Exactpro in the Media

Exactpro comments on the impact of AI-related regulatory oversight

The regulatory requirements that are likely to be imposed upon AI in the nearest future are now widely discussed by governmental and international bodies. But what does it mean for the technology firms? Will the regulations bring positive changes or stifle further developments in this area? For now, it is difficult to say for sure.
On the one hand, regulation can stimulate technology innovation as firms will get additional motivation to create more robust, resilient and competitive solutions. AI-related documents issued by the US and the EU draw more attention to the risks associated with the adoption of the technology, which will naturally result in new research exploring the ways to address those risks. Another benefit of standardization can come from firms putting more effort into ensuring both data and process quality.
On the other hand, increased regulation of AI is likely to complicate the business-as-usual processes in the AI-focused firms who can be required to store all the data used to create and fine-tune the underlying models for substantial periods of time. With the additional challenges of data sensitivity issues and antitrust policies, that will require vendors to allocate more resources to storing, processing, and, in some cases, encrypting the data.
Both points, though, are closely correlated with the necessity of independent verification and validation of data and training procedures behind an AI solution.

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Exactpro on applying recent NLP research to financial technology

Natural language processing (NLP) is a well-established research direction applied to various knowledge domains, with the financial industry not being an exception.
In the financial services, natural language processing is leveraged to extract the information about the events happening globally and their perception by the people. This multidimensional information containing facts, opinions, sentiments, ranking, poll data, etc., is then projected onto the capital markets: the data provides analytical insights and the ability to predict stock market movements and identify potential risks. The most common areas for NLP application in finance are market surveillance and fraud detection, portfolio and risk management, conversational assistants in retail and investment banking.

One of the challenges of NLP being applied to solve complex tasks in finance is associated with domain-specific textual data availability. When it comes to training a model behind any AI application, it is not always easy to obtain sufficient business case specific datasets. Such approaches as BERT, developed by Google and available in open source, help to overcome this challenge.

BERT is a language model which is pre-trained on plain, unlabeled “general-purpose” textual data. The benefit of this model is that it can serve as a basis for building other, more task-specific ML models. In the case of AI-related financial tasks, this means a lot: BERT helps to perform the most difficult part of the task using non-specific text data and significantly contributes to a learning algorithm, which can subsequently be fine-tuned using domain-specific datasets (e.g. financial data) of a much smaller size.

Such developments in NLP like BERT are undoubtedly beneficial for a wider tech community. As a software testing specialist firm, Exactpro sees the application of this and other recently emerged approaches to quality assurance and their further enhancement as a strategically important activity. We already use various NLP methods in our work with complex mission-critical financial platforms. One direction of this work covers using AI in testing activities and includes, among others, log analysis for system monitoring, process mining for test coverage improvement, and test execution failures analysis for root cause predictions. Another direction is quality assurance of such AI-based systems as conversational assistants and machine-readable news. These systems are very often built using machine learning models, and we are adjusting our test approach to their verification and validation.

Some of these thoughts are featured in Waters Technology’s AI deep dive by Joanna Wright giving an overview of the recent NLP research applied to financial technology.

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Exactpro on MiFID Best Execution Reports

The lack of clear regulatory guidance by national regulators across the EU on regulatory technical standard (RTS) 27 has led to uncertainties on the directive’s best execution obligations. RTS 27 requires firms to provide best execution reports, free of charge and downloadable in a machine-readable format. Read the full IFLR Practice Insight articles, including comments from Exactpro’s co-CEO and co-founder Iosif Itkin...

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Outsourcing Software Testing Services: Yea or Nay?

What are the pros and cons of outsourcing Quality Assurance (QA) processes in fintech? What industry-specific factors hinder the delegation of critical functions? Do large-scale infrastructures still resort to third-party services providers despite the hurdles? What level of quality control is expected from independent QA vendors? Learn more about the importance of independent software testing from Exactpro’s latest article published by A-Team Insight’s TradingTech Insight at https://a-teaminsight.com/are-companies-right-to-outsource-software-testing/

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Exactpro CEO on Why Checkbox Testing Decreases System Resiliency

Exactpro CEO sat down with FOW’s Luisa Chender to talk about how the checkbox testing approach to software quality assurance can give financial markets firms false hope about the resiliency of their systems.

How exactly does checkbox testing manifest itself? Why does it prove ineffective time and again? Why is the issue all the more pronounced in post trade? And what is a more reliable approach? Read the full article at https://www.globalinvestorgroup.com/articles/3692633/box-ticking-leaves-firms-unprepared-for-tech-failures

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Exactpro On the Current State of DLT in Fintech

More and more firms take up distributed ledger technology (DLT) initiatives and make steady progress on DLT migration. What is the extent of blockchain implementation in fintech? How do the cutting-edge technologies fit in with the existing infrastructure? What are the telltale signs of vast blockchain acceptance, and are they currently at the fore throughout the industry? Read the full interview with Iosif Itkin, CEO and co-founder of Exactpro at https://www.coindesk.com/exactpro-dlt-post-trade-software-testing

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