Putting fintech in the lab
How and why SmartStream is taking a white coat approach to testing new applications for artificial intelligence, machine learning and blockchain
The number of fintech solutions on the market increases as the industry gains trust in them. But wider choice brings added confusion, with the danger that decision-makers in financial services begin to feel like harried tourists in a digital souk.
Rick Striano, MD of digital product development for global cash management at Deutsche Bank, sums it up: “We are presented with new solutions at every turn. Some are great and others completely outlandish, but they’ll both promise the same thing – fantastic results.” New technology can be fantastic when applied in the right context. But where it has usability and feasibility are questions that lie at the heart of procurement – and financial institutions themselves are not always best placed to answer them, especially when it comes to the emerging areas of artificial intelligence (AI), machine learning (ML) and blockchain.
Global software and managed services provider SmartStream examined the market to pinpoint challenges felt across the industry before making its move. “All fresh tools have the potential to breathe value into systems,” says Andreas Burner, the firm’s chief innovation officer. “But their development is a long road filled with mistrials. “Our research showed that the biggest struggle faced by solution providers today is with the quality of data. If companies had known all along that one day their fi les would be worth gold, they would have perhaps stored them differently. As it is, we often find data quality or formatting to be subpar. “Once we grasped the achievable potential of AI, blockchain, Cloud and data analytics, we decided against creating tools first and instead founded an innovation lab to create an environment where a real banking problem’s workflow could be meticulously examined by experts before our programming began.”
Composed of mathematicians, applied data scientists and exceptional computer scientists, SmartStream’s first lab in Vienna, Austria, was opened in late 2018 for the sole purpose of evaluating banking case studies to decode and, ultimately, deploy the best possible models in AI, ML and blockchain. The case studies being prodded and poked by the Vienna team are taken from SmartStream’s extensive client list of leading asset managers, custodians, broker dealers and banks.
Mark Roth, chief marketing offi cer, explains: “No two of our 13 projects are alike. Some serve the purpose of driving down costs, others boost match rate efficiencies or automate inter-systems reconciliations. One uses advanced data analytics to re-engineer the middle and back-office processes.”
SmartStream CEO Haytham Kaddoura believes this software development strategy, based on a mix of targeted research and intimate model-building, is its secret sauce. It’s also the reason the client banks who’ve undergone pilots with SmartStream are already reporting tremendous returns. “We have built ourselves a framework where we can observe the workflows of users and businesses and take the time needed to detect not only what’s physically accounted for but infer the rest from the gaps in data,” he says. “There is no better position from which to start.”
