Tick & Tie Finance Blog

5 Ways AI/Machine Learning Reduces Risk in Account Reconciliation5 Ways AI/Machine Learning Reduces Risk in Account Reconciliation
Managing risk is a core function of Finance and Accounting (F&A) teams. Nobody wants surprises, be it extra work, a poor audit, or a restatement. New technology like Artificial Intelligence, Machine Learning and Cloud Software - when used properly - can reduce many types of risks inherent in account reconciliation software selection and use.
"How do I Get My First CFO Job?” - The Three Paths to CFO"How do I Get My First CFO Job?” - The Three Paths to CFO
The journey to CFO can be long and not particularly clear to most people in F&A. Especially that final jump to CFO. While we tend to think that just by keeping our heads down and doing a great job will eventually get us to the rank of CFO, it's never that simple. You need to be thoughtful and strategic to map your way to C-Suite. This post outlines three common paths for achieving CFO status that should help with your planning.
A Risk-Adjusted Method Of Software SelectionA Risk-Adjusted Method Of Software Selection
Software selection for the enterprise is a complicated process that needs a structure in order to be successful. Most standard frameworks deal with the features, pricing and fit but fail to include different risks of implementation and success. This post describes how to add risk to the framework so that your decision is de-risked.
White Paper - CFO's Introduction to AI - Machine Learning - Updated!White Paper - CFO's Introduction to AI - Machine Learning - Updated!
Artificial Intelligence (AI) and Machine Learning (ML) are terms we hear a lot in tech and industry press and can be thrown around without context or background. The PR hype accompanying AI/ML should appropriately trigger skepticism among CFOs in terms of business value the technology can generate. Where is the line between hype and reality? To start asking the right questions, it is helpful to understand some key concepts. * This white paper has been updated with new examples and clarity on how machine learning models learn and get updated.
Reducing Credit Card Reconciliation Time While Increasing Match Accuracy Through Intelligent AutomationReducing Credit Card Reconciliation Time While Increasing Match Accuracy Through Intelligent Automation
Credit/Debit cards now account for over 75% of consumer transactions but traditional methods of reconciling the steps in the process haven’t evolved nearly as fast - until now. Traditional tools like Excel driven matching or rules based reconciliation can help in lower volume, simple matching but credit card reconciliation - with it’s raw volume and many different systems in the processing flow - creates unique reconciliation problems that need a new approach. This article describes the process and opportunities for efficiency improvement through intelligent automation.

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