Technology is also streamlining existing business and audit processes alike. For example, asset verification has been a critical, labor-intensive audit step. Today, Deloitte auditors are using a proprietary application called Icount on their tablets and smartphones to scan and consolidate inventory count results automatically for real-time consolidation and analysis in an online portal. While conducting the count, the auditor can use a voice-to-text capability to create documentation, take pictures of the observed inventory, and generate the audit working papers automatically. Another benefit of innovation for private companies involves performing competitor analysis and identification of leading practices.
Audit transformation has become the topic of the day for audit firms, but the reality is we've been working with our clients to improve the audit for more than a decade. We've already invested in automation to make the process faster, higher quality and to give greater insight. But where are we going next? In our'Confidence in the future' series, we'll be releasing a number of insights covering how we believe audit needs to evolve, each looking at how we can deliver high-quality assurance to tackle some of the perceived challenges around the audit.
I know you guys are just dying to know the answer to this question, so let's get right to it. Audit Analytics recently came out with its breakdown of the top 20 audit firms that had the most insurance clients in 2018. Yes, the Big 4 firms took the top four spots, combining for 2,300 of the 3,946 insurance companies analyzed by Audit Analytics. But there are some firms in the top 10 that may surprise you. First, the most prestigious firm in all the land, PwC, audited the most insurance companies, with 692--nine more than in 2017.
Mathematician Cathy O'Neil is offering businesses a chance to test their algorithms for fairness. Opening the black box: As artificial-intelligence systems get more advanced, the logic paths they follow can be difficult or even impossible to understand, creating a so-called "black box." As these algorithms come to control increasingly important parts of our lives, like whether we get a job or a loan, it is crucial to understand their biases and decisions. The solution: O'Neil, who wrote the book Weapons of Math Destruction, has started O'Neil Risk Consulting and Algorithmic Auditing to perform third-party audits on algorithms. It examines everything from the people who programmed the software to the training data to the output, flagging any bias in the process.
The advent of audit analytics and cognitive technology does not mean the end of human auditors. It means an end to painstaking checking and crossfooting of debit and credit entries and the beginning of auditing careers that thrive on understanding, monitoring, and improving analytical and cognitive systems. I have worked for a couple decades with professional services firms that perform financial audits, but I have never done one--nor have I ever wanted to do one, to be honest. I'm not good with work that involves structured processes, details, and rigorous checking, and audits always seemed heavily infused with those kinds of tasks. Now, however, I am becoming quite interested in audits for two reasons.