Data Analytics

Data Analytics 2017-08-23T03:55:26+00:00
A2Q2’s data analysis provided powerful business insights into our transaction costs, one of the largest components of our cost of sales. We used it as leverage to negotiate with our many payment processors and to ensure that they were complying with the contract terms. Previously, analyzing the millions of transactions on our platform took months. A2Q2 did this in 1/3 the time, building a scalable process that could be leveraged across functions.
Carlton McMillan, Revenue Manager
uber

“At Uber, data drives everything.  And as an internal audit team, we need to be able to harness large quantities of data from multiple systems to gain insights that drive our work and value to the business.  We selected A2Q2 to work with us to identify trends and anomalies which accelerated the effectiveness of my team.”

Brandi Thomas, Head of Internal Audit

Data Analytics Team

Meet the Binary Bunch

… goofy data wizards who get kicks out of piecing together data elements from various systems to find business intelligence, trends, fraud and anomalies.

  • Need business intelligence?
  • Have massive data but no information to make business decisions?
  • Reconciling 20+ million sales transactions to see if you got all the money from payment processors?
  • Need help proving revenue, cash receipts and cash disbursements to regulators, vendors, customers or auditors?
  • Need to reconstruct your AR, AP or deferred revenue balances for millions of “in-transit” transactions?

Binary Bunch have found millions of “misplaced” transactions which drop directly to the bottom line. With our data analytics expertise, we have helped growing companies build scalable processes to manage data overload.

Data Analytics will help you in your decision making and create strategies for your business.

A client used our automated ACL reports to prove cash receipts, payment error and implemented controls to prevent fraud and errors. The company’s external auditors and Revenue Team relied on our data analytic reports to complete the company’s financial statement audits.

A fast-growing online services company uses its in-house payment tracking system to store and record credit card sales with multiple payment processors and banks.

As a result of the company’s rapid growth in recent years, the transaction volume had dramatically increased to over 10 million transactions. Manual reconciliations of the revenue and cost of revenue accounts using Excel had become time-consuming and impractical.

Using ACL (Audit Command Language), we reconciled transactional data from the internal databases with source data provided by multiple banks and payment processors (including PayPal, Envoy, Western Union, Chase, AMEX, and WorldPay). Our data analytic models factored in timing and foreign exchange differences between the various systems, and identify fraudulent payments and payment processing errors such as duplicate transactions and missing transactions from banks and payment processors.

With an audit deadline fast approaching, we quickly created an ACL script to assist our client in reconciling over 12 million credit card transactions. Operationally, we created a scalable, repeatable process that reduced the reconciliation time for one fiscal year from 36 weeks to one week

The online services company was manually reconciling credit card sales transactions between its internal sales system and data provided by external payment processors on a daily basis. Each month, this manual Excel process took up to three weeks to reconcile revenue and cash receipts.

The company’s quick growth boosted sales to 12 million transactions per quarter and Excel was not capable of the handling the transaction volume.

We assisted a retail client through an audit of its financial statements for multiple years. The client had home-grown, proprietary sales and inventory management systems which generated selected reports for management reporting and accounting purposes.

Over time, management noticed that large discrepancies existed between various reports using the same source data. To assist, we extracted large data files and analyzed them to identify the cause of the discrepancies.

Once we identified the potential root causes we proposed ways to remediate the situation. We created multiple trended analyses and reports for management as well as identified areas of revenue leakage.

We reduced the amount of work redundancy and mis-communication for the entire company by reconciling and consolidating the data sources for two departments — Financial Reporting Department and the Budgeting Department. A2Q2 worked with our client to streamline the annual budgeting and quarterly budget-to-actual analysis processes for 30+ departments.

The Budgeting Department used a quarterly data feed from Oracle into Hyperion Planning whereas the Financial Reporting Department maintained a separate database in Microsoft Access after running several SQL scripts of Oracle.

We worked with both departments to reconcile their data and reports to identify differences and the root causes of differences between the two databases (Hyperion Planning vs. Microsoft Access). A2Q2 gained a clear understanding of each department’s data structure, its uses, how it was maintained, and how it was populated. To reconcile the two databases, various custom templates were created in SmartView in addition to using pre-existing reports generated by both databases.

A2Q2 also assisted in mocking up reports to be created in Hyperion to fulfill the reporting needs of the Financial Reporting Department.

With over 500K lines of travel & entertainment (T&E) transactions manually entered (totaling $83 million), it was almost impossible for the Finance team to answer fundamental questions like:

  • What is the overall profile of the company’s T&E expenses?
  • How to efficiently and systematically control T&E expenses?
  • How to reduce T&E and FCPA risks?

Our client was growing exponentially and so were its T&E reimbursements. Using data analytics, we identified over $200k of duplicate payments, trends by department, trends by category and trends by vendor, missing receipts and split receipts. We pulled transaction data from Expensify, Bills.com and the GL to analyze.

With these insights, we proposed suggestions to refine the T&E policy and procedures.

Using the knowledge from our previous data analytics payment reconciliation models, our team was brought in to assist a client with the implementation of ReconArt, a third party automated reconciliation software solution. The ReconArt implementation involved the configuration of 50+ active bank accounts, 10+ payment processors, and 20+ unique data file structures in conjunction with 1million+ transactions per month.

This system implementation was a daunting task for the original two-person team. To keep pace with the fast growing company’s business needs, we joined the team to build and test the import and reconciliation logic, backfill historical data, and test automated feeds for both existing and new processors soon to be activated. Data integrity issues that were identified at this stage were communicated to the engineering team and external payment processors and resolved to improve the flow of data between all departments.

Using only external processor files, the team was able to successfully map the reconciling data, and configure the system to automate daily data imports and reconcile on a daily basis. Tasked with the bulk of building groundwork in our hands, the client’s team had the available bandwidth to focus on more crucial tasks, such as ERP integration, transactional exceptions, and data error handling. With more resources allocated to exception handling, data issues were caught and resolved in just a matter of days. Previously, the client would detect data issues, such as incomplete data and inconsistent data formats, months after they occurred.