#12/2021 Financial LoB 34. A Glance at Avaloq Implementation in Singapore & Australia 38. Sybase Database Migration 12. ESP32 JOURNEY TO THE CLOUD 0+ #12/2021 4 The Fundamental Review of the Trading Book Jonathan Corsane 8 The FinTech Disruption in India Jakil Dedhia 12 ESP-32 Journey To The Cloud Richard Clarke 34 A Glance at Avaloq Implementation in Singapore and Australia Liu Lei 38 Sybase Database Migration Mikhail Zankovich 44 How Investment Banking Functions These Days Juliana Baliasova 50 Digital Trends in the Banking Industry Victor-Valentin Filipoiu LoGeek Magazine, 0+ Chief Editor: Dilya Saramkova Editor: Julia Murashova Have any comments, suggestions, reports of copyright violations or want to be a part of the next issue? Please contact us at [email protected] All rights reserved © Luxoft Global Operations GmbH, 2020. The materials are not an offer. The opinions expressed in the articles are not representations of fact; the opinion expressed in each article is the opinion of its author and does not necessarily reflect the opinion of Luxoft Global Operations GmbH. Therefore, Luxoft Global Operations GmbH does not accept liability for any errors or omissions in the content of articles or of the expressed authors’ opinions, which may arise as a result of the publication. THE FUNDAMENTAL REVIEW OF THE TRADING BOOK THE WHO THE WHEN The Basel Committee on Banking Supervision (BCBS), The first consultative paper on the framework was a committee of banking supervisory authorities, issued in mid-2012, with the second closely following in was established in 1974 by a group of ten countries 2013. By 2014, the BCBS had instigated two Quantitative in, you guessed it, Basel, Switzerland. The BCBS has Impact Studies (QIS), with the first requiring banks had the Fundamental Review of the Trading Book in to calculate regulatory capital based on a BCBS- development since 2009 in its revisions to the Basel created hypothetical portfolio followed by the banks’ II market risk framework, aka Basel 2.5. Its aim was to actual portfolios. At the end of 2014, a final paper address deficiencies in market risk capital in a post- that covered outstanding issues was released, with a financial-crisis world. However, it was soon clear that second round of QIS studies being completed in 2015. these changes didn’t resolve all the shortcomings of the framework. The FRTB was intended to be a fully The final version of the FRTB was released in early comprehensive refurb of the framework. 2016. Since then, questions have been raised on how 4 #12/2021 exactly to interpret and implement the changes with coronavirus has put on their market risk teams. They no one sure exactly what the impact will be. Even as want breathing room to fight market volatility without banks started the slow process of implementing the the burden of the new FRTB rules. rules, there were still several elements within the framework with unanswered worries, questions, and THE WHY inconsistencies. During a meeting in December 2017, the BCBS agreed to postpone the implementation of During the 2009 financial crisis, it was clear that a the FRTB from January 2019 until the same month in number of financial institutions were over-leveraged 2022. and didn’t hold enough capital to cope with stressed market conditions. It also became clear that the BCBS Even now, some EU banks are seeking a further FRTB couldn’t rely on the banks’ own assessment of if assets delay due to the added strain, excuse the pun, that should be included in banking or trading books. The 5 problem with these books was the criteria was difficult systems would send these P&L vectors back to the risk to regulate and there could be large differences in engine in order to be aggregated. capital requirements for similar product types on either side. This led to risk arbitrage, particularly in the The idea of a ‘golden’ source of market data is par- treatment of credit products. amount in ensuring confidence in the metrics pro- duced. There needs to be a clear data lineage of The FRTB aims to provide a clear delineation between front-to-back trading data used in risk calculations. trading and banking books, and proposes significant Having this golden or global source as reference for changes to both models used for calculating all downstream risk calculations across the bank pro- regulatory capital charges: the internal models-based vides accountability, as it ensures one version of truth approach (IMA) and the standardized approach (SA). across the banks’ systems. This standardization of risk The changes to the standardized approach make factors and sensitivities throughout a firm would allow it more risk-sensitive and require charges to be for better and more universal insights to be drawn. calculated for each trading desk as if it were a stand- FRTB is pushing banks to stand back and