Artificial Intelligence and Reflections on 4 Frontiers in Finance for 2020

Venky Srinivasan
Group Vice President-Sales, Asia Pacific, Japan, Middle East & Africa, Oracle Financial Services

The Singapore FinTech Festival (SFF) is always a top draw for business leaders and technologists every year. 2019 was no different, with more than 60,000 participants from 130 countries.

Right off the bat, the Monetary Authority of Singapore (MAS) chief, Ravi Menon, made it clear that Singapore had by no means arrived, and innovation is an ongoing process. He reiterated the primary purposes of financial technology were to “green” the world, making it more inclusive and dynamic.

DPM Heng Swee Keat sharing about Singapore's plan to put artificial intelligence (AI) at its forefront.

In cementing this idea, Singapore’s Deputy Prime Minister Heng Swee Keat outlined the country’s plan to put artificial intelligence (AI) at the forefront of the city-state's plans to transform almost every facet of Singapore’s economy, from finance and transport and logistics to healthcare and education, by 2030.

As prominent as AI adoption may be in the financial services sector compared to other industries, panel discussions agreed that most AI use cases apply to customer support and back-office functions. Nevertheless, an inflection point is on the horizon.

Financial crime uses data science toolkits to leverage machine learning for financial crime pattern detection. It also uses intelligent AI-powered analytical applications to connect outcomes autonomously and derive insights from data across business functions, platforms, and channels.

AI also allows banks to offer new global cash management propositions, thereby improving cash flow forecasting.

Open banking beckons

Open banking, mooted for years, and the crux of the matter is whether FinTech companies are trusted as much as banks. A recent survey showed that three in five Singaporeans believe FinTech companies are as trustworthy as banks. Around 13 percent feel these companies deserve more trust than financial institutions. While these numbers may vary from survey to survey, open banking appears to rely on the premise that only ecosystem partners of the two groups will survive the coming storm.

While big tech companies are not scrutinized to the extent that banks are, regulators are re-thinking their rules of engagement. The first phase of open banking is based on payment data for underlying transactions. But this will evolve as customers start consenting to open data sharing.

Discussions at SFF 2019 revolved around the importance of a level-playing field to accelerate FinTech innovation. The overview is that banks are finding themselves obligated to open their data to FinTech companies. In contrast, big tech giants aren't necessarily as open in sharing their data. “Over the next five years, we will see a financial services industry and a customer experience journey which is even more evolved than it has been the last five,” said Piyush Gupta, CEO, and Director of DBS Group.

Discussion on 2020: Banking in a New Global Context, Moderated by Haslinda Amin, Chief International Correspondent Southeast Asia, Bloomberg. Panelists include Bill Winters, Group CE, Standard Chartered, Calvin Chol, CEO, AMTD Group, John Dugan, Chairman, Citigroup Inc, Noel Quinn, Group CE, HSBC, Piyush Gupta, CEO, DBS

Singapore has taken the bold step to provide a single platform for consumers to access their financial information from various accounts across various banks, insurance companies, and brokerages. The single platform is expected to be announced next year, and consumers will be expected to provide consent to sharing their consolidated financial data with banks as well as FinTech companies.

Payments and impact on banks and FinTech companies

The retail payments segment has taken off like a rocket, with more and more banks leveraging their process platforms to initiate payments for the customers’ benefit. 74% of retailers saw a rise in customer expectations in the past year alone. 

This trend is also gaining momentum in the corporate banking/payments space. While customers will ultimately have their way in terms of the above, they will also demand transparency and privacy of the processes. Regulators like the MAS have foreseen this and have introduced new policies to regulate payments. These policies are categorized by technology rather than the institutions that are involved in the payments process.  

Singapore has been working with more partners in ASEAN to standardize real-time payments to enable retail micropayments using mobile numbers on smartphones. This bodes well, especially for the tourism, small businesses, and the remittance sectors.

In terms of corporate banking payments, there are requirements to comply with Standardized Messaging and Processing Built grounds up with ISO 20022 & SWIFT GPI. This provides data standardization by creating more automation and straight-through processing via machine learning and blockchain. It also increases the traceability of payments throughout the cycle.

The next level of SME financing

SME financing has always been a recurring theme in many similar events. However, SME financing has evolved somewhat in the last few years. While domestic banks bear the burden of financing the bulk of our SMEs around the world, the use of AI, data analytics, reg-tech, and AML software has increased significantly.

By leveraging data, banks will be able to harness time efficiencies and deliver a much better end-to-end customer experience for SMEs. Beyond this, banks can become indispensable financial partners for SMEs by starting with having a better understanding of what keeps SMEs up at night.

Digitization, technology, talent retention, and market expansion are some of the prime focus areas for SMEs. It should come as no surprise that as many as 71% of SMEs are expected to adopt open banking by 2022. This is a strong indication that SMEs understand the usage of open APIs and its benefits.

Technology for a new generation of threats

Criminal behavior is ever-changing. Banks must rapidly evolve their traditional, costly, and cumbersome anti-financial crime programs towards advanced analytical technologies that can leverage and learn from big data. Companies with superior machine intelligence will operate more effectively and efficiently in terms of detecting financial crime, carry out investigations, and fulfill reporting requirements. Through machine learning-based analytical cloud applications, banks will be able to thwart increasingly sophisticated criminal activity.

There is now an increasing requirement for banks to deliver continuous compliance. And due to the ever-increasing complexity of the business, technology and regulatory landscape, digital banks will need to make inventive use of KYC, risk, and compliance data to gain useful business insight and protect their customers at the same time.

The monitoring of financial crime compliance throughout the entire customer financial lifecycle is crucial. Machine learning for analytical capabilities, robotic process automation (RPA) for workflows, and graph analytics for the visualization of networks are setting new industry standards. Besides, they are turning compliance into a competitive advantage for banks by enabling them to meet evolving regulations and detect suspicious financial activities. The use of AI in identifying high-impact, genuine alerts would also increase efficiency in focusing on significant threats rather than attempting to focus on every alert.

Challenges for the future

They say it takes a village to raise a child. By the same analogy, it will take the entire industry across the globe to stay relevant, which is what cross-border collaboration is all about. By sharing information on changing risks and climates of different locations, with all gears working in tandem from regulators to banks to FinTech companies, the industry may be able to make the transition to a new frontier in finance.

To learn more, feel free to message me to explore more, or have a conversation.

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