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Making real-time reporting a reality

By Andreas Hauser,Senior Business Product Manager, Real-time Reporting and Innovation Cash Clearing, Cash Management, Deutsche Bank   

If a client were to ask its bank why a payment had not been fulfilled, is it really acceptable for the answer to be: “We don’t know”? Real-time liquidity benefits are ready to seize in the here and now. With the right application and a consistent consumption of real-time account information, banks can have a clear view on their current liquidity situation. 

Flashback to the year 2008 and the height of the financial crisis. A counterparty has just defaulted on a sizeable payment to a large global bank. The bank is highly sensitive to changes in its intraday liquidity positions, so immediate action is required. Unfortunately, the bank lacks visibility over its intra-day payment flows and is therefore unable to respond to this situation quickly and decisively. Without the necessary liquidity the bank finds it hard to mitigate the negative impact on its own time-sensitive payment obligations and the situation begins to snowball – spreading from one bank to another before the end of the business day.

The potential for such scenarios was an obvious red flag for regulators. Something had to change and as a result, the Basel Committee on Banking Supervision (BCBS) proposed guidelines in 2008 and 2013, known as BCBS 144 and BCBS 248 respectively, recommending principles for banks to track their liquidity flows over the course of the business day. Returning to the present day, we find the regulatory emphasis on real-time visibility has even increased, with the incorporation of BCBS 248 into the Basel Framework. However, the mandate of real-time cash-balance monitoring and reporting has yet to materialise across the market.

Andreas Hauser, Senior Business Product Manager, Real-time Reporting and Innovation Cash Clearing, Cash Management, Deutsche Bank
Andreas Hauser, Senior Business Product Manager, Real-time Reporting and Innovation Cash Clearing, Cash Management, Deutsche Bank

It’s an issue that has receded from the limelight in recent years, but, in this day and age, if a client were to ask its bank why a payment had not been fulfilled, is it really acceptable for the answer to be: “We don’t know”? Banks should have a clear view over their intra-day cash positions – be it on their RTGS accounts or on accounts held with Nostro Agents. It’s the starting point not only in guarding against stress scenarios, but also to manage and optimise their payment flows. Put simply, banks that don’t capitalise on this opportunity are missing out on potentially huge efficiencies and controls.

Maximising efficiency and control

From medium-sized to more specialist players, there are a number of banks with significant cash positions in the main currencies. In any given 24-hour period these positions are likely to vary significantly. Though there is no one optimum pattern – as this depends on the bank’s business models, products and locations – the benefits of implementing the guidelines published by the Liquidity Implementation Task Force (LITF), in response to the former BCBS 248-paper, are clear.

These have been demonstrated in a recent Deutsche Bank study, which compared the daily real-time cash balances from start of day until end of day for four banks across a three-month period.  Figure 1 shows a bank that has not implemented a real-time cash-balance reporting strategy, while Figure 2 shows a bank that has.

Figure 1: Non-user of real-time reporting services

 

Figure 2: User of real-time reporting

At the bottom of Figure 1, the outlined box shows the points at which the account is under-funded. To avoid being short on the account and having time-sensitive payments queuing-up as a result, a liquidity deficit such as this might force the bank to rely on intra-day credit lines, incoming flows or liquidity transfers. In contrast, the box at the top of Figure 1 outlines where the account is being over-funded – meaning that the bank is holding onto surplus cash that could be better leveraged elsewhere. These inefficiencies, resulting from either over- or under-funding, can last for the majority of some business days.

Comparatively, the bank that has implemented real-time cash-balance reporting into its liquidity management strategy, as depicted in Figure 2, suffers shorter and less frequent instances of over- or under-funding and has a clearly defined daily pattern, reflecting a considered strategy.

Seize the opportunities

So why do these benefits remain off the radar for many participants in the correspondent banking network? For a considerable number of banks, industry-wide projects, such as the migration to the ISO 20022 payment messaging standard, are being addressed with a greater sense of urgency. In addition, the development of complementary technologies, including Application Programming Interface (APIs), Distributed Ledger Technology (DLT) and artificial intelligence (AI) and automation, are rising up the strategic agenda.

