The disrupted becomes the disruptor
23 Oct 2018
Philippe Ruault, head of digital transformatin at BNP Paribas, explains how asset servicers are becoming the disruptors
Image: Shutterstock
Asset servicing clients want more and better for less and faster, putting pressure on providers who sometimes rely on historic systems and manual interfaces. The increased demands from clients also expose incumbents to disintermediation from start-ups, big-techs—the so-called FAANGs otherwise known as Facebook, Apple, Amazon, Netflix and Google—and dynamic competitors who are developing products that are more applicable and in step with (often younger) customer expectations. If asset servicers want to retain client loyalty and deflect disintermediation, they must pursue a disruptive strategy.
Asset servicers take to DLT
Embedding distributed ledger technology (DLT) into business processes will be a major enabler behind the future success of asset servicing and its product delivery. DLT introduces a number of operational and cost benefits for users, as its immutability facilitates superior transparency, greater security and reduced error counts. The technology, therefore, has the potential to refresh many core activities in securities services such as clearing, settlement, collateral management, corporate actions and fund distribution.
BNP Paribas Securities Services is beta-testing a number of DLT applications, as part of our digital transformation and commitment to continuously improve client experience.
The PlanetFunds programme is striving to generate efficiencies in fund distribution, reducing the need for human intervention and cutting cost. By using blockchain and smart contracts to streamline the flow of information between fund buyers and sellers, BNP Paribas hopes to deliver an enhanced customer experience from the on-boarding of investors to smart analytics on their buying behaviour. The technology will also improve the actual mechanics of buying and selling funds through its end-to-end execution facility, reducing reconciliation costs and delays in the distribution chain. Through implanted analytics, PlanetFunds will help investors comb through fund data prior to selection while helping managers to fine-tune their distribution channels.
In addition to distribution, providers are also using DLT to augment post-trade activities. BNP Paribas plays a leading role in an industry consortium which is supporting the launch of LiquidShare, a financial technology start-up which provides a DLT infrastructure for small-to-medium-sized enterprises (SMEs). The technology will streamline post-trade processing for SMEs, not least through enabling T+0 settlement and consolidating securities registers in what should help these companies obtain easier access to capital markets.
Blockchain is being incubated and developed at large market infrastructures too, most notably Australian Securities Exchange (ASX). ASX is leveraging digital asset holdings to replace its post-trade Clearing House Sub-Register System (CHESS) platform for cash equities with DLT.
This milestone is expected to be reached in 2020/2021. If the ambitious scheme nets tangible benefits, more infrastructures will follow Australia’s lead.
However, incorporating DLT into financial markets is a huge project, and many obstacles will need to be tackled along the way, namely acquiring regulatory buy-in; averting market-wide fragmentation; ensuring interoperability; minimising the technology’s carbon footprint; and identifying where DLT adds value, something which may require firms to become more selective about the type of data they store on DLT. Ultimately, the providers which have a serious DLT strategy will be the ones at a competitive advantage moving ahead.
Artificial intelligence: taking asset servicing to the next level
While widespread automation has generated efficiencies in asset servicing, the adoption of artificial intelligence (AI) and robotics will bring about unprecedented change. A report by McKinsey said that securities services could net $20 billion in savings if automation and robotics are applied at scale across the industry. BNP Paribas sees AI as a critical tool in the industry’s future development, and we are implementing a number of initiatives around the technology.
Robotic process automation (RPA) can help remove manual intervention, and it is being steadily adopted by banks and fund managers globally. The natural language generation (NGL) is already automating the production of client and regulatory reports, thereby helping to optimise costs and condense the overall time spent on these activities. BNP Paribas is also using this technology in its management information system reports for clients.
In addition, we are accelerating our natural language processing (NLP) capabilities, a subset of AI which uses computers to understand and aggregate structured and unstructured data including non-digital documents such as faxes generating language off the back of it—in effect mimicking human functions. In conjunction with Fortia, BNP Paribas is using NLP tools to assist fund managers with their compliance requirements. These tools comb through documents, such as prospectuses, extract data, then flag potential breaches, in real-time—an advancement which will create significant efficiencies for users.
Client experiences and communications will be transformed too through the roll-out of cognitive, machine learning chatbots, which can field rudimentary enquiries from customers, but as the technology onboards more information, they will eventually be able to respond to more complex requests.
AI can help asset servicers support clients through predictive analytics by scrubbing data to identify patterns and trends, allowing banks to warn clients proactively about potential risks.
BNP Paribas is already trialling this technology, Smart Chaser, a trade matching tool, which not only boosts automation but can analyse historic data to identify patterns in trades that have previously required manual intervention. Smart Chaser, which has a 98 percent prediction accuracy rate, will immediately alert clients about their live trading activities so action can be taken. However, AI does have some hurdles to clear. Validating that the data being supplied to AI technology is not riddled with errors is pivotal, otherwise, the AI analytics could be distorted leading to the spread of misinformation.
The biggest priority at providers utilising AI is to corroborate that data has been obtained and used in a way that complies with the European Union’s General Data Protection Regulation (GDPR). GDPR breaches come with harsh penalties so data mining must be done carefully and sensitively.
