- At the level of design: forecasting of demand of banking products, prediction of the shifts in demand, automated scoring of risks.
- At the production rate: automation and optimization of interaction with the existing and potential clients. Automation of document handling and approval of the credits.
- At the level of promotion: providing the personalized offers in the fullness of time. Automatic control of interest rates depending on history of the client.
- At the level of providing service: development of automated systems and interfaces of self-service in all communication channels.
Bank platform of new generation
Chat-bots and roboedvayzing
Modern chat-bots are able:
- Informing on features of products and services
- Providing contact information
- Carrying out payment transactions
- Financial recommendations to the client
- show rates and exchange currency
- carry out the accounting of personal finance
- make a transfer from the card on the card
- send requests to trade and the Internet acquiring and to check the partner by TIN/PSRN (SP)
- answer questions of the user
Robo-Advisers as perspective example of application of AI
The roboedvayzing became an alternative of financial advisors on bank questions, specific purchases and other cash transactions online.
Roboedvayzera give big advantages in the field of online trading. First of all, it is requests in one click and opening of the account in real time, monitoring, topical news and processing of large volumes of transactions at once. Distribution of brokers on social networks makes investment knowledge more available and clear, and communication with the client — simple and address.
Automation allows to present 24/7 information, at the same time reducing costs of processes. Roboedvayzera are available on a desktop or in a format of mobile applications, bear in themselves functions of the portfolio managing director defining risks and an optimal investment strategy.
Individual offers and increase in loyalty
- The recommendations of banking products and purchases (the loyalty program from different retailers), including with knowledge deployment about the client from social networks
- Determination of B2B of communications of the client with the subsequent recommendations of new partners
- Modeling of financial risks for small business (a default, a cash gap) in real time with the recommendations of target strategy and products
IoT (Internet of Things)
- Management and tracking of use of leasing assets
- "Smart" insurance for retail clients (medicine, car loans)
- Smart Home + Daily Shopping: order of products, payment of utility accounts, subscription to a TV content
Antifraud. External and insider threats
- Signs of use of the plastic card of the client by the third party
- Signs of so-called "dropper" proceeding from the nature of receipts and transactions in Internet bank and ATMs
- Detection of dummy salary projects (credits, cashing in)
- Identification of unauthorized account account transactions of clients and to plastic cards of the client
- Errors in parametrization of programs of a bonusirovaniye for plastic cards which lead to "wrapping" and damage
- Schemes of cashing in of money, including using Internet bank and plastic cards
- Abuses when carrying out conversion transactions as on physical, and legal entities
- Unauthorized connection of Internet bank to customer accounts and the plastic card issue without the knowledge of the client
- Unauthorized increase in limits of credit cards
- Identification and automatic correction of deviations in transactions
- Natural Language Processing algorithms for the analysis and generation of statements of claim
- Monitoring and forecasting of failure of infrastructure (ATMs, IT resources)
- Optimization of cash flow and a remaining balance in cash desks and ATMs. Optimization of work of collector services
- Optimization of search and hiring of personnel (analysis of the summary and primary selection)
- Speech analytics in real time for call centers and departments (quality management of consultations)
2019: JPMorgan began to use the AI copywriter who writes advertizing texts better than marketing specialists
At the beginning of August, 2019 JPMorgan Chase signed the five-year contract with the startup using artificial intelligence for copywriting. The transaction followed successful pilot testing of new technology. Read more here.
The first results of AI transformation of Sberbank: robots replaced employees in tens of processes
In the annual report for 2018 published in April, 2019, Sberbank summed up the first results of AI transformation implementation (AI – Artificial Intelligence, artificial intelligence). The bank implements the concept of AI-first, building in artificial intelligence all the processes.
According to the annual report, in 2018 the bank was concentrated on creation of the necessary conditions for AI transformation including preparation of infrastructure, data, models, processes. In bank single open platforms on which service is provided for all internal business customers are created.
Also need to have the corresponding specialists is noted. In Sberbank the competence from 200 experts in robotization of processes was created.
Routine transactions in 53 processes in bank are executed by robots instead of employees, the annual report says. Where program robots are used, 30 of them processed 100% of industrial volume of transactions, and on 23 processes 50–80% of industrial volume were processed.
Due to robotization of processes and reduction of manual work in 2018 the efficiency of a back office was increased by 25%, Sberbank claims.
