New digital assistant Oleg has a mission to help users navigate the Tinkoff ecosystem. It aims to make customers’ lives simpler, and become a friend who is always nearby. Notably, Oleg is the first voice assistant built by a financial institution as a proprietary solution. Douglas Blakey reports
Tinkoff has launched Oleg, the first voice assistant created in Russia for finance and lifestyle-related tasks.
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As the name suggests, Oleg is something of a novelty as a male digital assistant; this contrasts with earlier digital offerings such as Garanti’s MIA and Bank of America’s Erica.
Other notable examples include BNP Paribas’s Hello Bank assistant HelloiZ, Standard Chartered’s Stacy, and Emirates NBD’s Liv assistant, Olivia. Tinkoff’s new assistant is named after the bank’s founder, the ever-so-colourful Russian entrepreneur Oleg Tinkov.
His voice is synthesised from hours of speech by a famous Russian actor, who has dubbed many popular films for Russian-speaking audiences. Oleg is a man aged between 25 and 40. Tinkoff says he is polite, but firm when needed.
He is funny, but will not teach anyone how to live their lives unless specifically asked. Oleg has an inkling that he may not be human, but is not overly concerned about it.
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By GlobalDataOleg resides in the Tinkoff mobile app, is able to recognise and interpret different user commands, ask follow-up questions, solve problems and speak eloquently on a variety of subjects.
In his first version, Oleg will be able to:
• Transfer money to Tinkoff Bank and Sberbank accounts;
• Make restaurant and beauty salon bookings;
• Buy cinema tickets with a cashback offer of 15%;
• Search for discounts on products and services;
• Converse on various topics;
• Give advice and life-hacks from the Tinkoff Journal;
• Consult on banking and stocks;
• Manage financial products such as debit and credit cards;
• Change personal information in the Tinkoff ecosystem, and
• Request and email documents, such as bank statements for embassies.
In future, Oleg will become more capable and integrated into all elements of the Tinkoff ecosystem, including travel, mobile, investments, insurance, entertainment, business and Tinkoff Junior.
Oleg will also be able to identify a user’s voice using biometric data, and carry out commands that currently require authorisation in the Tinkoff app. This will enable users to carry out such tasks as transferring money while driving a car.
Teaching Oleg
As a young voice assistant, Oleg has much to learn. Users give ‘likes’ and ‘dislikes’ to Oleg’s responses, which are analysed by the Tinkoff team.
Customers can also say “enough” or “speak with a representative” if they feel Oleg is not resolving their problem successfully. Tinkoff says Oleg is set to solve the majority of customer issues automatically.
He can also call for backup from call centre staff to resolve issues he cannot solve alone. As Oleg spends more time interacting with customers, he will learn to change his tone from friendly to formal in real time, as appropriate for the nature of the conversation and the customer’s mood. As the world becomes more interconnected, Oleg is training and learning using Tinkoff’s Kolmogorov cluster, one of Russia’s most powerful supercomputers.
The Tinkoff team will be able to increase the speed with which it trains the neural networks for speech recognition and synthesis, natural language processing and open-ended conversation. Deep neural network models and voice technologies were used to create Oleg.
Tinkoff has been working on this since 2014 within its AI First strategy. In 2016, Tinkoff began work on its own voice-recognition technology, which works equally well with noisy speech received via telephone channels and clear speech from high-quality sources. Currently, this recognition technology allows Tinkoff to correctly identify up to 95% of spoken words.
It uses terabytes of data and tens of thousands of hours of human speech to continue to train and improve the technology. In 2017, Tinkoff launched its own biometric system, which makes the right decision in 99.99% of cases. In 2018, Tinkoff became the first vendor bank of the Unified biometric system in voice biometrics.
That same year, Tinkoff began developing its own voice-synthesis technology, based on neural models such as WaveNet, Tacotron and Deep Voice, making synthesised speech as close as possible to the human voice.
Voice technology is not just for the voice assistant, it also enhances Tinkoff’s automated customer service processes. Voice-recognition technology helps field around 1 million calls; meantime, a biometric system trained on customer voice data helps the call centre to combat fraud.
