Commentary

Collaboration holds the key to unlock the pathways for traditional bank incumbents and technology entrants in the disrupted world of financial services, where disruptive companies can offer compelling alternatives to the huge customer base of unbanked and underserved across Southeast Asia.

The success of neobanks has raised challenges amongst the fintech industry. Providing a digital alternative to traditional banking, neobanks are, without a doubt, playing a key role in the evolution of banking.

Many large institutions and individuals are interested in the benefits that Security Token Offerings (STOs) could bring to Asia. These offerings give investors and companies alike a more formal and regulated framework for blockchain fundraising.

In the past 12 months, we witnessed a range of companies racing to qualify for a spot among Singapore’s first digital banks, mirroring what happened with Hong Kong’s virtual bank licenses the year before. The sense of urgency is understandable - the nature of what it means to be a bank is changing, and this shift is opening a gap in which newer operators can assert themselves. The importance of this is underscored by the fact that the Asia Pacific region has an astonishing share of the world's digitally native population; in markets like India, Vietnam and Thailand, it’s common to become "digitally banked" without having had a credit card – or even a bank account. While Asia Pacific is diverse in its financial systems, there are some unifying factors which are going to change the face of banking across the region.

Sustainable banking is getting momentum in developing countries and Bangladesh has been one step ahead now by initiating particular sustainable banking activities in various fields. The country has many success stories surrounding corporate governance, corporate social responsibility, social awareness of stakeholders, preparing sustainability reporting under globally accepted method-GRI (Global Reporting Initiative) and leadership with green banking being one of the most notable initiatives. In 2011, Bangladesh Bank (‘BB’), the regulatory authority of commercial banks in Bangladesh, issued “Policy Guidelines for Green Banking” to implement and promote green banking activities across the country in three phases.

As digital banking proliferates through the developed world, its adoption in emerging markets in Southeast Asia continues to lag. A McKinsey study in 2018 noted that whilst digital banking penetration has grown by as much as 300%in certain emerging Asian countries, the median level is only around 52%.

 

Understanding the intricacies of global best practices and adapting to it will set machine learning (ML) on a successful course; highly skilled accountants are vital to that process – including those in the banking industry.

Although growth is decelerating, the performance of Chinese banks has been resilient so far. Net profits of listed banks grew robustly in Q3 2019, higher than the same period in 2018. Such general improvement was also backed by a reduction in provisioning led by large banks. While the performance of large banks remained steady, the rebound came from small banks. The question really is why small banks have rebounded and whether it is sustainable. Thus, it is a good time to examine the recent financial results of Chinese banks and the reasons behind the improvement, especially for small banks.

The trade finance gap is a serious issue that is impacting the health of global trade and business development in many countries across the world. Trade finance is the fuel of global trade, upon which 80 to 90% of world trade relies, and if access to trade finance is compromised for certain companies, global trade will be unable to reach its full potential.

The origination of the ongoing crisis of Non-Performing Assets (NPA) in India cannot be attributed to a single event nor can it be confined to a particular timeline. It was only in the mid 1990’s; post the economic liberalization when the country entered into the new millennium that the banks realized the sudden compounding of bad loans. The NPA situation essentially propelled in the mid 2000’s following over-optimism in the economy specifically between 2006-2008, on the back of strong economic growth and pending infrastructure projects completing on time and within specified budgets, a thing largely unheard-of till then. This irrational exuberance was followed by number of bad loans being advanced by the banks often by compromising due diligences. Riding on this positive environment, corporations were being granted loans based on recent performances and growth. Loans were being advanced at an alarming rate, and these corporations grew highly leveraged which led to most of the financing through external borrowings rather than internal equity. However, though post the global financial crisis of 2008, the bubbled economic growth stagnated and the repayment capability of the same corporations substantially decreased causing unparalleled financial stress on the banking and the corporate sectors. The strong projections for various projects started seeming unrealistic and it became increasingly clear there was no set structure in place to recuperate these loan advancements.

Deteriorating asset quality led to enhanced provisioning, reduced profitability and a subdued capital position has created a challenging period for the Indian banking system. Poor asset quality levels also necessitated capital infusion into several banks, especially in the government owned banks. Policy measures like resolution under the Insolvency and Bankruptcy Code (IBC) has helped the banks in recoveries of certain bad accounts. The government has taken decisive measures towards consolidation of the banking sector by creating fewer banks of significant size which would be easier to operate and capitalize. Further, the government has announced infusion of capital to enable transition of these banks.

With increasing volumes of data, and the introduction of Artificial Intelligence (AI) and Machine Learning (ML) technologies, models are at the heart of every financial institution (FI)’s operations. But as FIs increasingly rely on model outputs for decision-making, the focus on model risk – or risk of errors in the development, implementation, or use of models – has continued to gain momentum.

Some might still perceive millennials as a generation of teenagers obsessed with avocado toasts and fancy festivals. However, the upper bracket of today’s millennials are now almost 40 years old and many of them are entering their prime spending years. Over the next three decades, millennials would have inherited 30 trillion US dollars, and by next year they will make up 50% of the total global workforce.

Traditional banks are under fierce rivalry from new competitors, both big tech companies and smaller fintech start-ups. Initially, existing regulators were making it harder for new entrants to challenge banks, but this is starting to change. In Hong Kong, Chinese technology firms such as Alibaba, Tencent and Xioami were recently granted virtual banking licenses. They can now compete head-to-head with traditional banks on a level playing field. To preserve their market share, banks need to reposition themselves in the market and offer customers a better digital experience. Simply hiring a digital team and occasionally implementing stand-alone digital initiatives will fall short.

In a period of uncertainty for global trade, fuelled by protectionism and increasing concerns regarding a potential US-China trade war, the strength and resilience of Asian trade endures.