The future of employees, whose work in processes it did not become necessary, in Sberbank did not specify TAdviser. In 2018 the head of bank German Gref spoke about perspectives of large-scale dismissals of personnel in connection with implementation of artificial intelligence.
Also the bank already uses AI for improvement of client experience in several products. According to Sberbank, the speed of separate client processes grew at 4-10 times.
| ||"Smart products" change credit process: corporate clients can obtain the credit in 7 minutes, and private clients spend for filling of the questionnaire at online application for the credit read minutes, - Sberbank in the annual report notes.|| |
AI is used also for the personalized communication with retail and corporate clients using chats and voice bots and also when collecting arrears.
In turn, use of AI at asset-liability management helps bank to model a balance sheet layout taking into account a set of factors, including macroeconomic and to make optimal solutions at financial planning and establishment of product rates, Sberbank states.
| ||In 2019 Sberbank will be focused on products, client experience and financial effect of use of AI, said in the annual report of Sberbank.|| |
Banks earned $41 billion from artificial intelligence
In 2018 banks earned about $41.1 billion thanks to artificial intelligence. Enter this amount as direct income from implementation of such technologies, and volume of the cut-down expenses and benefit from increase in efficiency of financial institutions (in comparison with if they left the same processes and infrastructure). The data of analysts of IHS Markit published on April 10, 2019 demonstrate to it.
According to forecasts of specialists, by 2030 commercial AI projects will bring to banks in total $300 billion.
| ||The innovation opportunities which the artificial intelligence gives to the sector of financial services are capable to lead to cardinal conversions — the leading analyst of IHS Markit Don Tait says. — AI is ready to throw down a challenge and to blur our concepts of calculations and the "normal" person. This serious change will demand from the companies and the governments of development of deep foresight and crucial understanding of all effects of digitalization and the developing technologies.|| |
Specialists say that the artificial intelligence makes a revolution in the banking sector, revealing fraud in financial transactions on the basis of the predeterminated rule set.
North America remains the largest market of use of solutions AI in the banking sector: there the companies earned $14.7 billion from such technologies at the end of 2018. To the 2030th economic effect of implementation of artificial intelligence in the region will jump up to $79 billion, analysts predict.
However by 2024 the Pacific Rim where banks will earn will get into the lead and will save thanks to AI about $50.6 billion against $11.5 billion in the 2018th. By 2030 the indicator will rise to $98.6 billion in many respects thanks to demand in such countries as China (including Hong Kong), Japan, South Korea and Singapore
However implementation of artificial intelligence technologies in the bank industry bears also negative effects — reductions of jobs and redistribution of the personnel in connection with improvement of productivity of work of financial companies due to AI technologies.
According to forecasts of analysts, the artificial intelligence will affect tens of millions of jobs in the global financial industry. In the USA, for example, it will concern 1.3 million people by 2030, and in Great Britain — 500 thousand
Among bank employees whom distribution of AI can influence in IHS Markit called cashiers, the staff of departments of client service, interviewers and clerks, financial managers, controllers and credit specialists.
| ||But in general artificial intelligence technologies will change structure of the financial industry, having made the banking sector more humane and intellectual — Don Tate considers.|| |
The fact that banks use artificial intelligence more and more actively is confirmed in consulting company Deloitte. According to the research published in April, 2019, 29% of the companies from the financial industry working in the different countries use robotic process automation — the software which automates monotonous routine work. In this selection of 25% of respondents use such technologies for risk management, 21% — for report generation about risks, 20% — for the normative reporting.
Big Data and analysts also became priority for banks — 40% from them use such tools along with artificial intelligence.
About 25% and 19% of the polled representatives of the companies said that they involve machine learning and cognitive analytics (including natural languag processing) respectively to cut down expenses and to increase the accuracy of transactions while 24% told that they use modeling tools of business solutions.
Banks with Wall Street began to use machine learning for the analysis of foreign exchange markets
On June 29, 2018 Bank of America announced the beginning of use of machine learning for the analysis of currency strategy. As a reason for carrying out a research in the field of artificial intelligence which analysts of bank began in June, 2018 the unstable political situation served in Italy — specialists were afraid that it will affect not only euro, but also other European currencies, and it threatens with the next financial crisis.