look at their alone portfolio. In order to test whether or not a bank infrastructure as a whole. It is giving them an op- will be permitted to use its own models or revert to portunity to improve their IT capabilities as well as to standardized values depends on a P&L attribution housekeep multiple systems into a more streamlined test in which theoretical future P&L is calculated and technical landscape. Sometimes, it takes a big shake- compared to actual values for those dates (excluding up like this to force us in the right direction. new transactions). Ratios of the difference in P&L are reported on a monthly basis, and if a bank experiences four breaches within the prior 12 months, they will be forced to capitalize under the harsher SA. Back testing and P&L attribution tests will require at least 250 days’ worth of data. This means banks will need to have their new desk/organisational structure decided well in advance. VaR (Value at Risk) has long been a method for banks to calculate potential losses. It estimates how much a portfolio might lose (with a given probability) under both normal and turbulent market conditions over a set period. However, it is well understood that it has a number of deficiencies. The FRTB framework looks AUTHOR to move from VaR to the Expected Shortfall model instead, as it can better capture tail risk and is less JONATHAN CORSANE sensitive to outliers. Jonny is a senior Murex THE HOW Consultant with over seven years of experience who thrives on learning Banks must decide how to adapt their in-house front and who takes on office and risk system IT architecture to cope with the challenges with zest and changes or work closely with external vendors to use commitment. He gained Murex accreditation by completing the MTEK program in their FRTB offerings. Most banks will opt for a cen- 2013 and has since worked with both the 2.11 and 3.1 tralized or semi-centralized model. The centralized versions of the Murex trade platform. Over his career, model would have all stages of calculation take place he has lived in London, Hong Kong, and Sydney, and in a risk engine. Positions would be imported into the he enjoys immersing himself in different cultures while risk engine and valued using market data and pricing experiencing and adapting to new environments. Jonny specializes in the Datamart and Market Risk models within the engine before being aggregated. Enterprise modules of the Murex trade platform. The semi-centralized model would generate scenarios Currently, he is working with NAB on their FRTB (stressed or historical market data change simula- Compliance project, specifically within the Risk Engine tions) in the risk engine before sending them out to stream. He has been with Excelian Luxoft Financial FO systems to revalue their own positions. The FO Services since March 2019. 6 #RunForIT In 2019, we launched a global initiative for Luxofters to unite and see how far they could run collectively. This past summer, more than 250 runners in 38 of our locations joined forces to contribute to charity – for every 5 km run and 15 km biked, 1 dollar was donated. Donations from this year’s run went to Teach for All, an organization that ensures that children have access to the learning opportunities and support they need. Advertisement #RunForIT THE FINTECH DISRUPTION IN INDIA According to a recent study, India is home to more than 687 million active internet users as of January 2020, making it the second-largest internet market after China. Interestingly, in 2019, the number of rural users surpassed urban internet users by a margin of 10%. This number has only grown in 2020. Hence, the country’s rural space is ripe for disruption by new- age fintech players, and the future will see them capturing this market segment on the back of effective digital-first solutions specifically designed for rural consumers. 8 #12/2021 Key aspects of disruption: • Financial inclusion and a mobile-first economy • Neo-banking • Digital payments • Alternative lending • InsurTech and WealthTech • Chatbots and IA (Intelligent Automation) • Risk evaluation through AI/ ML • Cybersecurity Financial Inclusion and a Mobile-First Economy A large portion of the Indian population has been excluded from the formal financial system, due to a lack of awareness about the benefits of formal banking and the inability of traditional FS players to serve this segment in a cost-effective manner. However, since the launch of governmental schemes, including Jan Dhan Yojana and Direct Benefit Transfer, and the increase in internet penetration in rural India, there has been a marked rise in awareness Neobanking levels of FS products. The traditionally unbanked and underbanked population that was earlier averse to Neo banks are the new-age interpretation of banking accessing formal FS products is now embracing them.