Our organization has developed a novel solution to a ubiquitous industry pain point, but up to now this pain point has remained largely hidden, been identified only anecdotally and has never been formally analyzed, quantified and documented.... until of course you work on it!.

The aim of this project is to perform an industry survey to rectify this situation and to produce the first published survey and analysis on this subject.

The ubiquitous industry pain point relates to the following business process which is performed by every single organization in every single industry, but which is a particular pain point for financial institutions due to their high transaction volume.

The problem occurs during transaction reconciliation processes. The most prevalent and most widely known example of a transaction reconciliation is a cash reconciliation which is performed between business activity transactions such as expenses, invoices, trades etc and the associated cash movements.

To match these transactions, most organizations use either spreadsheet, or a purpose made 'rules based' matching engine. This approach works well when the data has high quality, but when corresponding transactions do not have exactly matching attributes, or some of the attributes are blank, or there are multiple transactions for similar amounts, this simple rules based approach does not deliver 100% matching or can sometimes mismatch transactions. In such situations an automated match rate may only be 80% which with 10's of millions of transactions a year can lead to millions of unmatched transactions which have to be matched manually by the organizations staff. This is tedious, time consuming work which not only costs time and effort, but also leads to delays in completing the transaction reconciliation.

This project is to analyze, quantify and document the scale and business impact of this problem in the financial services industry. Specifically some of the details which this market/industry research should address are

• Determine across industry estimates of the volume of manual matching and mismatches. (Stratified by type of financial institution)
• How many people in each organization are working on this function?
• How much time does a manual match typically take for an operation staff?
• Has this ever caused a delay in close?
• In the light of Covid-19, is there a directive to reduce dependency on labor for this kinds of functions?
• What is the accounting impact / operational risk of transaction mismatches?
• Estimate the cost of the manual effort across the industry and from this the total addressable market size.

We believe that there is enough industry data available which when combined with surveys/interviews will provide answers to these questions. We can provide appropriate industry contacts.

Using these findings, we would like a detailed research report that will be a valuable resource for our customer and will help us to position ourselves as thought-leaders for this particular problem (and more generally for the use of machine learning to help automate back-office repetitive business processes in such a way that guarantees a stellar return on investment for the customer.)

We believe this project will include but is not limited to:

1. Creating a survey and interviewing both owners and line workers who are focussed on the reconciliation function

2. Determining industry known volumes such as total payments moving through the Federal Reserve to provide an estimate for the magnitude of this issue.

3. Using the timing estimate gathered from interviewees/survey participants, determining the $ cost of this business problem.

You will work with the core Operartis team and meet weekly with the CEO as the project progresses and will be able to adapt, augment this general plan as the project progresses. The Operartis team is a compact, friendly team where you will have a welcoming place to express your creativity and problem solving skills.