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Technology and banking law – disruptive innovations


Today, the segment is witnessing the progressive application of disruptive innovations, integrating the variables of intelligence and automation in the respective business models, aimed at improving activities and the customer experience.
The banking sector in recent years has experienced intense digitalization of its activities, from the services available electronically to mobile devices. Today, the segment is witnessing the progressive application of disruptive innovations, integrating the variables of intelligence and automation in the respective business models, aimed at improving activities and the customer experience.
In this space, disruptive innovations are associated with the transformation of the market promoted by the introduction of services and products supported by new technologies, as seen in fintechs, challenging what had been established until recently in this sector. Some examples of these innovations are: Artificial Intelligence (AI), analytics, blockchain, process automation and the essential reinforcement to cybersecurity.
AI and its functionalities mean to financial institutions in-depth knowledge about the expectations and experiences of customers and, consequently, the gaps of the business model based on the availability of significant volume of data in these organizations, such as scores, financial behavior, online transactions , withdrawals, among others, that contribute to the strategic decision-making process.
AI applications are observed in customer service management (service through virtual assistants with tools to monitor emotions in real time and offer personalized recommendations), risk management (granting credit and loans) and legal and regulatory compliance ( fraud prevention and detection, customer identification and authentication, prevention of criminal activities).
Survey [i] conducted in 2018 with 206 US executives working in the banking sector found the recurrent use of AI, detailing its applications in machine learning (forecasting cash flow events, advising customers on financial habits, developing scores credit, identification of fraudulent transactions); natural language processing (understanding of voice searches made by customers, detection of errors in documents, verification of information); deep learning (reading and classifying complaints, results of data analysis in a simple and intuitive format, creating investment strategies); and computer vision (biometric security, immersive experiences for investment portfolio allocations).
Among its benefits, there is a cost reduction estimated, in general, at approximately US $ 447 billion by 2023 [ii]. Of this amount, 44.5% from virtual interaction solutions, biometric technologies and personalized insights in the front office; 48.5% based on anti-fraud solutions, applicable to risk management and prevention of criminal activities in the middle office; and 7.0% supported by solutions aimed at credit underwriting and smart contract infrastructure in the back office.
Analytics and big data involve the detection of patterns and meanings in unstructured data from, by illustration, contracts, business plans and reports. It is intended, in effect, to examine non-financial factors, results of marketing campaigns, to understand the risk profiles of clients, to evaluate contracts. Elements that tend to gain more and more space due to the growth in the volume of data produced, which requires from the banking sector new means to store, classify and use this information.
The blockchain technology applied in this space has the potential to reduce infrastructure costs, disseminate the safe and reliable use of smart contracts, reducing interactions with intermediaries and contractors, improving data quality, providing efficiency and speed to transactions, improving cybersecurity , with fewer procedures essential for confirming authenticity.
There is an increasing tendency to accept this technology, observed, for example, in investments made in startups that develop blockchain-based solutions, which, according to PwC data [iii], went from US $ 16 million in 2011 to US $ 1, 6 billion in 2017.
Expert forecasts suggest that in the next three to five years [iv] there will be a significant increase in the volume of transactions and the consolidation of highly efficient blockchain platforms, which may include the transfer of digital or physical assets, protection of intellectual property and verification of the supply chain. custody.

Minimizing errors, improving customer relations, reducing costs and time linked to repetitive activities are the main purposes of process automation in financial institutions. It is applied, among other cases, to support billing of expenses with suppliers, checking adherence to the rules and regulations applicable to the sector, verification of customer data, credit approval, service through virtual assistants and identification of fraud patterns.
The expansion of these disruptive innovations, together with the use of more sophisticated and complex technologies, of mobile devices by customers, third-party networks and the connectivity of devices in the context of the Internet of Things are elements that express the concern with cyber risks in the banking sector. Thus, it is an indispensable aspect to take advantage of the opportunities brought by the application of innovations.

Currently available technological resources can contribute to the identification of anomalies, the detection of fraud, the blocking of attacks and the creation of secure communication channels. However, it is necessary to reinforce cyber risk management based on a continuous governance program, listing of threats, collaboration between all areas of the organization and an operations model capable of limiting service interruptions or financial losses through the identification of threats and quick responses to any security incidents.
The analysis of this scenario leads to the conclusion that these innovations will allow, according to their specificities, gains in efficiency and safety for financial services, reduction of time dedicated to repetitive tasks, risk mitigation, assertive forecasting of customers’ needs, increasing the satisfaction of those with the services delivered, in addition to expanding the added value delivered to interested parties.
Therefore, the banking sector needs to be aware of the consolidation of technological advances, adjusting models of Information and Communication Technology, reducing costs with legacy systems when adopting innovations, observing customer needs, expanding connectivity and 24/7 availability of transactions , adopt effective cyber risk management and, mainly, integrate disruptive innovations with the strategic objectives of organizations.

By: Wilson Sales Belchior

[i] Available at: <https: //www2.deloitte.com/us/en/insights/industry/financial-services/art ….
[ii] Available at: <https://www.businessinsider.com/ai-in-banking-report>.
[iii] Available at: <https: //www.pwc.com/il/he/bankim/assets/2018/Top%20financial%20services% ….
[iv] Available at: <https: //www.pwc.com/gx/en/financial-services/assets/pdf/technology2020-a ….


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