Survival of the technologists
Just as countless other industries have been forced to change, so too will banking. Asset servicing—as it is known today—will evolve dramatically over the next five to 10 years. Firms which adopt and integrate technology thoughtfully into their product offerings will be the provider’s customers of the future turn to.
Custodians that fail to embrace reform are likely to be punished, and eventually forgotten about.
Asset servicers take to DLT
Embedding distributed ledger technology (DLT) into business processes will be a major enabler behind the future success of asset servicing and its product delivery. DLT introduces a number of operational and cost benefits for users, as its immutability facilitates superior transparency, greater security and reduced error counts. The technology, therefore, has the potential to refresh many core activities in securities services such as clearing, settlement, collateral management, corporate actions and fund distribution.
BNP Paribas Securities Services is beta-testing a number of DLT applications, as part of our digital transformation and commitment to continuously improve client experience.
The PlanetFunds programme is striving to generate efficiencies in fund distribution, reducing the need for human intervention and cutting cost. By using blockchain and smart contracts to streamline the flow of information between fund buyers and sellers, BNP Paribas hopes to deliver an enhanced customer experience from the on-boarding of investors to smart analytics on their buying behaviour. The technology will also improve the actual mechanics of buying and selling funds through its end-to-end execution facility, reducing reconciliation costs and delays in the distribution chain. Through implanted analytics, PlanetFunds will help investors comb through fund data prior to selection while helping managers to fine-tune their distribution channels.
In addition to distribution, providers are also using DLT to augment post-trade activities. BNP Paribas plays a leading role in an industry consortium which is supporting the launch of LiquidShare, a financial technology start-up which provides a DLT infrastructure for small-to-medium-sized enterprises (SMEs). The technology will streamline post-trade processing for SMEs, not least through enabling T+0 settlement and consolidating securities registers in what should help these companies obtain easier access to capital markets.
Blockchain is being incubated and developed at large market infrastructures too, most notably Australian Securities Exchange (ASX). ASX is leveraging digital asset holdings to replace its post-trade Clearing House Sub-Register System (CHESS) platform for cash equities with DLT.
This milestone is expected to be reached in 2020/2021. If the ambitious scheme nets tangible benefits, more infrastructures will follow Australia’s lead.
However, incorporating DLT into financial markets is a huge project, and many obstacles will need to be tackled along the way, namely acquiring regulatory buy-in; averting market-wide fragmentation; ensuring interoperability; minimising the technology’s carbon footprint; and identifying where DLT adds value, something which may require firms to become more selective about the type of data they store on DLT. Ultimately, the providers which have a serious DLT strategy will be the ones at a competitive advantage moving ahead.
Artificial intelligence: taking asset servicing to the next level
While widespread automation has generated efficiencies in asset servicing, the adoption of artificial intelligence (AI) and robotics will bring about unprecedented change. A report by McKinsey said that securities services could net $20 billion in savings if automation and robotics are applied at scale across the industry. BNP Paribas sees AI as a critical tool in the industry’s future development, and we are implementing a number of initiatives around the technology.
Robotic process automation (RPA) can help remove manual intervention, and it is being steadily adopted by banks and fund managers globally. The natural language generation (NGL) is already automating the production of client and regulatory reports, thereby helping to optimise costs and condense the overall time spent on these activities. BNP Paribas is also using this technology in its management information system reports for clients.
In addition, we are accelerating our natural language processing (NLP) capabilities, a subset of AI which uses computers to understand and aggregate structured and unstructured data including non-digital documents such as faxes generating language off the back of it—in effect mimicking human functions. In conjunction with Fortia, BNP Paribas is using NLP tools to assist fund managers with their compliance requirements. These tools comb through documents, such as prospectuses, extract data, then flag potential breaches, in real-time—an advancement which will create significant efficiencies for users.
Client experiences and communications will be transformed too through the roll-out of cognitive, machine learning chatbots, which can field rudimentary enquiries from customers, but as the technology onboards more information, they will eventually be able to respond to more complex requests.
AI can help asset servicers support clients through predictive analytics by scrubbing data to identify patterns and trends, allowing banks to warn clients proactively about potential risks.
BNP Paribas is already trialling this technology, Smart Chaser, a trade matching tool, which not only boosts automation but can analyse historic data to identify patterns in trades that have previously required manual intervention. Smart Chaser, which has a 98 percent prediction accuracy rate, will immediately alert clients about their live trading activities so action can be taken. However, AI does have some hurdles to clear. Validating that the data being supplied to AI technology is not riddled with errors is pivotal, otherwise, the AI analytics could be distorted leading to the spread of misinformation.
The biggest priority at providers utilising AI is to corroborate that data has been obtained and used in a way that complies with the European Union’s General Data Protection Regulation (GDPR). GDPR breaches come with harsh penalties so data mining must be done carefully and sensitively.
Survival of the technologists
Just as countless other industries have been forced to change, so too will banking. Asset servicing—as it is known today—will evolve dramatically over the next five to 10 years. Firms which adopt and integrate technology thoughtfully into their product offerings will be the provider’s customers of the future turn to.
Custodians that fail to embrace reform are likely to be punished, and eventually forgotten about.
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