In the first research of Bank of America algorithms of machine learning are estimated on efficiency of work with the fundamental and survey data, for example, concerning the public expenditures and consumer expectations. A problem of AI — to make the forecast of the relations of currency pair euro-dollar. The command used as controlled training when the machine should analyze the data marked by the person and reveal patterns, and uncontrollable training when the person does not control process any more and does not give AI of any instructions.
| ||Because of the nature of the market of foreign currencies to predict its future only on the basis of the known situations quite difficult therefore we try to involve machine learning to the alternative strategy of assessment — the currency strategy specialist Alice Leng who developed a market research on the basis of AI in Bank of America noted.|| |
Use of machine learning for complex analyses — not an innovation in the financial sphere. But, according to Vasant Dhar, professor of information science of New York University and the founder of SCT Capital Management - a hedge fund which within two decades relied on applications for machine learning - foreign exchange markets still represent a major issue for AI algorithms. The complexity and a variety of macroeconomic factors which can influence intermonetary relations can significantly complicate the analysis in this sphere, unlike the normal stock exchange markets long ago applying AI and machine learning.
Despite active use of AI, most banks did not manage to implement it in the work at the global level yet. In the report on digital bank service in fall of 2017 the vast majority of financial institutions noted that it to some extent used machine learning, but as analysts note, only less than 20% were beyond the simplest techniques of work with AI.
Among three largest banks Bank of America of the USA the first included developments of models of machine learning in publications of results of currency researches. The research group of financial holding JP Morgan studied applications for machine learning, but did not decide to use them yet. The Wells Fargo banking company states that it adheres to fundamental economic approach for the analysis of foreign exchange markets as trusts the experience in it the sphere. Many do not trust computers which analyze information by the methods unavailable to understanding of the person, and claim that they are not ready to accept the predictive conclusions of AI processing data out of causes and effect relationships.
However changes already approach – for example, the Morgan Stanley commercial bank employed professor of applied information science of the Pennsylvanian university Michael Kearns who was earlier working in a hedge fund to expand use of AI, and the command of Deutsche Bank included machine learning in the analysis of the data.
Some analysts claim that they thanks to general availability of instruments of machine learning of the research Wall Street will lose the relevance as investors will be able to develop own analysis techniques on the basis of AI. But Peter Uodkins (Peter Wadkins), the analyst of FX Aite Group, considers that it not so possibly, apparently, for machine learning quite large amounts of data and hi-tech methods of their processing are required.
As collectors use artificial intelligence for knocking-out of debts
By June, 2018 the Chinese collectors began to use actively new technologies, for example, the artificial intelligence, for the purpose of collecting of the debts which arose as is supposed, because of a speculative credit bubble of $200 billion in size which was created in the crediting industry between individuals in the country.
From 2013 to 2018 in China there were thousands of the new companies which mediated between private creditors and people, needing cash. However because of the burst scandal these companies appeared under cross fire of regulating authorities, and from the middle of 2017 when the Chinese government introduced loan granting control and also licensing of creditors and intermediaries, very many similar companies providing the services as individuals completely stopped the activity.
By estimates of analytical online company Wdzj.com the outstanding debt between individuals for May, 2018 made more than $200 billion, and the growing number of debt repudiations opened a door to a wave of startups on the basis of the latest technologies using which creditors try to recover the issued means, transfers the Financial Times edition.
Crediting between individuals is widely used in China, but the government carefully traces only an official banking system, Cherry Sheng, the chief executive of the company on collecting of debts in Shanghai Ziyitong and the former manager of Citigroup and ANZ Bank notes. However thanks to emergence of advanced technologies even individuals had an opportunity to repay a debt.
The Ziyitong company which managed to repay about $29 billion debts from the moment of the opening in 2016 started the platform on the basis of artificial intelligence recently to return overdue loans. As clients of Ziyitong about 600 debt collection agencies and more than 200 creditors, including Alibaba Group and Postal Savings Bank of China as Cherry Sheng reports act.
A system analyzes the data on borrowers and their friends available on the Internet, and then contacts the borrower by phone using the dialogue robot. A talk registers and analyzed using an algorithm which then defines a formulation which with the largest probability will take effect on the borrower and will force to repay a debt. A system also contacts his friends and with their help asks the borrower to return money.
According to Cherry Sheng, as of May, 2018 the system on the basis of artificial intelligence used by Ziyitong showed very high coefficient of compensation - 41% for large customers on the credits delayed for a period of up to one week. For comparison – the efficiency of traditional collection methods of return of debts on the similar credits is only 20%. Ziyitong is also going to use the AI system for return of the credits delayed more than for one week.
