The Monetary Authority of Singapore (MAS) and the Bank of Thailand (BOT) launched the linkage of Singapore’s PayNow and Thailand’s PromptPay real time retail payment systems. MAS said that it is the first of its kind globally.
The linkage is the culmination of several years of extensive collaboration between MAS and BOT, both countries’ payment system operators, bankers’ associations, and participating banks.
Customers of participating banks in Singapore and Thailand will be able to transfer funds of up to S$ 1,000 or THB 25,000 daily across the two countries, using just a mobile number.
There will be no need for details such as the recipient’s full name and bank account details, as with normal remittance solutions.
The funds will flow seamlessly and securely between customers’ accounts in Singapore and Thailand.
The experience will be similar to how domestic PayNow and PromptPay transfers are made today, in which senders can use their mobile banking or payment applications to initiate fund transfers instantly and securely, at any time of the day.
The transfers will be completed within a matter of minutes, representing a marked improvement over the average of 1-2 working days needed by most cross-border remittance solutions.
The participating banks have committed to benchmark their fees against the market. The fees will be affordably priced and transparently displayed to senders prior to confirming their transfers.
Senders will also be able to view the applicable foreign exchange charges prior to sending their funds, with these rates benchmarked closely to prevailing market rates.
The PayNow-PromptPay linkage is a key collaboration under ASEAN Payment Connectivity that was initiated in 2019, and closely aligns with efforts by the G20, Financial Stability Board, and other international standard-setting bodies to facilitate faster, cheaper, more inclusive and more transparent cross-border payment arrangements.
MAS and BOT will progressively scale the PayNow-PromptPay linkage to include more participants and extend the transfer limits to facilitate business transactions.
Ravi Menon, Managing Director of MAS, said,
“The PayNow-PromptPay linkage is only the beginning. MAS’ shared objective with BOT is to work with our ASEAN counterparts to expand this bilateral linkage into a network of linked retail payment systems across ASEAN.
With the rise of the digital economy, we want to empower individuals and businesses in the region with simple, swift and secure cross-border payments through just a few clicks on their mobile phones.”
Dr Sethaput Suthiwartnarueput, Governor of BOT, said,
“With the success of PromptPay, our domestic payment system, we have sought to enhance cross-border linkages with ASEAN and other countries and have launched our QR cross-border payment connectivity with Japan, Lao PDR, Cambodia and Vietnam.
Today’s PayNow-PromptPay linkage represents another key milestone in our digital payments journey.”
KeyBank ramps up RPA ops
Improved data quality and cost savings have spurred KeyBank to roll out robotic process automation (RPA) in its frontline, back office and technology operations recently. KeyBank first implemented RPA solutions via the cloud-native, web-based and AI-infused Automation Anywhere platform in 2018, said Dominic Cugini, chief information officer of service digitization at the $170 billion KeyBank, […]
Is Smart Data Fabric the Approach Financial Institutions Have Been Dreaming About?
This is a sponsored post in collaboration with InterSystems, Gold Sponsors of FinovateSpring, and Monica Summerville, head of capital markets, Celent, a division of Oliver Wyman.
Financial institutions and data have had a love-hate relationship for many years.
On the one hand FIs and data are a match made in heaven. It is a symbiotic relationship where business functions create and consume data over and over until the result exceeds the sum of the parts. Ideally this partnering results in revenue or alpha-producing insights. On the other hand, siloed, unreliable or simply too much data creates frustration and risk as the business potential is teased, but ultimately unattainable as FIs struggle to extract value from their data (see figure 1).
Business use cases for leveraging data across financial services are plentiful, from management reporting, enterprise risk, liquidity and treasury management, and more recently, driving innovative customer experiences. More specifically within capital markets and banking, trends such as the embracing of multi-asset trading or the desire to simplify architectures have triggered a rethink of data approaches. There is also, now more than ever, the desire for cost savings – equally important to FIs whose margins are increasingly coming under pressure from increased regulation and competitive factors. Indeed, research by Oliver Wyman and Morgan Stanley found that the benefits from having clean, consistent, and automated data management could be a two-to-four percent reduction of infrastructure and control costs. When IT spend ranges into the billions of dollars, as is the case with larger FIs, every percentage point of savings is a big win.
