Of late, more Russian banks are increasingly using artificial intelligence, as the technology’s exceptional growth seems ready to enhance their competitiveness.
However, infrastructure problems and a scarcity of individuals with the ideal expertise are hindering AI’s broader applications.
“AI is undergoing a period of unprecedented evolution. Over the next few years, the technology will progress so far that AI will be employed in financial institutions just as often as humans,” said Sergey Putyatinsky, deputy chairman of Credit Bank of Moscow (CBoM).
“Active use of AI technology will be a decisive factor in banks’ competition in mass segments.”
A recent study conducted by the local rating agency Expert RA, in conjunction with the Centre for Financial Technologies, revealed that banking institutions in Russia often leverage artificial intelligence in credit analysis.
The study also revealed other areas that have experienced increased AI adoption, including marketing and debt collection.
Furthermore, the Expert RA study also found out that Russian banking institutions regularly set their hopes on artificial intelligence in areas such as credit scoring, debt collection, and uncovering fraudulent transactions, while automating call centers by using chatbots.
However, leveraging artificial intelligence in remote customer identification, human resource management, and algorithmic trading is seen to be less promising.
Nonetheless, the authors of the study said the latter areas might not be disregarded by lenders as inappropriate for AI adoption, even though generating returns on investment from the application of the technology in such areas is challenging.
Russian banks mostly prefer adopting technology in small phases.
“We are pragmatic about the adoption of ‘hyped’ technologies,” said Putyatinsky. “We normally start with smaller-scale pilot projects that allow us to evaluate the potential usefulness of the technology and build up in-house competencies.
“Wherever possible, we use open-source software. We make calculations for every project to determine if it is financially viable and, based on that, we make decisions on whether to greenlight it.”
Putyatinsky said that CBoM’s areas of priority, particularly for artificial intelligence technology include making loan decisions, processing full-text documents, financial monitoring and dealing with overdue debts.
Rosbank, another leading Russian lender, leverages artificial intelligence (AI) technology specifically for processes that involve loan issuing, uncovering fraud, optimization of the branch network, interaction and communications with customers.
“We believe that over the next one to two years, AI will also be adopted for the bank’s other processes that are not directly linked to interaction with customers,” said Dmitry Smirnov, head of Rosbank’s data lab.
“Accumulating large amounts of data and the arrival of new data sources will facilitate that. We are actively exploring areas where AI could be potentially adopted.
These are processes aimed at improving the organization’s efficiency and, from the customer’s viewpoint, processes that simplify their interaction with the bank.”
At the moment, Promsvyazbank’s key areas for applying AI include creating offers for customers, uncovering fraud, and credit decision-making.
“Currently, we are working on broadening the scope of AI application,” said Daniil Tkach, head of the customer relations department at Promsvyazbank.
“In the short term, automated systems will tell us which products would be the best offer for a customer, what channels will be the most efficient and what communication style will be most amenable to the customer.”
Tkach said that the primary conditions for the broader spread of artificial intelligence include a sufficient amount of reiterations of processes designed for learning purposes, reliable systems for collecting data, and a sufficient level of manageability and automation.
According to him, this can be applied in almost all banking activities such as operations, anti-fraud, communications, and sales.
“We could also single out intellectual management systems, in which AI substantially helps superiors to understand the quality of work by their employees and provides tips to all employees for possibly improving their work,” Tkach said.
Nonetheless, Russian banks still view artificial intelligence as a technology that can assist in automating new areas as opposed to replacing the already available automation solutions.
“We are not trying to revamp existing solutions,” CBoM’s Putyatinsky said. “Instead, we look at areas that have not yet been automated and start automating them from scratch with the use of new technology.”
Challenges affecting AI Adoption
The process of AI adoption, especially in the banking sector is not always flawless.
There are challenges affecting the wider spread of technology across the entire banking industry.
According to Expert RA’s study, such impediments include data inconsistencies in information systems, but once that problem is resolved, getting qualified personnel to help in processing the data is expected to be a major issue.
Industry insiders have already raised complaints regarding the challenges faced in getting qualified individuals to operate artificial intelligence (AI)-based solutions.
“The main factors that are impeding the adoption and development of AI are shortages of qualified professionals and problems with the infrastructure of information systems,” said Smirnov.
READ MORE: 6 Reasons that Hinder Full AI Adoption
Putyatinsky agreed, claiming: “The acutest issue is the training of qualified personnel.”
To address this problem, CBoM has been operating an internship programme dubbed IB Universe for the last one year. “This allows students and recent graduates to acquire practical experience in various areas of investment business,” added Putyatinsky.
Putyatinsky said that such educational programmes would ultimately enable banking institutions to train people in the working environment, generating a new breed of employees who will be sufficiently ready to work with new technologies like machine learning (ML) and artificial intelligence (AI).
Another problem facing the application of artificial intelligence (AI) is the sophistication of the technology’s algorithms, Promsvyazbank’s Tkach claimed “Contemporary machine learning algorithms are so complex that humans have problems understanding decisions made by AI,” he added.
The Expert RA study also said that over the coming few years, the progress made with AI adoption in Russia’s banking industry is expected to mainly rely on investments in personnel training, the ability of banks to retain and attract clients, and investments in regional networks.
“The good news is that at this point, a bank doesn’t need to make an enormous investment to become one of the [Russian banking industry’s] AI leaders,” said the study’s authors. “But the bad news is that to achieve that, you have to act right now.”