Improving operational efficiency and decision making through increased use of AI and machine learning

SmartStream’s Robin Hasson and Andy Burner, together with Standard Chartered’s Vikram Gupta discussed their thoughts on the increased demand and dependability on artificial intelligence and machine learning, as well as the opportunities and threats that come with its adoption. 

In this podcast titled Artificial Intelligence and Machine Learning, SmartStream has partnered with Asian Banking and Finance to talk about how Artificial Intelligence (AI) and Machine Learning (ML) is spearheading rapid change in data validation and reconciliations, as well as how these technologies deliver significant efficiencies into business processes, and how these translate to cost and risk benefits.

SmartStream Senior Product Manager - Reconciliations Robin Hasson and Chief Innovation Officer Andy Burner, together with Standard Chartered Bank’s Executive Director and Head of Technology - Data Science, Automation, Data Analytics & AI/ML Vikram Gupta shared their insights on how financial institutions are now taking big strides in improving their operational efficiency and decision making in times of increased demand and dependency on the use of AI and ML. 

Vikram observed that as new business models emerge in the banking scene at such a rapid pace, customer expectations are changing with it, in such a way that they are looking to have 24 by seven systems, personalised services, and all digital. These, he believes, are driving the digital transformation across the industry.

“We as a Bank are pushing the way we manage our reference data, sanctions, confirmations, settlements, balances and positions thereby, envisioning a pathway to increase sustainability and operational efficiency,” Vikram said.

Meanwhile, Hasson pointed out that if stakeholders want to understand where the efficiencies and opportunities lie, they have to consider today’s challenges in the industry, such as increased volumes, diversity of a wider range of data, which is also more complex.

“All of these challenges mean that the reconciliation tools themselves have had to evolve. And that's certainly where we've invested heavily as a firm into AI and machine learning technologies,” Hasson said.

To add to his point, Hasson mentioned SmartStream’s latest AI observation learning capability, “Affinity,” a tool that learns from user interactions, such as how to correlate and perform user interactions automatically and to mimic those users automatically at the same time. Hasson noted that the efficient simulation reduces the time taken to perform matching types.

Burner also highlighted SmartStream’s Innovation Lab, a facility in Vienna, Austria catered to improve financial services businesses. Amongst the projects they are working on is conducting pilots to fast track and prove high-value AI business cases. He described that as they define a good business case, they create a team where their customer provides the business know-how and the data scenarios.

“Our target really is to allow quicker processes, to better data enrichment, and to help the financial services industry to improve their processes,” Burner said.

He added that the Innovation Lab was launched as they see a big business problem in the industry, and SmartStream tries to fulfil that. Burner also believes that having a business problem is where AI starts and thrives. 

“AI is a solution to have better control for the financial services industry, to reduce the costs, and to really gain more efficiency,” he said.