But history teaches us that the “next big thing” will always loom on the horizon, while real-time liquidity benefits are ready to seize in the here and now. With the right application and a consistent consumption of real-time account information, banks can have a clear view on their current liquidity situation. What’s more, in combination with SWIFT gpi, banks can enjoy improved visibility across all parties involved in cross-border payments, including the status of the payment at each embedded agent. These are upgrades that can be implemented today and pay for themselves long before the ISO 20022 migration has completed.

CategoriesIBSi Blogs Uncategorized

ML algorithms learning investment signals

Machine learning and associated algorithms are making real waves not just in banks’ front offices but also in analysing and spotting trading opportunities in the stock markets.

Machine learning (ML) is being used to identify trading patterns, initially in historical trade and quote data. This may sound familiar to those who are cognisant of technical analysis and the end goal is indeed the same, that is, to find useful patterns in historical and even real time data that lead to decisions that may result in profitable trades either long or short.

According to Tom Finke, head of machine learning product management at software and data provider OneMarketData: “What’s different now is that the techniques have evolved in performing that analysis. In particular, we are able now to use machine learning algorithms to help improve some of the more historical sorts of algorithms that were used to try to detect patterns. When we train machine learning models, such as neural network models, they are able to find patterns that traditional analyses like regression analyses might not otherwise find. These sorts of algorithms are able to find patterns that mere humans are not able to find because of the extent of the vastness of the data that can be analysed.”

An arms race?

Of course, if every trader was to follow the same analytical signals they would all be doing the same thing at the same time. Finke admits that funds, brokers, trading firms, banks and asset managers are facing a “sort of arms race”! He added: If you don’t participate, there is a risk, you’ll indeed be left behind. It would be advisable for investment firms and investment funds that want to stay on top of things that they really should form teams to at least investigate how machine learning can help with their investment and trading decisions.”

But the machines are not completely taking over, well not yet. “It takes some human ingenuity and cleverness, to decide the parameters around those machine learning algorithms. For example, what is the most appropriate data set on which to build a machine learning model?”

Right now, the human element is still required. It takes a person to decide which ML algorithm should be used and what pool of data should be analysed. However, there are companies working on this with ML algorithms being developed with the aim of having them choose which are the best ML algorithms to use.

Watching the markets move

With algorithms being used to analyse trading patterns it should come as no surprise that one way this is being leveraged is in market surveillance. OneMarketData’s core product is a time series tick level database on which that company had built various vertical applications – one of the most popular being trade surveillance.

“We have that particular application being used by a major exchange in the US and by quite a few investment banks. They’re analysing order books; some historically and a few in real time to try to detect patterns that are nefarious such as spoofing  or layering [both forms of illicit manipulation in which a trader may attempt to deceive others regarding the true level of supply/demand for a given financial instrument]. Traditionally there are patterns that you can look for and detect to try to find these activities and now we are in the early stages of applying machine learning algorithms to that,” said Finke.

One thing that has changed in the financial markets in the last few decades is the sheer volume of data and number of trades. Finke noted that in the last week of February 2020 when the world’s financial markets became seriously ‘spooked’ by  concerns over the global Coronavirus (COVID-19) outbreak, the number of ticks during the volatility was such that “some of our customers were running out of memory in their memory databases”.

Seeking the right signal

ML and the appropriate algorithms are capable of analysing more than just price data. For example, Bloomberg now provide a machine-readable news feed that is tagged to make it easier for computer software to parse the text.

This parsed news may then be stored in the same way as trader quote ticks. Run it through a natural language processing algorithm to parse it into meaningful chunks (a technical term!) and then as stage two use another ML algorithm to decide whether there is enough information to provide a trading signal… and if there is, what should that signal be?

