Companies across industries are realising the business use cases of blockchain (distributed ledger technology or DLT), which is evident from the increased funding trends for this technology.
Source: PwC analysis of data from 1 June 2012 to 9 November 20177
As per PwC’s Global FinTech survey 2017, the most likely business cases of blockchain, according to 55% of the respondents, are payments infrastructure, followed by fund transfer infrastructure (50%), and digital identity management (46%). 8In India, the most notable use cases of blockchain technology have been POCs for cross-border remittances, trade finance and vendor financing.
Blockchain can play a major role in streamlining the entire KYC process of organisations. A centralised identity platform has real benefits in terms of making the KYC process more efficient, economical, indisputable and secure. This use case can also be extended to other forms of document management and authentication, especially in processes requiring large amounts of verification, including underwriting processes. Due to its low transaction costs and reduced settlement time, blockchain can also help create new business models based on micropayments in segments such as savings, loans, insurance and investment.
Other blockchain applications such as smart contracts are bound to see increased adoption in the future. These smart contracts automate the exchange and finalisation of complex agreements such as mortgages, derivatives, insurance policies and letters of credit, where all parties validate the outcome instantaneously.
Blockchain could be used with other advanced methods, tools, and technologies to improve information security and predict, detect and analyse frauds. A unified infrastructure with all related parties on board could help avoid events like the recent bank guarantee/letter of undertaking (LOU) related frauds.
Robotic process automation (RPA) technologies have found application in a number of internal FS processes, and FS firms have started to transition RPA options from experimental and exploratory exercises to relevant mainstream processes. PwC’s 2017 Financial Services RPA Survey highlights the growing acceptance of RPA and its applications across FS areas:9
While RPA technologies are capable of taking on low-value activities in a quick and efficient manner, the next phase is leveraging artificial intelligence to deliver intelligent process automation (IPA). IPA technologies will allow bots to not only automate standard processes, but also learn from prior decisions, deviations and patterns to improve decisions, thus further reducing the need for human oversight and increasing efficiency gains in internal processes. The combination of these capabilities with other relevant technologies such as optical character recognition (OCR) and NLP could lead to a completely new digital back office.
Combining IPA and OCR technologies has helped insurance firms streamline and automate their claims processes. Asset management firms are using IPA along with NLP to automate portfolio commentary communication to customers, and a number of banks are using intelligent automation to streamline and improve transaction processing.
7PwC. (2017). Blockchain in financial services. Retrieved from https://www.pwc.com/us/en/industries/financial-services/research-institute/top-issues/blockchain.html (last accessed on 9 May 2018)
8PwC. (2017). Global FinTech Report 2017. Retrieved from https://www.pwc.com/jg/en/publications/pwc-global-fintech-report-17.3.17-final.pdf (last accessed on 9 May 2018)
9PwC. (2017). 2017 Financial Services RPA Survey. Retrieved from https://www.pwc.com/us/en/industries/financial-services/library/2017-rpa-survey.html (last accessed on 9 May 2018)
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