Fraud Analysis

A Small But Highly Transactional Client

What was the pain point?

Fraud testing had traditionally relied on manual analysis and sampling techniques. With analysis performed in Excel the team found it challenging to filter and review transactions, causing them to use multiple worksheets on incomplete listings. Therefore, effective fraud testing and insight was lacking for a client who had a particularly large dataset of transactions.

The nature of the organisation, being highly transactional and with finance involving multiple users, meant there was an increased risk that the business could be exposed to internal fraud. To effectively test and identify potential fraud, the engagement team wanted to more easily and more visually analyse an entire transactional population. The team knew this was also a risk the client was concerned about, as the finance team were exploring how fraud risk could be managed more effectively.

How did lnflo help?

lnflo was used to make fraud work more manageable for the accounting firm, whilst the client team were curious as to what the analytics could provide. lnflo was able to subject all of the transactions to a suite of characteristic-based data analytical techniques within minutes to identify transactions which posed the greatest risk of fraud or error. The engagement team were empowered using the intuitive visualisation and drill down capabilities to immediately identify trends and anomalies to perform more focussed investigation and testing of high risk transactions.

What was the result?

The team found that discussing the outputs with key client staff and presenting these powerful insights in client facing reports, they had improved their credibility as it helped the client management team to evaluate the effectiveness of their finance function and identify areas to focus attention. In fact, the client was so impressed with the new approach and insights presented that they asked the team to provide this valuable analysis on a quarterly basis in future.

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