Yigou, one more startup for debt collection, started the application for mobile phones which allows collectors to carry out search in thousands of individual debt records and to select necessary cases, simplifying interaction between creditors and collectors. The company can also provide location-based data of some borrowers to help collectors to keep track of their location.
Wen Yeung, the chief executive of Yigou company, noted that the latest technologies began to play a significant role in the collection industry. According to him, many companies providing services in crediting between individuals were forced to organize own collection cells as the number of cases of an unpaid debt in this sector considerably grew.
Considering that regulatory bodies do not stop trying to intercept a flow of cash collectors of such companies expect from shadow banking and asset managers who provide filling of loan funds between individuals that by the end of 2018 more and more borrowers will evade from return of the credits. As individuals do not report on the activity, precisely it is difficult to determine debt volume, however collectors assess a situation as unfavourable.
Microsoft, IBM and Google forced Sberbank to review approach to artificial intelligence
Having communicated to representatives of the world IT companies, such as Microsoft, IBM also Google Sberbank reinterprets the approach to transformation in the area AI (AI – Artificial Intelligence, artificial intelligence). Such conclusion can be drawn from the words of the chairman of the board of Sberbank German Gref during a conference call with top managers of Sberbank and analysts on February 28, 2018.
| ||We spent much time with our partners from Silicon Valley, Microsoft, IBM and Google and understood that AI transformation – it differs a little from what we did several months ago and the last several years, - Gref's words in official interpretation of a conversation are quoted. - It means that we need to transform all our technology roadmaps and plans for transformation through the concept of artificial intelligence.|| |
The head of Sberbank added that at the beginning of 2018 in bank the program of AI transformation started, and hoped that at the end of March the bank will have more understanding that it means for it.
In September, 2018 German Gref told that until the end of 2018 Sberbank is going to implement 159 projects with use of artificial intelligence technology. There is no field of activity in the company in which the bank would not try to use artificial intelligence, he noted.
Implementation of artificial intelligence considerably changes an internal business landscape of the company: a business model, convenience to clients, costs, profitability, the head of Sberbank emphasized. There came the period when the company if it does not use artificial intelligence in the activity, it loses, Gref said.
Even earlier the head of Sberbank noted that in 5 years about 80% of transactions in bank can be made using artificial intelligence and without participation of people.
Substitution of thousands of employees robots in the Japanese banks
At the end of October, 2017 it became known of plans of the leading Japanese banks to automate about 30 thousand jobs as, according to the companies, the traditional business model does not allow to increase profit any more.
According to the Japanese business publication Nikkei, Mizuho Financial Group is going to replace by 2021 financial year about 8 thousand employees with computers, and to the 2026th — to increase this indicator to 19 thousand.
One more large financial institution from Japan — Sumitomo Mitsui Financial Group prepares for large-scale automation. According to its plans, by 2020 financial year robots will carry out tasks which by October of the 2017th require 4 thousand human.
Does not lag behind competitors and Bank of Tokyo-Mitsubishi UFJ. In plans of this finance corporation it appears automation of 9500 working positions by 2023 financial year. At many Japanese companies financial year comes to the end at the end of March.
Due to use of computing algorithms instead of people Mizuho Financial Group expects to consolidate paper work, having minimized the number of personnel with the duplicated functions.
Also about 100 routine working tasks will be undertaken by new robotic processing system which Mizuho Financial Group at first used only for data entry when opening investment accounts on the website.
However, large-scale digitalization does not assume only reduction of the staff of Mizuho Financial Group. For example, fall of 2017 about 200 employees of a back office whose functions replaced computers, are transferred to customer relations departments. Besides, Mizuho Financial Group intends to increase number of specialists in financial technologies.
Sumitomo Mitsui Financial Group is going to transfer a part of the services provided by bank departments to a digital format. By October, 2017 the company opened nine data centers which will be engaged in processing of new data in Japan.
AI Robot of Vera
AI Robot of Vera — service of the automated selection of candidates for vacancies. Service is created based on machine learning technology, is capable "understand" the natural speech of the person and process more than 10 thousand calls at the same time, accelerating, thus, process of selection of candidates. According to the founder of Stafory (Stafori) of Vladimir Sveshnikov, all process of hiring thanks to service is reduced till three o'clock.
