The Kingdom for AI: How many banks save on machine learning, neural networks and chat bots
Credit rating on the client profile on Facebook, robots for debt collection and financial advice to investors, the fight against fraudsters and the battle with the routine - artificial intelligence in banks is needed in almost all areas. How AI helps Sberbank, VTB, Tinkoff Bank and other financial institutions to save billions of rubles is in the Binary District review.
According to the forecast of research company Autonomous Next, by 2030, banks around the world will be able to reduce costs by 22% with the help of artificial intelligence technology. Savings could reach $ 1 trillion.
Russian banks are already earning and saving large sums using AI. Thus, in 2017, Sberbank earned an additional $ 2–3 billion (the bank’s net profit for 2017 was about $ 11.6 billion) only through the use of AI and data analysis in risk and sales management.
We selected seven tasks that banks solve with the help of artificial intelligence, and we looked at how it benefits them.
Credit scoring is the most promising area for introducing AI. Its capabilities in this area were used by most Russian banks surveyed by the Expert RA rating agency in 2018 (11 banks took part in the study: Tinkoff, Gazprombank, MTS Bank, Moscow Credit Bank, Russian Standard Bank, etc.).
In Sberbank, AI is already making 98% of decisions on granting loans to individuals. Credit risks are analyzed on the basis of the user's “digital footprint”. According to the head of the bank German Gref, this footprint already reaches 500 MB per day, and on its basis the “second digital“ I ”is formed, which“ very precisely repeats our human “I”.
Credit risks with legal entities are still harder to assess: here the AI can make only 30% of the extradition decisions.
The second popular field of application of AI in banks is robot collectors. Sberbank was also a pioneer here: in 2016, it introduced a pilot project of its subsidiary company Active BK. After a year, the efficiency of the robot was almost a quarter (24%) higher than that of live operators: so much more often the debtors paid overdue payments within two weeks after the car’s call.
After that, AktivBK worked with another 27 banks (Otkritie, Binbank, etc.); in 2017, this direction brought the company about 25% of its total revenue. In the fall of 2018, a collector robot developed by the company introduced a VTB after three months in pilot mode.
Pochta Bank was one of the first to introduce biometric technologies in its branches in 2015. Now the facial recognition system is equipped with more than four thousand branches of the bank and 50 thousand stores of the bank's partners in POS-business. Two-factor authentication - by login / password and photo - is also necessary for bank employees to gain access to the CRM system and other business applications.
In 2016 and 2017, this saved Mail to the Bank a total of 3 billion rubles: in 2016, the bank received 9.2 thousand fraudulent applications for a loan of 1.5 billion rubles, in 2017 - about 10 thousand applications for the same amount. The system helped to identify who received these applications. The results for 2018 have not yet been summed up.
Alfa-Bank in 2018 was going to replace people with robots in thirty routine business processes. After the automation of the first seven processes, an annual savings of 20 million rubles was achieved. As a result, the bank planned to save up to 85 million rubles annually.
The bank handed over to robots such operations as processing payments of legal entities and individuals, processing unidentified payments, analyzing internal incoming mail, changing customer data on his application, editing individual loan agreements on their applications, as well as posting contact financing and answering typical requests.
Alfa-Bank used Blueprism platform for working with robotic programs (a three-year license costs less than a million rubles). Each robot receives a virtual workplace, on which the Blueprism agent is installed and the software required for operation. Further, the system is taught by a person familiar with the business process of the bank and with the technology of learning robots. Prior to that, the operating staff had to grow by 3.3%, but in the end the bank decided not to hire new employees.
Robo-advancing is another area that has been more actively interested in Russian banks since last year. One of such robot advisers for its Tinkoff Investments brokerage platform launched the Tinkoff Bank in July 2018.
For the first month after the launch, according to the bank, 42,000 people used the application. In total, during this time, 142,000 investment portfolios were generated. The average bill for the purchase of assets with the help of a robot adviser was 60 thousand rubles and 1678 US dollars. Most users purchased ruble securities.
Earlier, in 2016, similar projects were launched by Sberbank together with FinEx, AK Bars Bank and VTB24 (the latter joined VTB in 2018). At the same time, Conomy created its robot advisor, the Right application.
Rosbank in 2018 found another way to use AI - for the development of a retail network. About this in the column for Future Banking told the deputy chairman of the bank Arnaud Denis. According to him, the bank used technology from Marketing Logic, which specializes in geo-marketing.
