Artificial Intelligence Explained for the Client Accounting Services Firm

First off, if you are a CAS Firm, have a look at this blog post, Artificial Intelligence Explained for the Small Business Owner.

A Client Accounting Services (CAS) or Client Accounting and Advisory Services (CAAS) firm is an accounting practice or bookkeeping service that provides outsourced bookkeeping, accounting, virtual CFO services, virtual FP&A services (forward looking), financial statement compilation, financial statement review, and/or I will add financial statement audit or assertion services to their clients.  The types of core services offered include things like:

  • Daily Bookkeeping: managing accounts payable, accounts receivable, and bank reconciliations
  • Payroll & Compliance: processing employee pay, filing payroll taxes, and handling 1099s, maybe some lite human resources tasks related to payroll
  • Financial reporting: generating monthly balance sheets, income statements, and cash flow statements used to run a business
  • Virtual CFO/Controller: providing high-level budgeting, key performance indicator (KPI) tracking, and strategic business advice; this typically includes financial performance and analysis (FP&A) services

CAS and CAAS differs from traditional accounting firms in the following ways:

  • Timing: Traditional accounting firms look at financial information of a business once a year when the business' tax return is prepared. CAS and CAAS firms are more involved on a daily, weekly, and/or monthly basis.
  • Relationship: Traditional accounting work is seasonal and transactional; CAS/CAAS is an ongoing, year-round collaboration.
  • Pricing: CAS/CAAS firms usually charge fixed, predictable monthly subscription fees rather than hourly or one-time project rates.
  • Location: CAS/CAAS firms might be offshore whereas traditional accounting firms tended to be located in the same city as the business they are serving.
  • Collaborative: Traditional accounting work done using separate software from clients typically.  With CAS/CAAS the trend will be that work will typically be done more collaboratively with the client, the CAS/CAAS firm, and even artificial intelligence agents all working together collaboratively within the same software application.

Most software vendors providing “automation” software for CAS or CAAS firms are providing project management software relating to the management of a CAS/CAAS project or a number of different CAS/CAAS projects at the same time (e.g. managing several clients).  This "automation" does not really involve automation of the actual work (e.g. the work system itself) related to, say, creating the actual financial statement.  For example, imagine a virtual CFO where a bookkeeper can quickly ask a question related to how to post a journal entry.

A month-end close process is not a single task; it is maybe 15 to 50 separate tasks that are connected together in workflows, processes, and projects. Think of these tasks as "steps" or algorithms really. Each of the steps or algorithms take different skill/experience levels and some might be automatable and others need to be performed manually because they require judgement, approval, or some sort of signoff.  And for a CAS/CAAS firm, the 15 to 50 takes will be running simultaneously across your 100 to maybe 500 different clients.

For many (most) CAS/CAAS firms; this work is performed by emailing documents like electronic spreadsheets; tasks include copying a spreadsheet from last month and saving  it as a proforma for the current period, handoffs sent over email or maybe something like Slack when someone remembers, status tracked by sending an instant message or email or maybe even walking over and asking.

These systems work, but if you look honestly; the system is basically a kludge that gets the job done but it was not engineered; it just sort of evolved solving immediate problems as they appeared.  Saying this another way, these are not industrial processes engineered for productivity.

But there is another huge problem which is exposed because of artificial intelligence.  Your clients systems, processes, and data are not really digital and designed to maximize the possibilities offered by artificial intelligence.

Leveraging artificial intelligence to manage tasks, perform work tasks, information handoffs, transaction chasing, status checking, document chasing, and other such project management tasks is relatively straight forward.

What is harder is rethinking and improving the current "bucket brigade" of information flow. Having to resort to "the plug" in performing work (e.g. not understanding what caused the discrepancy).  Managing the risk of noncompliance. Not being able to leverage artificial intelligence effectively because of the problem of semantic fragmentation.

How many reconciliations, journal entries, variance analysis, movement analysis, and other such accounting and report creation tasks and processes are being effectively automated? What sort of providence tracking capabilities do you have? Do you have traceability/trackability to easily examine any information at any point in the process and be able to understand the origin of the information?  What sort of capability do you have to query across the set of, what maybe 100 or more electronic spreadsheets and what do those electronic spreadsheets do to your provenance, traceability, and trackability?

There are different classes of collaborative work systems.  Enterprise level closing platforms or closing books are created for large corporate reporting teams doing multiple entity consolidations with Sarbanes Oxley compliance using US GAAP or IFRS.  That type of enterprise grade system is completely wrong for a small or medium sized business, or for a not-for-profit, or a state or local government type entity.

Tools built for CAS/CAAS firms which have many client engagements to manage is one work flow.  Managing 50 or 500 separate client engagements (e.g. the project management), doing a simple month end close without consolidation, without multiple currencies, and with out the other sorts of complexities, and those complex closing platforms required for a multinational enterprise are all completely different types of systems.  Different specialized industries can, and should, have different specialized systems.

Saying this another way; think of all this in terms of platforms and ecosystems.  Think of the systems as truly collaborative work systems which enable humans and machines to effectively collaborate.  Think of these systems if they were digital graph first model based systems. Think of a system where the gaps where consciously eliminated. Think of this in terms of a refactored office of the CFO. Think of this in terms of leveraging the deterministic nature of accounting. Think of this in terms of leveraging the mathematical nature of accounting.

What if you applied this same thinking to the audit and the audit bundle?


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