Three Capabilities Banks Need to Work On While Adopting Open Source
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As banks are now willing to experiment and adopt new age technologies such as artificial intelligence and blockchain, the next big step of its digital disruption has to do with open source banking.
With the adoption of open source, banks are likely to open their APIs and share customer data with third-party players to develop innovative products and offer customized real-time bespoke services to customers.
Industry experts consider it to be the best time to embrace open banking as customer buying patterns are changing.
In a previous interaction with Entrepreneur India, Rajeev Ahuja, Executive Director, RBL Bank accredited this change to “the emergence of nontraditional competition such as fintech startups, growing domination of technologies like blockchain, artificial intelligences, machine learning, etc and lastly, the initiatives taken by the Reserve Bank Of India to regulated the payments banks, peer to peer lending platforms, linking of Aadhar, and e-kyc.”
Open banking is not just a hero amongst the big players but even small banks like Ujjivan SFB is keen to work around the platform.
“With the dynamic nature of the business, there is shifting need towards trying and experimenting. The mantra is to try fast and learn from failures,” says Ittira Davis, Chief Operating Officer, Ujjivan SFB while adding that, “Open source allows this experimentation and also allows a lower cost of ownership. Ujjivan as part of its mandate is exploring new age technology and open source primarily on domains like analytics.”
Presently, there are around 4-5 platform banking models available such as the proprietary platform (one sponsor and one provider), licensing platform (one sponsor, many providers), joint venture platform (many sponsors, one provider), and shared platform (many sponsors, many providers).
While every model has it’s own advantages and disadvantages, once the bank chooses to adopt one of it, there will be a shift in the process of resource deployment.
Noting the change, in a recent report – A New Era Open Banking Platform, Accenture identified some key capabilities which help the bank in its journey to adopt open source:
Banking leaders should avoid looking at open source as a digital drive and instead focus on programs of a holistic change which would have an impact on culture, system and even capabilities. Unlike traditional banking, open source adoption requires a lot of focused investment and more importantly planning and cross-bank coordination.
Furthermore, the bank needs to operate somewhat like a software company wherein your front office will act as a relationship manager for the clients. It also hints at the creation of new roles such as technologist, data scientist for the development of an innovative product line.
In other words, banks as an organization need to focus on being more agile along with robust failure management process while making a smarter decision.
Banks should remember at the end open source is all about improving customer experience which can only be achieved with customization, speed and ease of use.
And hence, banks need to act quickly to acquire deep capabilities in user experience. Therefore, machine learning here is the key – as its bridges the gap between data generation and data analysis.
They should also be in a position to support IT leaders with identity driven policy wherein they can plug and play on the platform to provide a seamless experience.
An open API is a bank product with versioning-based life-cycle and therefore, the organization must manage the life-cycle within its ecosystem.
“A new version of an API is effectively a new product for the bank’s customers and therefore, it should be designed with life-cycle management at its core. Each new version must ensure backwards compatibility until the end of the agreed lifecycle is reached,” the report added.
Additionally, the banks must remember the open API is fueled with core banking data and hence, adequate security measures should be adopted to secure and manage the data.