No wonder then that cracking the data management challenge has long been considered the perfect marriage of technology achievement and business function. FIs have made repeated attempts and invested hundreds of millions of dollars through the years to get this right. From simple relational databases storing structured data, to data warehouses and more recently data lakes capable of holding all types of data, there has been no shortage of excitement that maybe (whisper it) this latest approach could be “the one.” Heartbreaks inevitably followed as the heady days of getting to know new technologies turn into frustrations and recriminations. A pristine data lake becomes a swamp.
The latest research by Celent discovered that leading FIs including Bank of America, Citi, Goldman Sachs, JP Morgan and RBC, to name a few, have lately been getting serious with a new data management approach called Smart Data Fabric. As these entities move from a process- to platform-driven organisation, their business focus has shifted to ensuring the best customer experience possible. This shift however requires mastering and leveraging data to generate insights at an enterprise level. The reality is that a history of disjointed business expansion common to financial services, means data is siloed across numerous platforms, tuned for very different use cases. There are multiple “single sources of truth,” and these vary depending on whose truth you are seeking.
The right data management approach should empower FIs to become better versions of themselves, without fundamentally changing who they are. Unlike previous data management architectures, Smart Data Fabrics offer centralized access and a single unified view of data across the organization. Crucially, Data Fabrics do not require that copies of the data be created and stored outside its original location, so can offer a useful bridging solution between modern and legacy systems – the latter often holding the most business crucial data. In this way Data Fabrics can also avoid the creation of more data silos, which is especially important as FIs increasingly embrace cloud. A Data Fabric becomes “Smart” when it inherently supports advanced data analytics and aims to future-proof data management (see Figure 2).
Financial institutions, from asset managers to banks and brokers, have always known that they need to become smarter about data. Business end-users and clients are demanding better user experiences, targeted insights, and increased access to analytic capabilities which requires free access to accurate and harmonized data drawn from disparate sources across the entire enterprise. At the very core of modernization is the ability to innovate at scale, and this relies on freer access to data. Celent’s latest research report sponsored by InterSystems found that the business necessities and benefits of better data management is driving adoption of Smart Data Fabrics. This time it might just be for real. Read the full report here >>
EML & Fupay join forces to launch Europe’s first responsible BNPL-as-a-service product attached to a virtual card
EML Payments Limited (ASX: EML) (S&P/ASX 200) continues its evolution as one of the world’s most diversified payments and digital banking enablers. EML powers Fupay’s cash flow management and millennial credit product in Australia. Now, EML is moving to the next level and partnering with Fupay to take their combined technology to Europe to offer businesses a cutting-edge white-label BNPLaaS solution.
Fupay’s millennial focussed money management platform uses Open Banking data to provide smart cash flow forecasting, actionable insights, responsible BNPL ‘smoothing’ and engaging spend benefits designed to help users make every penny count. At the heart of it all is Fupay’s proprietary spending and lending engine, which is well-positioned to address the ever-growing consumer and regulatory demand for a better and safer short term lending option.
EML & Fupay are passionate about driving a more responsible & affordable BNPL experience with their combined capabilities:
- Low touch e-identity verification and affordability assessment.
- Personalised and flexible payment options based on the user’s cash flow.
- Real-time virtual card and payment options available in one app.
- Rich AI-driven data insights with high impact visualisation options to help make money management easy for consumers.
Michael Fredericks, Managing Director & Founder at Fupay, stated: ”When we started Fupay, we predicted the need to address the challenges faced by millennials meeting lifestyle costs, including a responsible millennial credit solution. We’ve focussed on addressing the solution rather than focussing on selling a thin BNPL product as quickly as possible. There’s a clear need for BNPL organisations to do more to ensure their customers can afford to repay credit extended to them and be more accountable for their customers’ financial safety. We’ve seen a growing appetite from customers and regulatory bodies to see real responsibility, and Fupay is championing this mature approach to trending payments tech alongside EML.”