The system developed by this company uses machine learning. She assesses the potential of a place for a new branch by 250 variables, which are divided into three groups. The first group is geo-characteristics (distance to the center, to the metro, price per square meter, etc.), the second is traffic (the number of ground transportation routes in different radii from the location) and the third are objects (availability of shopping centers, business centers, houses and banks).
Due to the analysis of all these parameters in the next few years, the bank plans a "significant increase" in the financial performance of the branch network. (now the bank has 350 branches).
Chat bots are one of the most effective ways to answer questions from employees and customers 24/7. According to the R-Style Softlab survey conducted in 2017, every fifth bank (21%) in Russia and in the CIS was ready to use bots, and most of the lending institutions planned to introduce them in 2018.
One of the most successful examples in 2018 was the bot of Alfa-Bank, developed by it for its employees-users of payroll projects. Prior to its introduction, bank operators daily received over a hundred calls from colleagues with questions about the conditions and rules for opening bank accounts. As a rule, these were standard questions. After they were handed over to an intelligent bot, the teller began to answer other questions 50 times faster.
In addition to chat bots, in theory, banks can use voice assistants. This is a more sophisticated technology, there is only one working voice assistant in Russia - “Alice” of Yandex. In December 2018, the head of Tinkoff Bank, Oleg Tinkov, announced that the bank plans to create such an assistant.
Learn more about how to use facial recognition, neural networks, and machine learning in different business areas at the AI for Business two-day course. The course speakers from Microsoft, Nanosemantics and Home Credit Bank will tell you how to use different types of AI and what tools are available for this. The nearest intensive will take place on March 30-31.
For those who want to learn how to apply machine learning for different tasks - AI School . It is designed for developers who have minimal Python skills. The closest course is from March 2 to April 6.
How many banks save on the introduction of AI
According to the forecast of research company Autonomous Next, by 2030, banks around the world will be able to reduce costs by 22% with the help of artificial intelligence technology. Savings could reach $ 1 trillion.
Russian banks are already earning and saving large sums using AI. Thus, in 2017, Sberbank earned an additional $ 2–3 billion (the bank’s net profit for 2017 was about $ 11.6 billion) only through the use of AI and data analysis in risk and sales management.
We selected seven tasks that banks solve with the help of artificial intelligence, and we looked at how it benefits them.
What tasks AI helps to solve
1. Check the borrower
Credit scoring is the most promising area for introducing AI. Its capabilities in this area were used by most Russian banks surveyed by the Expert RA rating agency in 2018 (11 banks took part in the study: Tinkoff, Gazprombank, MTS Bank, Moscow Credit Bank, Russian Standard Bank, etc.).
In Sberbank, AI is already making 98% of decisions on granting loans to individuals. Credit risks are analyzed on the basis of the user's “digital footprint”. According to the head of the bank German Gref, this footprint already reaches 500 MB per day, and on its basis the “second digital“ I ”is formed, which“ very precisely repeats our human “I”.
Credit risks with legal entities are still harder to assess: here the AI can make only 30% of the extradition decisions.
2. Kick off debts
The second popular field of application of AI in banks is robot collectors. Sberbank was also a pioneer here: in 2016, it introduced a pilot project of its subsidiary company Active BK. After a year, the efficiency of the robot was almost a quarter (24%) higher than that of live operators: so much more often the debtors paid overdue payments within two weeks after the car’s call.
After that, AktivBK worked with another 27 banks (Otkritie, Binbank, etc.); in 2017, this direction brought the company about 25% of its total revenue. In the fall of 2018, a collector robot developed by the company introduced a VTB after three months in pilot mode.
“For now, it is effective for small periods of delay. The average talk time is one and a half minutes, which is comparable to a conversation with an operator. If an employee makes about 200 calls a day, then for the robot this number is practically unlimited, ” said the deputy chairman of the board of VTB, Anatoly Pechatnikov, in an interview with the Izvestia newspaper.
3. Fight scammers
Pochta Bank was one of the first to introduce biometric technologies in its branches in 2015. Now the facial recognition system is equipped with more than four thousand branches of the bank and 50 thousand stores of the bank's partners in POS-business. Two-factor authentication - by login / password and photo - is also necessary for bank employees to gain access to the CRM system and other business applications.
