Automation in accounting, finance and auditing

The automation of accounting, finance and auditing is transforming how organizations manage data, monitor risk and deliver timely insights. As companies grapple with more transactions — and the regulatory complexity and desire for faster reporting that comes along with them — automating out repetitive tasks as well as applying intelligent checks against them are no longer nice-to-have features; these are now becoming table stakes. In this piece we outline the key steps towards achieving automation, why and when it is necessary, its dangers as well common sense advice on being successful longer-term with minimising workload.

Start by identifying and ordering the processes.

Understand current business process flows for accounting & finance from transaction capture through to reconciliations, journal entries/AP/AR/fixed asset management processes, close & reporting processes and audit sampling. Seek out repetitive, rule-bound work that takes too long — and has an error factor guard. Number, complexity and likely effect on cycle times and effectiveness reduced. 2. The `quick wins' in this area might include automated data import, despatch note and purchase order matching invoices with part numbers, recurring journals and standard reconciliations.

Design for Data Quality and Integrity.

Automation magnifies efficiencies and mistakes when data or rules are flawed. Apply validation rules, normalize COA mappings and data specifics upstream on source data where possible. Embed audit trails that reveal who does what, when for all automated action to provide evidence of transparency. Leave the minions at checkpoints to do the judgement stuff, automation is for us as users only a helper but not without manpower an expert evaluator in situations where professional skepticism applies.

Staying ahead as more than a bean-counter with emphasis on finance automation.

Centralize all budget, forecast and cash management into a consolidated workflow of automated data collection and scenario generation. Fast close and analysts with time to do driver based analysis can be driven by automating consolidation and eliminating through financial automation. Utilize the workflow automation to direct approvals, notify exceptions and escalate delinquencies. The result is faster decision cycles and more reliable financial visibility for executives.

Audit and regulatory compliance would obviously be major beneficiaries.

Automatic audit sampling, continuous monitoring of transactions and exception reporting provides auditors with opportunity to provide their test work on a much greater confidence basis and more time to consider the real issues. Automated controls checks in pipelines: SoD (segregation of duties) validations, limit based approvals and real time anomaly detection. Continual auditing reduces the need for over-reliance on historical testing, and unearth problems nearer to ‘Day 1’.

Measure benefits with clear KPIs.

Take days to close, hours spent in reconciliation time, count of manual adjustments required, error rates, cost per transaction from the processing and percent of exceptions that are routed through your organization that didn’t go through some automated process. By monitoring these KPIs before and after deployment, it’s easier to determine ROI and what still needs to be optimized. Remember also that there are qualitative victories, too: staff will be happier using the system, it should be easier to audit and there should be a greater confidence in the numbers.

Manage change and people impact.

It shifts staff from data entry to analysis, interpretation and advice. Adopt vision and values. WHY?Retrain employees and writers (fundamental workforce downshift to go from braces, bridges to implants)._RESET THE BAR: Write new job descriptions with greater value added. Engage finance, accounting and audit teams early — the individuals who do this work often can suggest the best automation rules and exception criteria. A staged roll-out among pilot teams lets rules be adjusted and trust established.

Control and governance are essential.

Establish common governing body to manage automation standards, change requests and waivers. If it is code that can be written, what rules around logic and updating as well as custom change management when required would need to happen including versioning of automation scripts or approvals for changes. Acculturate internal audit alongside governance that it will keep pace with compliance. Don't forget to review any automated rules as business is expanded.

Security is obviously very important.

Spend a few clicks so next time when you sending automated flows, you’re not breaking any privacy law and in-house policy. Use the principle of least privilege when granting access to systems, encrypt sensitive data in transit and at rest, and monitor logs for unauthorized activity. Automation can provide powerful control — provided it is build with good sign-on (SSO) and access controls in mind, not otherwise for then people’s questionable use of credentials or permissions will belek.

Avoid common pitfalls.

Over-automation too early moves grime quicker to the layer of automation; stabilize and standardize the process before adding automation. In circumstances when rules are not sufficient, such as dynamic and complex situations — exception handling and human-in-the-loop for review. Trust is lost through lack of documentation and monitoring; document why you’re building what you’re building, what it’s based on, build dashboards that show well, but track poorly: performance against errors.

Practical implementation steps:

So take a look at what you do and measure it to see if there’s any opportunity for automation.

Normalize input data as well as mapping.

Build modular automation pieces for data ingest, validation, matching and journaling.

Good logs and audit trails on all of your automated steps.

Conduct a small-scale pilot to test and obtain performance data.

Grow slowly, iterating governance and training materials as you go.

In future, improved machine learning for anomaly detection, natural language processing (NLP) to extract information from unstructured documents and continuous auditing platforms that interface with transaction systems are among the promising developments within CCM. These capabilities will push the realm of automation further into richer analytical tasks, yet at that stage tighter governance and explainability of automated decisions is needed.

Process automation in accounting and finance, if conducted in accordance with good process improvement principles, can lead to substantial efficiency benefits by either removing some of the manual effort involved or tightening up controls In summary Start with focus on priorities, priority-driven, ensuring data quality, control and auditability built in and a role for measuring outcomes as well as managing change around people. “How you apply automation strategically on top of transactional accounting and finance arms, is the moving to strategic partners who can get insights faster and have more reliable controls as financial stewards.