs filing abriged accounts and 8 sector specific models (i.e. Agriculture and mining, manifacturing, energy/recycle and waste, contruction, retail, leisure, real estate and business services).

Every model comprises an impressive and unique set of variables including financial information, qualitative information (e.g. Board size, age of the company, CCJ, delay in filing accounts, etc.) and macroeconomic variables (e.g. Industry risk, GDP growth, Competition index, etc.).

The performance of all models is impressive varying between 77% and 85% accuracy ratio on test samples.

Competition

BROKER

CREDITSCORE

RATING

PRODUCTOPTIONS

Wiserfunding LtdGrand Union House20, Kentish Town RoadNW1 9NX London

www.wiserfunding.com