Such algorithms are being developed with the analysis of historical data but once the models are trained, they can be applied to real time streaming news data to try to generate real time trading signals. Sure-fire success in such endeavours is by no means guaranteed. “This still a hard problem. It’s hard for humans, it’s hard for anybody to pull meaningful market sentiment out of newsfeeds. We’re still in the early stages of having any sort of effective results, but that’s certainly not stopping people from making the attempt,” concluded Finke.

 

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Ingenico ePayments says wearables, sound, NFC will dominate digital payments in India

By Ramesh Narasimhan – CEO at Ingenico ePayments, India

Demonetisation was a watershed moment in the history of independent India. A decision geared to curb black money provided the platform and impetus to consumers to move to non-cash payment methods, and a slew of initiatives undertaken by the Government of India thereon has catalyzed the e-payment ecosystem in the country, expected to worth USD 135.2 billion by 2023, from USD 64.8 billion in 2019.

With India’s share in worldwide transaction value set to increase from 1.56% to 2.02% by 2023, the country’s e-payment sector is witnessing exciting trends, existing and evolving, which have the potential to catapult the nation as a dominant player in this segment.

Wearables as alternate payment channels

Internet of Things (IoT), which has the potential to bring a fundamental change in the way we interact with our surroundings has not only made objects smarter but has also enabled the seamless transfer of information between devices, organizations, and end-users.

Riding on the burgeoning growth of India’s wearable market, which registered a whopping 168.3% year-on-year growth in 2019, these inter-connected devices have evolved as alternate payment channels.

Last year, Mastercard announced its collaboration with token service provider Tappy Technologies to enable contactless payments through fashion wearables, starting with Timex Group’s analog watches.

Tappy Technologies in a similar collaboration with ExpressPay Card (a JV between China Union Pay and Bank of China) and Saga Watch offered cardholders a wearable payment option, acknowledged by merchants capable of accepting China UnionPay contactless payments.

Sound-based payment – the next big thing

Voice commands have revolutionized the home automation market and could soon sweep the digital payment space. The new frontier in this segment, the USP of sound-based payment system lies in its simplicity and convenience.

With nearly 668.3 million users projected to rely on soundwave technology by 2021, this mode of digital payment can radically change the dynamics of the digital payment sector.

Realizing the potential of soundwave technology, a few companies in the country are facilitating payments through soundwaves without the Internet. Encrypting data from one device to another using sound waves, all one needs to do is to program their device with the software developed by these companies, places the device within proximity of the POS terminal and the transaction is completed within seconds.

Near-field communication payments picking up pace

Also known as contactless payment and tap-and-go, near-field communication (NFC) payments truly came of age when the National Payments Corporation of India (NPCI) launched the National Payment Mobility Card last year, whereby users could make payments just by tapping the terminal, without the need to enter a PIN for transactions below Rs. 2,000.

Like QR codes, which are already quite popular among informal and small merchants, NFC-based payments give users complete control over transactions and the payment process. Following NPCI’s footsteps, many banks and financial institutions came up with NFC-enabled cards as one of their primary offerings.

The launch and success of applications like Google Pay make a strong case for NFC-enabled payment system, which I believe will gain significant traction in the coming days.

In conclusion

With technology taking center-stage of financial services, and the Government’s drive to a less-cash economy, the digital payment segment in India is expected to the breeding ground for innovation and newer opportunities in the coming days.

(Disclaimer: The views and opinions expressed in this article are those of the author and do not necessarily reflect the views of  IBS Intelligence. Ingenico is a digital payments solution provider)

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Contagious pandemics like Corona prompt investors to move towards safer haven

By Nitin Mathur, CEO & Founder of TAVAGA

Nitin Mathur

When the world’s second-largest economy gets hit, the tremors are bound to be felt by both large economies such as the US and developing ones like our own.

The Coronavirus (COVID-19)epidemic, with its epicenter in Wuhan, the capital of the busy province of Hubei in China, has claimed more than 3,000 lives and infected over 90,000. It has spread to over 60 countries and sent shockwaves through financial markets. Beyond its pathological implications, lies its impact on the global economy.

The Indian angle

The trade between China and India is worth $87 billion, of which we import goods worth $70 billion from China. It includes everything from electric components and machines, medical instruments and pharma raw materials, vehicles and auto parts, iron and steel components to nuclear machinery.