As the artificial intelligence changes banks. 6 trends from Mikhail Hasin, the senior managing director of Sberbank
In the performance on TAdviser SummIT 2017 Mikhail Hasin, the senior managing director of the Technologies block of Sberbank, told how the artificial intelligence (AI) becomes the driver of technology innovations in banks.
The artificial intelligence, according to Mikhail Hasin, is already rather developed and reliable in all that concerns risks, confidentiality, problems of a human factor and marketing strategies. In the bank environment 6 key trends connected with artificial intelligence are noticeable.
Chat-bots. If before people called in contact center and communicated with the employee of the bank, then now more and more banks implement at themselves chat-bots. The person communicates with the robot and obtains all necessary information and service. Communication can be built in the form of Sms or in the form of the text which can be typed in a chat. At the same time the chat-bot can analyze needs of the client and right there provide different financial recommendations.
Roboedvayzing or algotrading. The Roboedvayzing became an alternative to financial advisors on bank questions, purchases and cash transactions. The volume of a portfolio which is under control of robots in financial markets of the USA now reaches 1 trillion dollars. By 2020 it will make already more than 2 trillion dollars.
Individual offers and increase in loyalty. The person plunges into the world of AI more and more, and he begins to receive more and more services in real time. The analysis of what happens to it allows to offer very effectively different unique personified offers. All service in the digital world becomes more and more personal.
| ||If the person in social network collected more than 200 likes, and we well know profiles of those people which these likes delivered, then on the basis of this information it is possible to learn about this person more, than the nearest relations know. There is other analytics which shows that unambiguously to define the person, it is enough to know his 3 most frequent GPS coordinates, usually the house, work and some favourite place. Actually, on the basis of information of this sort it is possible to understand the social environment with whom he communicates - it is possible to determine by such information more effectively credit rating which this person can appropriate, - Mikhail Hasin gives an example.|| |
Having defined that the person works in the field of agriculture, it is possible to offer it different products connected with a harvest insurance. On small business, analyzing supply chains and partners of the enterprise and also analyzing seasonality of deliveries and payments, it is possible to predict very precisely at what moments the client can face spaces of liquidity or local cash gaps. And in advance to offer the services, to save the entrepreneur from hassle. Such services become more and more demanded.
Internet of Things. By 2025 in the world there will be about 28 billion devices, about 5 on each person, connected to the Internet and providing information. It leads to the fact that any person will leave so-called electronic marks in a cloud. Mikhail Hasin sees opportunities for emergence of new types of services here. For example, analyzing time, the fact that the person got into the car, AI can define that that is going to go home, and at once to offer the necessary route. Or, understanding where and behind what the person usually goes to do shopping, it is possible to do the preorder automatically. The person will need only to stop by at shop and to take away purchases.
Smart refrigerators which will actually recognize everything that is at present in them are now developed. It becomes not by the barcode or RFID, and using the camera.
| ||It means that it is possible to the smart refrigerator, understanding that it is a standard consumer basket and that is in it at present, automatically to do the order. Moreover, at the following level he can address to different shops and do the order where this basket costs cheaper. All this opens the new horizons as systems should behave and as financial services should be integrated into them, - Mikhail Hasin explained.|| |
Antifraud. The artificial intelligence becomes a powerful board on the way of external and insider threats. For example, analyzing frequent places of purchases of the client, it is possible to define who exactly makes this purchase, to detect signs of use of the plastic card of the client by the third parties. The list of the algorithms revealing a fraud, huge it constantly extends, important area where there are investments.
Operational efficiency. The overwhelming number of actions which now in back office are done by people can be automated and algoritmizirovat. There will be a total failure from paper, to automatic recognition of documents and storage of scans on electronic media, lack of need to come physically to bank and to transfer these documents.
There will be a transition from work on transactions for work with deviations. People will monitor deviations in time and terms of carrying out this or that transaction and to take measures, and processes will go practically with the 100th level of automation of %.
| ||In order that all this easy could be integrated into the current bank services, it is necessary that the bank platform supported it. It is obvious that those platforms at which banks work generally now were created 10-15 years ago, in them embedding of these algorithms is impracticable. Therefore banks are puzzled now with how to make engineering of the landscape to have an effective possibility of embedding of artificial intelligence and machine learning to the bank platform, - Mikhail Hasin summarized.|| |
The TAdviser SummIT conference took place in Moscow on May 31, 2017. For the first time it was carried out with official support of the Ministry of Telecom and Mass Communications of the Russian Federation. At a conference the reports devoted to global technology trends, the changed political and economic realities, their influence on the IT industry were heard. Also sessions on IT in the separate industries were organized. 400 IT heads of the large commercial and state organizations, top managers and experts of the IT companies participated in an action.