In 2016 and 2017, this saved Mail to the Bank a total of 3 billion rubles: in 2016, the bank received 9.2 thousand fraudulent applications for a loan of 1.5 billion rubles, in 2017 - about 10 thousand applications for the same amount. The system helped to identify who received these applications. The results for 2018 have not yet been summed up.
4. Rid of routine work
Alfa-Bank in 2018 was going to replace people with robots in thirty routine business processes. After the automation of the first seven processes, an annual savings of 20 million rubles was achieved. As a result, the bank planned to save up to 85 million rubles annually.
The bank handed over to robots such operations as processing payments of legal entities and individuals, processing unidentified payments, analyzing internal incoming mail, changing customer data on his application, editing individual loan agreements on their applications, as well as posting contact financing and answering typical requests.
Alfa-Bank used Blueprism platform for working with robotic programs (a three-year license costs less than a million rubles). Each robot receives a virtual workplace, on which the Blueprism agent is installed and the software required for operation. Further, the system is taught by a person familiar with the business process of the bank and with the technology of learning robots. Prior to that, the operating staff had to grow by 3.3%, but in the end the bank decided not to hire new employees.
5. Help customers with investments
Robo-advancing is another area that has been more actively interested in Russian banks since last year. One of such robot advisers for its Tinkoff Investments brokerage platform launched the Tinkoff Bank in July 2018.
“In just a few minutes, according to the set parameters, the robot advisor can collect the investment portfolio balanced across industries and companies, taking into account the available investment amounts, with an optimal balance of risk and return,” the release explained.
For the first month after the launch, according to the bank, 42,000 people used the application. In total, during this time, 142,000 investment portfolios were generated. The average bill for the purchase of assets with the help of a robot adviser was 60 thousand rubles and 1678 US dollars. Most users purchased ruble securities.
Earlier, in 2016, similar projects were launched by Sberbank together with FinEx, AK Bars Bank and VTB24 (the latter joined VTB in 2018). At the same time, Conomy created its robot advisor, the Right application.
6. Search for a place for new branches
Rosbank in 2018 found another way to use AI - for the development of a retail network. About this in the column for Future Banking told the deputy chairman of the bank Arnaud Denis. According to him, the bank used technology from Marketing Logic, which specializes in geo-marketing.
The system developed by this company uses machine learning. She assesses the potential of a place for a new branch by 250 variables, which are divided into three groups. The first group is geo-characteristics (distance to the center, to the metro, price per square meter, etc.), the second is traffic (the number of ground transportation routes in different radii from the location) and the third are objects (availability of shopping centers, business centers, houses and banks).
Due to the analysis of all these parameters in the next few years, the bank plans a "significant increase" in the financial performance of the branch network. (now the bank has 350 branches).
7. Answer where the salary is, clearly and quickly
Chat bots are one of the most effective ways to answer questions from employees and customers 24/7. According to the R-Style Softlab survey conducted in 2017, every fifth bank (21%) in Russia and in the CIS was ready to use bots, and most of the lending institutions planned to introduce them in 2018.
One of the most successful examples in 2018 was the bot of Alfa-Bank, developed by it for its employees-users of payroll projects. Prior to its introduction, bank operators daily received over a hundred calls from colleagues with questions about the conditions and rules for opening bank accounts. As a rule, these were standard questions. After they were handed over to an intelligent bot, the teller began to answer other questions 50 times faster.
In addition to chat bots, in theory, banks can use voice assistants. This is a more sophisticated technology, there is only one working voice assistant in Russia - “Alice” of Yandex. In December 2018, the head of Tinkoff Bank, Oleg Tinkov, announced that the bank plans to create such an assistant.
“So far, very modestly, we decided to call“ Oleg ”. But maybe we’ll still change, maybe we’ll call “Ivan,” Tinkov explained.According to him, the assistant will help users in solving financial and everyday tasks - for example, transfer money or reserve a table in a restaurant. At the same time, the voice of “Oleg” will be different from that of a businessman. Other banks of voice assistants do not plan to implement yet.
Learn more about how to use facial recognition, neural networks, and machine learning in different business areas at the AI for Business two-day course. The course speakers from Microsoft, Nanosemantics and Home Credit Bank will tell you how to use different types of AI and what tools are available for this. The nearest intensive will take place on March 30-31.
For those who want to learn how to apply machine learning for different tasks - AI School . It is designed for developers who have minimal Python skills. The closest course is from March 2 to April 6.
Source: https://habr.com/ru/post/440902/