While China takes 5.1 percent of our total exports, in the form of cotton, salt and organic chemicals, and mineral and metal ores among others, we get 13.7 percent of our total imports from China alone.

Needless to say then, when our second-largest trading partner hits the brakes on its factory output, companies in India break into a sweat.

We may have pushed for smartphone manufacturers to increase their domestic production, but they still depend on China for their components. Other electronic goods manufacturers would also be facing production issues.

A supply shortfall in consumer electrical and electronic goods in India (either due to coronavirus-led Chinese cuts or our economic slowdown) would also trouble online sales, as they form a sizable portion of e-commerce goods sales.

Pharma companies bring in key raw ingredients from China to make medicines. Automobile manufacturers, too, are heavily dependent on their components on their Chinese suppliers.

However, the Chinese New Year in January-February would have proved to be a greater boon than usual as companies would have stocked up by December last year, anticipating the Chinese holiday season.

Goods and services 

Goods and services across the world are suffering the aftermath of the quick spread of the Coronavirus (COVID-19). Global exports and imports and Chinese exports and imports are so intertwined that it is unavoidable.

The spillover of disruption has been the most acute in China’s neighbors as seen in their monetary policy responses.

Impact of Corona Virus, DBS Report/Tavaga

 

Goods movement

Shipping has been heavily affected with curbs on movement to stem the spread of the Covid-19 virus.

Shipping companies have cut back on their ships sailing from China to the rest of the world, carrying goods, to prevent the virus from advancing to other areas.

It has a direct bearing on the world’s supply chain as 80 percent of global goods trade by volume is transported in ships and China itself houses seven of the world’s 10 busiest container sea-ports, says the United Nations Conference on Trade and Development. The contagious coronavirus is a threat to business infrastructure in adjoining countries as well, as Singapore and South Korea, too, have busy ports and have seen the disease escalate.

Global GDP

The global GDP will be compromised due to the economic fallout of the coronavirus. China accounts for around 18 percent of the global GDP (2019) compared to 4 percent when the Sars epidemic had broken out in 2003. Chinese businesses are now more ingrained in global supply chains.

Sars had robbed China of 1 percent of its economic growth in the eight months it had lasted. The coronavirus is expected to shave off 1-2 percentage points off China’s GDP growth in the first quarter of 2020.

Investor takeaway in times of epidemics

Contagious epidemics such as Coronavirus (COVID-19) bring uncertainty to the investing community worldwide, prompting them to move towards traditional assets such as golds and bonds that are perceived to be more stable, instead of the assets with systemic risk like equities.

That is where smart investment planning involving diversification and asset allocation comes in. It allows us to stay out of troubled waters and focus on our health, instead.

 

(Disclaimer: The views and opinions expressed in this article on Coronavirus are those of the author and do not necessarily reflect the views of  IBS Intelligence.)

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Quantum Computing: The next frontier.

By Kiran Kumar, Co-Founder and Executive Director of Profinch Solutions.

Growth and relevance are quintessential business matters that keep organizations on the qui vive for opportunities to conduct business more efficiently and profitably while keeping step with changing times. The last few decades saw digitisation and technology emerging as this opportunity – starting off as a differentiator that set the leaders apart from the laggards to eventually becoming the only option available to stay relevant. The tech quarters are now abuzz with Quantum Computing – the nouveau arrive that promises to bring in the new wave of disruption.

Quantum Computing and Financial sector – What’s the fit?

Quantum Computing is a field which applies theories developed under quantum mechanics to solve problems. It entails the use of qubits to represent data as opposed to traditional binary units (0 and 1). Qubits are more flexible and allow for a combination of 0 and 1 simultaneously thus storing way more data than traditional bits wherein data must be either a 0 or a 1.

Quantum Computing’s enormous advantages over traditional computing stem from its conceptual design – the solution space of a quantum computer is orders of magnitude larger than traditional computers, even immensely powerful ones. The power of a quantum computer can be approximately doubled each time only one qubit is added. Relative to classical information processing, quantum computation holds the promise of highly efficient algorithms, providing exponential speedups in a multitude of processes.