Sarah Bowles, Group Chief Product Officer at EML, commented: ”EML’s thrilled to expand our connection with Fupay beyond Australia into a true growth collaboration. Our exciting new venture brings together EML’s virtual card, A2A payments, the newest Open Banking products and Fupay’s best-in-class cash flow and millennial credit product to create a market-leading white-label offering. We’re impressed with Fupay’s groundbreaking platform and see the absolute need for this type of solution to enable merchants and enterprises to deliver an exceptional user experience without needing to become payment experts.”
How Big Data impacts the finance and banking industries
Nowadays, terms like ‘Data Analytics,’ ‘Data Visualization,’ and ‘Big Data’ have become quite popular. These terms are fundamentally tied preidominantly to matters involving digital transformation as well as growth in companies. In this modern age, each business entity is driven by data. Data analytics are now very crucial whenever there is a decision-making process involved.
Through this tool, gaining better insight has become much easier now. It doesn’t matter whether the decision being considered has huge or minimal impact; businesses have to ensure they can access the right data to move forward. Typically, this approach is essential, especially for the banking and finance sector in today’s world.
The Role of Big Data
Financial institutions such as banks have to adhere to such a practice, especially when laying the foundation for back-test trading strategies. They have to utilize Big Data to its full potential to stay in line with their specific security protocols and requirements. Banking institutions actively use the data within their reach in a bid to keep their customers happy. By doing so, these institutions can limit fraud cases and prevent any complications in the future.
Some prominent banking institutions have gone the extra mile and introduced software to analyze every document while recording any crucial information that these documents may carry. Right now, Big Data tools are continuously being incorporated in the finance and banking sector.
Through this development, numerous significant strides are being made, especially in the realm of banking. Big Data is taking a crucial role, especially in streamlining financial services everywhere in the world today. The value that Big Data brings with it is unrivaled, and, in this article, we will see how this brings forth positive results in the banking and finance world.
The Underlying Concept
A 2013 survey conducted by the IBM’s Institute of Business Value and the University of Oxford showed that 71% of the financial service firms had already adopted analytics and big data. Financial and banking industries worldwide are now exploring new and intriguing techniques through which they can smoothly incorporate big data analytics in their systems for optimal results.
Big data has numerous perks relating to the financial and banking industries. With the ever-changing nature of digital tech, information has become crucial, and these sectors are working diligently to take up and adjust to this transformation. There is significant competition in the industry, and emerging tactics and strategies must be accepted to survive the market competition. Using big data, firms can boost the quality and standards of their services.
Perks Associated with Big Data
Analytics and big data play a critical role when it comes to the financial industry. Firms are currently developing efficient strategies that can woo and retain clients. Financial and banking corporations are learning how to balance Big Data with their services to boost profits and sales. Banks have improved their current data trends and automated routine tasks. Here are a few of the advantages of Big Data in the banking and financial industry:
Improvement in risk management operations
Big Data can efficiently enhance the ways firms utilize predictive models in the risk management discipline. It improves the response timeline in the system and consequently boosts efficiency. Big Data provides financial and banking organizations with better risk coverage. Thanks to automation, the process has become more efficient.Through Big Data, groups concerned with risk management offer accurate intelligence insights linked to risk management.
Engaging the Workforce
Among the most significant perks of Big Data in banking firms is worker engagement. The working experience in the organization is considerably better. Nonetheless, companies and banks that handle financial services need to realize that Big Data must be appropriately implemented. It can come in handy when tracking, analyzing, and sharing metrics connected with employee performance. Big Data aids financial and banking service firms in identifying the top performers in the corporation.
Client Data Accessibility
Companies can find out more regarding their clients through Big Data. Excellent customer service implies outstanding employee performance. Aside from designing numerous tech solutions, data professionals will assist the firm set performance indicators in a project. It will aid in injective analytic expertise in multiple organizational areas. Whenever there is a better process, the work processes are streamlined. The banking and financial firms can leverage improved insights and knowledge of customer service and operational needs.
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