In panel discussions participants of the summit exchanged views and forecasts on perspectives of development of technologies and information systems.
Sberbank will transfer work of 3 thousand employees to robots lawyers
Sberbank in 2017 "will release" about 3 thousand jobs thanks to implementation of so-called family of robots lawyers, the vice chairman of the board of bank Vadim Kulik reported on the Gaidar forum . Kulik emphasized that it does not mean automatic reduction of staff.
The banker specified that Sberbank in the fourth quarter 2016 already "started the robot lawyer who can write statements of claim".
"It is one of examples of the working robots. Actually at the moment it means that honor all claims which are written at us on individuals, completely will pass to these robots within this half-year 2017" — he told.
The representative of Sberbank added that the innovation will allow "release" about 3 thousand jobs, but it does not mean that all employees who were engaged in this work will be laid automatically off.
"These people will get under the program of retraining. If we do not find how to retrain them, then reductions will begin further" — explained to the deputy chairman of Sberbank.
The sandpiper added that the bank aims to lay off employees so that not to affect labor market. At the same time he recognized that new technologies force bank to implement actively robots and in a set of other directions. "At us big and aggressive paypline" — he added, but did not specify parts.
The sandpiper commented later through the press service of Sberbank that it is about transfer to robots of preparation of standard claims and that it "will exempt lawyers of bank from routine work and will allow to be focused on the solution of difficult legal issues".
Research R-Style Softlab
Only every fifth domestic bank applies this technology, however an absolute majority of banks consider it perspective. In half of the polled organizations are ready to undergo payment transactions and information services in messengers. Every third bank is ready to entrust chat-bots of function of blocking of payment cards, in every fifth — confirmation of transactions. It these researches R-Style Softlab which passed from February to April, 2017 took part in it heads and specialists IT and business divisions of 100 Banks of Russia and the CIS, more than a half of which are banks of category of TOP 100.
Growth of number of the Russian Internet users, availability smartphones and further development of the mobile Internet create new habits and behavior models. Users of social networks and mobile applications are guided by obtaining instant result and implementation of target action in couple of clicks more and more that in many respects explains rapid rise of popularity messengers WhatsApp, Viber and Telegram Messenger.
However the need for receiving qualitative financial services and personal consultations did not disappear anywhere: people still call in call centers. Despite development of the RBS systems, the number of addresses in phone, according to representatives of 30 largest credit institutions, lately significantly increased.
The technology of chat-bots allows to optimize business processes and to reach reasonable compromise in the solution at once of several versatile tasks: simplify interaction of the user with bank, increase the level of service and reduce finance costs by work of call center and service of the SMS notification. Simulation of dialog happens in the chat environment, usual and comfortable for the client, at the same time he receives the choice of the services earlier available only on the website or through the RBS system — all this allows to save and increase loyalty.
Unfortunately, at the moment full text recognition and processing of any requests of the interlocutor by means of artificial intelligence technologies cannot be brought to acceptable level.
Distribution of many companies, perspective, according to, the so-called interface bots created on platforms of Telegram and Facebook does not resolve an issue of high-quality simulation of a live conversation and preserving of a customer loyalty. "Colloquial" bots, first of all their primitive options created with the entertaining purpose quite often are exposed to criticism in connection with limitation to on what they are capable to conduct dialogues.
As the feeling of live contact is important for the person at discussion of questions with bank, the most right direction development of "colloquial" bots on condition of existence in them of ample opportunities of the language analysis seems. At the thought-over implementation it is possible to call them the "correct" chat-bots capable to qualitatively imitate the human speech.
Such solution will seriously lower load of call center, will save a possibility of live dialog and will allow in complex cases to transfer a conversation to the specialist of bank, helping it with solution — function of the offer of hints to the operator from base of trite phrases is activated.
Head of Sberbank: In five years the bank will be able to make 80% of all decisions using AI
"We counted if to compare bank today and Sberbank five years ago, then about 50% of those decisions which were made by people are accepted by machines today. And in five years, we consider that we will be able to make about 80% of all decisions automatically using artificial intelligence" — told.
The head of Sberbank specified that in that case these processes will happen "much with higher quality". "It means that in our case tens of thousands of people will lose the today's work" — Gref concluded.
