The pace with which data is manufactured each year continues to vex the financial services industry as growing volumes become trickier to manage. Increased regulation only adds more pressure on financial institutions to find meaningful ways of presenting it.
There is ever growing need among banks create processes, train staff to reduce complexity and simplify tasks to present clear, concise and up-to-the-minute findings.
Like an accordion that ebbs and flows to create musical notes, so too do business users need to isolate certain metrics for certain queries or to show department heads, then expand them for reporting to regulators or up the chain of internal management.
Atoti is a fintech solution that is particularly expert at solving complex use cases native to the financial industry.
Atoti for FinReg
Banks have been struggling for years with how to meet regulatory requirements quickly and easily, while continuing to maintain BAU and churn a profit. Time, naturally, is of the essence. Here we demonstrate several use cases specific to financial regulations solved by Atoti and with links to how to create the notebooks we used to do that.
- Climate Risk
Atoti is perfect to begin the arduous process of testing portfolios and assets against climate risks. UK and EU regulators are already mandating the banks they look after to perform stress tests to gauge various climate risk impacts. In fact, Green RWA, an organization that developed a model to do just this used atoti to do so. Read more about it here: A New Paradigm: Identifying and Managing Climate Risk in Loan Portfolios.
- VaR and Stressed VaR
Value at Risk or VaR involves testing potentially millions of datapoints at a time, especially if you are looking at historical data. Calculating VaR on trading books or any number of positions is a daily banking task and one method to gird against excessive losses. Banks back test their portfolios on their own but regulators also require them to test them against stressed periods to see how they hold up.
Regulators have increasingly used stress tests over the last several years as a means to gauge a bank’s ability to hold its solvency in the face of adverse conditions. Liquidity and, currently, climate risk are two areas where banks had to report findings to regulators on this. Because it can handle so much data, Atoti makes it easy to crunch numbers of all sizes and create results on a dashboard. It saves our clients time.
- PnL Explain
The ability to explain your profit and loss to superiors, not to mention calculate it accurately to meet global regulations isn’t always as straightforward and easy a task as it could be.
Atoti can consume data from almost anywhere (CSV files and pandas and spark datastores) and through a “cube” which is automatically created, users can examine terabytes of data across dimensions, pinpoint any irregularities and explain how they derived PnL.
- IFRS 9
Monitoring credit risk and gauging potential loan defaults is an exercise that requires a tool that can handle all of the data in any given loan book plus the ability to slice and dice that data based on trends and patterns in the loans.
Creating a “vintage matrix” for the entire loan portfolio is easy with a few lines of code. Once the data is loaded, you can parse a loan portfolio or set of loans by credit quality, due date or any other metric you like and see the results on the Atoti dashboard.
