A Digital Reality Check Of The Finance Function
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A Digital Reality Check Of The Finance Function

Two weeks ago, I attended a Digital Finance Day at PwC in Copenhagen. My intention was to do a digital reality check of the finance function. I wanted to see how far we’d come in terms of AI and RPA. These two technologies are two of the most touted ones when it comes to the digital finance transformation. On one hand the day was an enormous success and on the other quite a disappointment. Now how can that be?

Firstly, thank you to PwC for an excellent event. All the right topics, interesting companies, and many insightful cases. Job well done and a success in my book! On the flipside I was disappointed with how far we’ve come. One thing is to imagine the potential possibilities of how digital can transform the finance function and another is to see what’s really happening. Let’s dig deeper into that. 

Imagination vs. reality 

Now I had a lot of great ideas of what could be done in Finance with AI and automation. Those can still be a reality of course but here’s how the reality check looks like. 

AI in Finance 

There are two ways I was thinking about using AI in Finance. 1) is for automated forecasting. I’ve seen that in use in at least two companies. I was hoping to hear more about that. 2) chatbots for self-service insights into business and financial developments. I had heard about chatbots being commissioned in Finance so I wanted to see what they could do. I only got to participate in one session about chatbots in Finance and here’s what I saw.

They had invited one of the leading authorities in the field from Copenhagen University who had also started multiple companies and even sold some off too. I was disappointed with what I saw though. Firstly, he showed examples of a chatbot in customer service. Secondly, all the interactions the robot had with the customers were pre-scripted by humans. Finally, these were all simple interactions with little insights shared with the customers.

I had imagined that you could deploy a chatbot in Finance and ask it about certain variances observed in your management report. You would ask “what happened”, “where did it happen”, “why did it happen”, and “what should we do about it”. So, I asked this question in the session and the answer was “go to PwC and in 2-3 months they’ll come back with an answer”. It’s possible that my question simply wasn’t understood because we’re too far off from reality. Still, I had expected more. 

RPA 2.0 in Finance 

RPA at its core is like Excel macros. They’ll do the job that you program them to do and nothing else. Still, if you combine various kind of macros or similar technologies you can start to automate end-to-end processes. This is what I was looking for when I joined the session RPA 2.0.

We were shown a case from Danske Bank. They wanted to automate the handling of closure documents for real estate deals. The input would come in relatively standardized formats yet each real estate agent would typically put their own unique touch to it. In addition, the documents would include free text clauses about the individual deals and, of course, also handwritten signatures and dates for when buyer and seller had signed the deal. The documents would be sent to the bank in a scanned pdf version. Does it sound like a complex task to automate?

At face value it might seem simple but it is quite complicated. You can see from the picture all the different solutions that were employed to extract all the information needed. Even when all information was extracted a human would still need to read through all the clauses in the document to understand the conditions of the deal.

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Let’s just say that while we can do a lot with automation there are no plug and play solutions as we soon as we start to increase the degree of complexity. This solution took Danske Bank 1.5 years and a lot of concerted efforts to develop. We might say RPA 2.0 but there’s certainly room for a 3.0 and 4.0 in the future. 

Therefore, we need to do reality checks 

I spoke to other people at the event who had been in other sessions and they confirmed the same picture I was seeing. They thought we had come further. Therefore, we must do reality checks of our perception of reality. It’s so easy to read a 30-page consultant report about tech in Finance and think that you’re running far behind. In the real world you’re likely not too much behind and still have time to catch up.

Where are you on the digital finance journey? What solutions have you implemented and how are they working for you? Do you seek inspiration from what other companies are doing are trying to do it all from scratch? Let’s compare notes on the status of digital finance transformation and discuss what we can do to progress it further.

This is the final article about Digital Finance this time around and you can read previous articles about RPA and AI below.

How To Make Robots A Part Of The Finance Family?

Why You Should Only Robotize Standard Processes 

Robots and Humans. A Marriage Made In Heaven Or Hell?

A Tale Of Robots: From Assembly Lines To Knowledge Workers

Robots Must Solve Business Pains To Be Successful

What AI Competencies Do Your Finance Team Really Need?

Here's How To Test If Your AI Solution Will Be A Success

You're The User Of AI. Yes You, So Take Charge!

You can read previous articles about robotics and other stories about finance transformation below.

Blip. Blop. Accounting Robot. Are You Ready?

Are You Ready For Robotics Process Automation?

Have You Met Your Robot Accountant Yet?

Robots Are The Future Of Analytics

Your Robot Accountant Has A Name, It's Dixie

What Defines A Finance Master?

The CFOs Roadmap To Transforming Finance

How Finance People Can Be More Successful

The New Career Path For Finance Professionals

I also encourage you to take a tour of my past articles on finance transformation, finance business partnering and not least “Introducing The Finance Transformation Nine Box” which is really the starting point for the transformation. You should join our Finance Business Partner Forum which is part of the Business Partnering Institute's online community where we will continue to discuss this topic and you can click here to follow me on Twitter.

Anders Liu-Lindberg is a Senior Finance Business Partner at Maersk supporting our largest product and I have more than 10 years of experience working with Finance at Maersk both in Denmark and abroad. I am also the co-founder of the Business Partnering Institute and owner of the largest group dedicated to Finance Business Partnering on LinkedIn with more than 7,000 members. My main goal at Maersk is to show how to be successful with business partnering and drive value creation as a trusted partner. I am the co-author of the book “Create Value as a Finance Business Partner” and a long-time Finance Blogger with 30.000+ followers.

Drew Strzepek

Finance Executive | Treasurer | Board Member | Woodworker | Set builder | Husband & Father

5y

Anders, thank you for the insights.  I think too often people fall into the trap of thinking that technology is the solution.  We need to constantly remind ourselves that technology is an enabler.  We need to focus on our future state streamlined processes and vision that allows us to move towards Business Partnering.

Frank Steinle

Project Manager, Product Owner, Business Analyst

5y

I could not help noticing one of the key learnings was "Managing Expectations". I think this to be a good recipe for any project! Though sometimes it is hard to bring expectations closer to reality, especially when product vendors (or your own sales team) made the customer believe in magic.

Andy Burrows

I train and coach Finance professionals, helping them to grow into business leaders and CFOs with successful, satisfying careers | Former Finance Director | LinkedIn Top Voice

5y

Thanks for the honest report. All the hype around makes it feel, as you say, like most of us are running far behind. The reality is that those considering RPA and going through the implementation difficulties are actually pioneering. And the AI we want is still in the realms of sci fi and Knight Rider!

Having the chatbot do scenario comparison, variance analysis or even variance analysis taking into account the development of drivers (other accounts or indicators) is easily achievable. The big problem is when we start posing open-ended questions like "Why did it happen" and expect to receive more than deep analysis of the data that is contained in the report itself. Replying to "What happened?" is pretty easy for the bot since the bot can show you the development, show the biggest transactions at the account, etc.

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