- 10.03.2020 04:15 am
- 05.02.2020 06:00 am
- 31.01.2020 04:30 am
- 28.01.2020 04:30 am
- 23.10.2019 07:45 am
If you think about it, financial services have traditionally been disconnected from their customers’ goals. For instance, when we want to buy a vehicle or house, or purchase inventory for a manufacturing process, we typically begin by researching and evaluating our options, then making a purchase decision. Only then do we look at the financial services necessary to complete the transaction.
But financial services companies today are already well on their way to changing this experience, and three technologies are key to this transformation: APIs, adaptive intelligence (AI)/machine learning, and blockchain. These key strategies involve leveraging large troughs of data so banks can become an integral part of the consumers’ journey, engaging intelligently with customers through contextual offers and advice, and connecting customers and the services they need.
The Integral Bank: becoming integral to customers’ lives by using APIs to embed the bank in every customer interaction
One key opportunity that financial services companies have with APIs is to bring the banking experience directly to the customer where a decision is happening with banking-as-a-service-enabled strategies. One example of this is a recent partnership announcement between Citi and big-tech Google. Using APIs to expose its banking services, Citi has enabled Google to offer these financial services as the customer is searching for services and offers on the web.
In the future, customers will be able to search for a vacation home or airline travel, and Google will be able to integrate seamless and contextual banking services into the customer flow. Then a bank like Citi will power the transactions, be it on-point lending or embedded payments, to complete transactions without users ever leaving their journey. By exposing their services so they can be embedded in customers’ daily experiences, banks can increase their reach and help provide contextual services to customers at the point of the transaction.
This example of delivering banking ubiquitously is now being explored by many leading banks who are opening up their banking services as APIs and embedding the bank experience directly where the user conducts everyday transactions, rather than the consumer having to come to the bank. This approach also enables banking to be distributed by third-party fintechs or big techs without needing to take on the regulatory burden of becoming a bank.
On the other side of the spectrum, banks can assemble third-party services that they typically don’t offer and, essentially, become a one-stop financial services shop for their customers through an approach called banking-as-a-platform. Starling Bank in the UK is an example of a bank using APIs to bring all these services together to deliver a seamless experience to its customers – an experience Starling calls the Marketplace. The bank describes the Marketplace as an “ecosystem of financial products” – both consumer and business customers can access a number of digital financial services through their Starling accounts, including mortgages, pension investment management, and homeowners’ insurance. A typical retail bank or credit union can achieve massive scale by implementing a platform approach and aggregating services in a seamless experience—eliminating the need for consumers to go to different institutions for different services.
The Intelligent Bank: leveraging data with adaptive intelligence (AI) to engage with customers through intelligence and to enable autonomous finance
Once all of the available data is aggregated through banking-as-a-service or banking-as-a-platform, banks can power personalized offers based on all the interactions customers have with the ecosystem partners through AI/ML-enabled engines that parse the data in real time and present highly contextual and relevant inline offers. This is the future of banking: contextual finance, where the bank is able to offer the right product at the right time in real time to the right person based on data that’s acquired from interactions customers have with the ecosystems or with a wider set of platform applications.
Banks are already rapidly moving to deliver highly tailored services to a segment of one by leveraging all the data available to them. For instance, AI is already being used to provide consumers with advice on how to use their money, how to budget well, and how to invest and achieve long term investment goals, all powered by intelligent agents. Self-driving finance enables banks to deliver proactive advice to their customers to empower them to take control of their financial well-being. This strategy boosts customer engagement and product adoption. Using Oracle Autonomous Cloud, fintech company Personetics is delivering “self-driving” or autonomous finance today to banks.
We’re also seeing AI and natural language processing (NLP) being used to drive conversational engines that can converse easily with customers in natural language; these engines have full awareness of context and can seamlessly adapt to deliver a human-like experience. Another example of a company that delivers natural conversational AI banking experience with fully pre-trained agents is Ipsoft . Their digital agent Amelia can cover mortgages, loans, onboarding, wealth management leveraging the autonomous cloud, big data and the Oracle open banking platform. Employment of digital labor improves customer experience, reduces time to resolution while continuously improving back office bank efficiencies.
Machine learning-based models are also now being used in underwriting to provide a holistic view of borrower risk based on alternative data. In the past, this would have taken weeks because publicly available data had to be collected from different sources and then aggregated for analysis. Now, it can be seamlessly synthesized in minutes to enable the risk teams to bring all the information together in concise, succinct bullet-size information to make credit decisions.
Using real-time payment information and a risk management system to analyze thousands of customer transaction variables, MYbank in China is now making small business lending decisions in fewer than three minutes. Borrowers apply with a few taps on a smartphone and, if they’re approved, receive cash almost instantly. There are no humans involved in the process, and the default rate is practically non-existent (1%).
The Connected Bank: connecting customers and their banking needs through blockchain
When dealing with global financial payments, inter-bank transfers, fraud detection, and loan processing, the processes have traditionally been slow. At the backend, the process requires banks to cooperate and connect seamlessly with other entities. Lack of transparency is also a major hurdle. With these hurdles, it might take days for banks to complete a transaction. But blockchain is changing this experience.
Arab Jordan Investment Bank (AJIB) is an excellent example of how blockchain can improve and speed processing. Before adopting blockchain, the bank’s money transfers required third-party intermediaries for cross-border transactions. Each intermediary charged a fee and required AJIB to share some customer information with those third parties, which involved strict regulation compliance.
With Oracle Blockchain, the bank is now able to make transfers in real time without the transaction fees that used to occur at every stage. Both senders and receivers can track the money transfers as they’re happening, providing information about the exact timing and amount of the transfer. This has resulted in tighter security, elimination of delays, and automated transactions without third-party interference.
Oracle Helps Facilitate the Future of Financial Services
Oracle is taking a leading role in building the future of banking with technologies that enable banks to become integral, intelligent, and connected to their customers’ lives: