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‘How to use data mining to reduce risk, error, complexity and cost in Accounts Payable’ | 01

White paper How to use data mining to reduce

risk, error, complexity and cost in Accounts Payable

This white paper explains the most commonly observed anomalies and risks in Accounts Payable (AP), deduced from historical AP data. It highlights the value of AP data from multiple perspectives.

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This white paper explains how data mining can be used to identify ano­

malies and risks in Accounts Payable (AP). Topics are illustrated with the results

of a benchmark study of AP data delivered by 250 companies worldwide,

representing a consolidated spend amount exceeding 1150 billion euro.

How to use data mining to reduce risk, error, complexity and

cost in Accounts Payable

IntroductionIn today’s volatile business environment, Fi- nance strives to have an agile and responsive finance function in order to support the business in making the smartest and fastest decisions. Recent research by Open University Amsterdami shows that agile organizations:

• exercise control over a limited number of KPIs;• implement rolling forecasting;• use trend information and relative performance

indicators;• value knowledge sharing, learning and

collaboration within the finance organization. From this perspective, finance professionals want to review and improve their performance based on findings and trends that are distilled from hard, objective data. According to research by the Aberdeen Group (2009)ii , current challenges that CFOs are facing in improving financial performance are: reducing costs (73%), optimizing working capital (70%), forecasting financial performance (53%), and reducing anomalies (43%).

Financials therefore have an inherent interest in management information in the following areas:

• Historical and current AP process analysis• Payment terms; DPO• Exposure to fraud• Extent of contamination of the vendor master file • Supplier behaviour and risks associated with

the supply base

The ERP systems of organizations contain huge amounts of detailed information that has no special meaning in its bulk state, but that holds trends and important facts – in the above-mentioned areas – that can be discovered using data-mining techniques.

Based on hard, objective data this white paper explains the most common anomalies and risks in AP. The study is illustrated with results from a benchmark study of 250 randomly selected companies with a total of more than 1150 billion euro in financial data in various industries and countries worldwide.

Some of the applied data-mining techniques are straightforward, while others are more complex. In this white paper we do not elaborate on the specifics of the techniques, but instead focus on showing what value they can deliver. In the near future we will issue a series of white papers that will cover more in-depth information.

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Overview of this white paperSupplier behaviour and risks associated with the supply base

• Suppliers with high numbers of small invoices (below €200)• Suppliers with the same (i.e., duplicate) bank account number• Inactive suppliers• Payment term analysis• Spend analysis• Risk associated with the supply base

Accounts Payable process issues

• Payment errors• Credit issues• Fraud

For more information about this white paper, our services and/or other inquiries, please contact us:

0031 (0) 20 468 4648 | E sales@transparent.eu | W www.transparent.eu

About the authorFounded in 2000, Transparent is an international financial-services provider specializing in data mining of Accounts Payable (AP). The company has rapidly grown into a global organization, with offices in the Netherlands, Germany, Belgium, India, France, the United Kingdom, Italy and the United States.

Our services include the analysis of outgoing payments and associated processes with the aim to convert AP data into detailed management information. Alongside the analysis, we identify, verify and collect undue payments on a no-recovery, no-fee basis. The results are presented in an easy-to-read dashboard (SaaS) and used by Transparent to provide clients with management information and advice regarding their AP processes.

CFOs of blue-chip and medium-sized companies around the globe rely on Transparent to provide them with enterprise-level transparency of their AP processes and with sensible improvement recommendations. Moreover, many of our clients have seen an immediate profit increase after using our contingency-based recovery services. The analysis is solid, fast, risk-free, and doesn’t consume our clients’ resources, due to our excellent use of technology and fully industrialized process.