AI for selection of employees on Wall Street
On June 7, 2016 the Reuters agency published article devoted to volume as banks with Wall Street in attempt to cut down expenses address software developers that those helped with process optimization of search of suitable employees. It is staked on the artificial intelligence (AI).
Similar technologies allow to reveal qualities, useful to the employer, in applicants, including capability to work in a command, commitment, will power and other pluses which can not always be detected in the summary or during the interview.
The possibility of implementation of AI in work is considered by such financial giants as Goldman Sachs Group, Morgan Stanley, Citigroup and UBS Group. For example, Citigroup by the beginning of June, 2016 tests the technology developed by Koru Careers company for elimination of candidates. Software is tested on a small employee group, working in corporate and investment structures.
The program defines "a corporate print" of business (set of qualities of the acting employees on which high working rates of the company depend) and estimates qualities of candidates on the basis of the analysis of the short video in which applicants tell about the strengths and career aspirations. A system considers not only the speech speaking, but a method of giving of the presentation, including "body language" and rate of a talk. Koru allows to hold testing on the Internet, the mobile phone or on the local computer at office where the person who is looking for work came.
Users of software of Koru pay developers for drawing up "a corporate print" and also for each candidate who passes test. Koru claims, offered by software company allows to reduce the number of unsuccessful employments by 60%.
| ||Until recently the moment of technology helped to find only the best summary, now they will be able to understand really the people who addressed for work — Mark Newman, the head of the HireVue company developing the AI platform for assessment of candidates on video employment interview noted.|| |
In banks hope that similar developments will help to get rid of expenses in case of problem hiring and to improve a situation in labor market. The artificial intelligence, according to financiers, will allow to select the employees capable to cope with this or that work, thanks to creation of the templates constructed on the analysis of data bulks.
Employment of the bad employee can cost much to the company — to lead to big financial expenditure and loss of business opportunities. According to the experts Capital One Financial, losses from unsuccessfully employed worker can be measured by three salaries of the person who would be ideal for this position.
Developers program providing for selection and personnel management aim to save the clients from human errors, such as elimination of strong candidates who at first sight seemed weak, the area director on personnel recruitment of recruiting company Monster Worldwide Matt Doucette says.
| ||The best seller — it is normal not the one who overacts, and that person who modestly sits in a corner who avoids attention and asks the correct questions — Dusett told.|| |
According to the informed sources of Reuters, in UBS bank the computer algorithm allowing to analyze the summary for search of candidates with the necessary parameters and also technology of selection of strong candidates is used.
Goldman Sachs Group applies own software to search in the summary of the necessary qualities, such as team work, honesty and judiciousness. Also the company uses personal tests for the best understanding of qualities of the most successful bankers and traders.
The artificial intelligence is involved not only in the American banking sector, but also Russian. At the beginning of 2016 the Russian company Krawlly and iBank Global bank provided the personal financial assistant capable to aggregate data from different banks, to make a categorization of expenditure and to give personal advice on the basis of the analysis of Big Data. The software using possibilities of AI helps to offer bank clients different affiliate programs on investments of money.
- Robots (robotics)
- Robotics (world market)
- In the industry, medicine, fighting
- Service robots
- Collaborative robot, cobot (Collaborative robot, kobot)
- IoT - IIoT
- Artificial intelligence (AI, Artificial intelligence, AI)
- Artificial intelligence (market of Russia)
- In banks, medicine, radiology
- National Association of Participants of the Market of Robotics (NAPMR)
- Russian association of artificial intelligence
- National center of development of technologies and basic elements of robotics
- The international Center for robotics (IRC) based on NITU MISIS
- ↑ Global Business Value of Artificial Intelligence in Banking to Reach of $300 Billion by 2030, IHS Markit Says
- ↑ AI Invasion of Wall Street Is Reshaping BofA’s Currency Research
- ↑ China’s debt collectors focus in on of $200 bn P2P debt pile
- ↑ Japan's megabanks to automate around 30.000 jobs' worth of work
- ↑ of RBC: Sberbank will transfer work of 3 thousand employees to robots lawyers]
- ↑ 6,0 6,1 [http://www.rbc.ru/finances/08/09/2016/57d194e69a79470ff754a8ac?from=main Gref Cherez
- ↑ Wall Street hopes artificial intelligence software helps it hire loyal bankers
- ↑ iBank and Krawlly will offer the market of the personal financial assistant with artificial intelligence