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“Responding to open banking is a non-negotiable.”  David Lindberg, CEO of the UK Retail Bank If we see the trend over the last few years, a silent player in the data game, application programming interface (APIs) has been working to revolutionize how two systems can interact securely with each other. The increase in cloud adoption and increased network bandwidth has made it more relevant than before (I know that Postman and its valuation came to your mind!) Banking is as old a concept as trade and today we interact with APIs on a daily basis, knowingly or unknowingly. Open Banking is a framework which is built entirely on the foundation of APIs and it has the potential to transform the way we deal with banking services today. We chose to talk about open banking in this article as 74% of financial institutions see data analytics as the most relevant technology to invest in (source: PwC Global FinTech Report). The Indian market is currently geared to open up new opportunities for ML & AI use cases with the neo bank market valued at approximately $500Mn and expected to reach $15,000 million by 2027.  Our learners also read: Python online course free! If we want to evaluate the success of the open banking framework, we should study the use case of Plaid, established in 2012. Visa recently paid $5.3Bn to acquire the company which facilitates connecting financial apps to the banks, that presents a big number. So is Plaid’s empire which interacts with more than 2,500 digital finance products today and with more than 10,000 developers building on the Plaid platform at present. To answer the question whether the opportunity is lucrative enough or not, let’s glance at a few numbers from the UK market, which essentially initiated the Open Banking revolution. 7.2bn Euros 71% 64% Expected revenue opportunity to be created by Open Banking by 2022 of  SMEs expected to adopt it by 2022 of adults expected to be adopters by 2022 Source What is Open Banking essentially? Open banking is a framework where banks and other institutions open up customer data and facilitate transactions using APIs which enables third party organizations to build new apps and services. The following diagram clearly talks about the different entities in the Open Banking framework and how APIs follow a consent based architecture which puts customer as a authorizing authority unlike credit bureaus where the data can be fetched without any user authorization: Potential Business Use Cases for Open Banking Platforms Access to user transaction data and feasibility of interacting with core banking systems, enables financial apps to build smarter use cases related to everything money. The following table summarizes a few of such use cases. Entity Description Example use cases Personal Finance Advisor Uplifting users towards better savings and investments Prompting user to stop spending once it crosses a certain threshold Creating spending pots with limits (e.g., Restrict your food spends to 5,000 Rupees) Rounding off kitty (e.g., you are trying to make a payment of $995, it will make a deduction of $5 and save it) Suggesting the best payment mode based on the cards/ accounts you have Financial Inclusion Giving access to financial services to those who were not able to access it before Utilizing digital banks to reach out to the farthest of geographies providing full banking services Utilizing data from multiple alternate sources to score and underwrite an underserved segment Enhanced Processes Automation and integration of intelligent processes Automatic identity verification and management services Validation of income, debt and recurring payments in a loan journey Fraud prevention using already verified information over an API Aggregated view of customer’s financials across different financial relationships Ease of use Customer need focussed products Aggregation of multiple bank accounts at a single place Easy reconciliation and tracking Merging Debit, Credit & Forex cards into one   Read our popular Data Science Articles Data Science Career Path: A Comprehensive Career Guide Data Science Career Growth: The Future of Work is here Why is Data Science Important? 8 Ways Data Science Brings Value to the Business Relevance of Data Science for Managers The Ultimate Data Science Cheat Sheet Every Data Scientists Should Have Top 6 Reasons Why You Should Become a Data Scientist A Day in the Life of Data Scientist: What do they do? Myth Busted: Data Science doesn’t need Coding Business Intelligence vs Data Science: What are the differences? Fully Digital Banks  Fully digital banks are the entities which provide the entire suite of services which a typical bank provides but with a limited (or No) physical presence. RBI as a law doesn’t apply fully digital banking licenses today but startups like Jupiter, Neo, NiYo have figured a way out by partnering with already existing banks and building products using the APIs with the partner banks. Monzo, NuBank & Revolut are few names which one can not miss while talking about Open Banking or Neobanks. In fact, an estimated 40,000 people open a Monzo account every week. The following two graphs show the growth in terms of accounts for Monzo and Revolut. Source NuBank which was established in 2015 in Brazil has recently clocked more than 25M and valued at $10Bn – Added 42,000 new customers daily (Jan-March’20).  Read our popular Data Science Articles Data Science Career Path: A Comprehensive Career Guide Data Science Career Growth: The Future of Work is here Why is Data Science Important? 8 Ways Data Science Brings Value to the Business Relevance of Data Science for Managers The Ultimate Data Science Cheat Sheet Every Data Scientists Should Have Top 6 Reasons Why You Should Become a Data Scientist A Day in the Life of Data Scientist: What do they do? Myth Busted: Data Science doesn’t need Coding Business Intelligence vs Data Science: What are the differences? Interestingly, more than 80% of NuBank customers come through unpaid referrals. Top Data Science Skills to Learn SL. No Top Data Science Skills to Learn 1 Data Analysis Programs Inferential Statistics Programs 2 Hypothesis Testing Programs Logistic Regression Programs 3 Linear Regression Programs Linear Algebra for Analysis Programs Where does India stand in this open banking revolution? India may have joined the movement a bit later as compared to our western counterparts but we have built a very strong foundation for facilitating any API based ecosystem. Providing a digital identity to more than a billion people through Aadhaar was the first step which was followed by UPI, which is undoubtedly one of the most robust and secured payment solutions built over API framework. The following slide shows the growth of IndiaStack over the years: Source Today we have around 1.26 billion Indians registered on the Aadhaar database and apart from the central bank there are at least 50 companies which are leveraging UPI’s app for their own wallets. In June 2020, UPI has processed more than 1.3 billion financial transactions and currently the underlying tech is being revamped to support 1 billion UPI transactions per day. Source Coming to the core philosophy of open banking, Account Aggregator (AA) framework is the talk of the town in India. AA allows financial information users (e.g., Lending app) to access customers data (with consent) from financial information providers (e.g., SBI) for various services. Apart from banking, entities like GST, pension funds, insurance, mutual funds etc might also be a part of the framework. RBI has already given licenses across the categories and we might see adoption and uses in coming months. upGrad’s Exclusive Data Science Webinar for you – How upGrad helps for your Data Science Career? document.createElement('video'); https://cdn.upgrad.com/blog/alumni-talk-on-ds.mp4   What does it mean for us? With the adoption of these frameworks we will soon see new opportunities opening up in the field of ML, AI, cyber security and blockchain. With the changing face of the banking sector in India opening doors for newer opportunities, it is your turn now to make yourself ready for the future! References: [1] digifingroup.com [2] indiastack.org [3] PwC UK [4] PwC and Open Data Institute White Paper   Conclusion The structure of the Data Science Program designed to facilitate you in becoming a true talent in the field of Data Science, which makes it easier to bag the best employer in the market. If you are curious to learn about data science, check out IIIT-B & upGrad’s PG Diploma in Data Science which is created for working professionals and offers 10+ case studies & projects, practical hands-on workshops, mentorship with industry experts, 1-on-1 with industry mentors, 400+ hours of learning and job assistance with top firms. Learn Data Science Courses online at upGrad

by Mohit Bansal

10 Nov 2020