How can today’s bankers prepare for tomorrow’s challenges?
Consider the financial models built using available data. Data collection and financial modelling used to be conducted in each different silos of the bank, with credit separate from market, which was separate from treasury and other groups).
Then data became “managed” and modelling was moved to “platforms” which did not mix well between the various silos. A few brave souls began to integrate the data management for different groups of the bank. Other brave souls tried to integrate the modelling. This was the phase of integration achieved through batch calculations.
“Real time integrated modelling and data systems offers benefits such as higher levels of efficiency and faster decision-making,” said Venkat Veeramani, Senior Vice-President and Head of Quantitative Analytics at Wintrust Financial Corporation. He was the first of two presenters at the February 25, 2016, webinar offered by the Global Association of Risk Professionals (GARP).
However, real-time integration comes at a cost—that of “heavy infrastructure investment,” often involving upgrades from legacy systems. The personnel involved must have “advanced analytical skillsets,” Veeramani cautioned.
“Is your modelling platform playing catch-up?” he asked. Financial Technology (FinTech) firms are changing, or disrupting, the interactions within and between financial institutions. The modelling platforms must be able to access lots of data from a wide variety of sources and come up with answers for complex, highly granular business questions in real time.
New regulatory requirements are exerting increased pressure. When it comes to handling big data, “many fear that financial institutions are lagging behind,” he said. He cited DFAST (Dodd-Frank Act Stress Tests) , CECL (Current Expected Credit Loss), and CFBP (Consumer Financial Protection Bureau).
Veeramani emphasized that adequately meeting the numerous business and new regulatory needs “hinges on the availability of reliable data.”
Ah, that is the crux: reliable data. The rule still holds: garbage in, garbage out. ª
Click here to view the webinar presentation “Modelling Platform for the ‘Future’ Analytical Banker.” Veeramani’s slides are 4 to 7 inclusive.
The modelling/data management picture is from Veeramani’s presentation and is used with permission.