Armed with these, Quantum Computing lends itself seamlessly to the financial sector since faster, more accurate, and more secure processing is at the core of how the industry needs to function.

Sample this – Google’s most advanced quantum computer named Sycamore could possibly solve a specific computational task that a traditional supercomputer takes 10,000 years to solve within 3 minutes. With that kind of speed and efficiency in tow, Quantum Computing is expected to produce breakthrough products and services likely to successfully solve very specific business problems. This could well usher in a new heyday, with financial sector holding the odds for being one of the most mightily favoured.

Delineating the Impact – what are the gains?

1. Enhance the efficiency of crucial operational processes in banking like

–  Client management, KYC processes, Client onboarding
–  Loan origination
–  Treasury management, trading and asset management

2. Revolutionise data security

Financial data encoded with quantum cryptography will be far more secure than other kinds of digital security. Such data cannot be hacked because the data in quantum states is perennially shapeshifting, i.e. constantly changing states and hence cannot be read. In fact, Quantum Computing has the potential to break even the most powerful security encryption of classical computers today. One of the examples to illustrate the use of quantum cryptography is known as a “quantum distributed key system” which promises secure digital communication that cannot be broken, even by a quantum computer itself. Banks such as ABN-AMRO are already starting to integrate this technology.

 3. Fraud detection

Quantum technology adeptly extends itself to fraud detection. As per a report in Feb 2019, financial institutions lose between USD 10 billion and 40 billion in revenue a year due to frauds and sub-optimal data management practices. Automation of fraud detection relies on recognizing patterns in data. Thanks to the qubit setup, the data modelling capabilities of quantum computers will prove superior in finding these patterns, performing classifications, and making predictions that are not possible today because of the challenges of complex data structures, thus averting fraud before it happens.

4. Customer targeting and service in banking

Classical computing is limited in its ability to create analytical models that can accurately and promptly cull insights from heaps of data available and target specific products at specific customers in near real-time. This greatly constrains the agility of response to rapidly evolving needs and behaviours of customers today. As per a study in 2019, 25% of small and medium sized financial institutions lose customers due to offerings that don’t prioritize customer experience. Quantum Computing can be quite the gamechanger for customer targeting and predictive modelling. It can also significantly enhance efficiency of critical frontal processes like customer onboarding which can sometimes take as long as 12 weeks to ensure due diligence. Use of quantum technology can turn around efficiencies thus enabling a far more superior and consistent customer experience.

5. Quantum data and transactions

Quantum technology’s ability to handle billions of transactions per second will be highly sought after by financial institutions consistently saddled with huge volumes of transactions. Quantum Computing reduces the likelihood of crashes and data loss. This will significantly accelerate the field of high-frequency trading.

Quantum computers will be able to mine colossal volumes of data almost instantaneously. This could enable the use of AI to make automated decisions using sets of pre-programmed rules.  AI is heavily reliant on large chunks of data to be able to learn. Given that Quantum Computing can handle that with incredible efficiency and speed, machines will quickly gather feedback that shortens their learning curve. Operations such as loan and mortgages can be automated, making them faster and efficient with seamless approvals and near zero delays.

6. Risk profiling

Financial services institutions are under increasing pressure to balance risk, hedge positions more effectively, and perform a wider range of stress tests to comply with regulatory requirements. With an ever-evolving regulatory climate, the complexity and cost of compliance is only expected to spiral in the coming years. Currently, Monte Carlo simulations are widely used to analyse the impact of risk and uncertainty in financial models but are highly limited by the scaling of the estimation error. In the face of more sophisticated risk-profiling demands and rising regulatory hurdles, the data-processing capabilities of quantum computers can improve the identification and management of risk and compliance.

7. Onward from here/ The shape of things to come

While the advantages run aplenty, Quantum Computing is still in the inceptive stages. A 2000 qubit quantum computer is expected only after 2025; beyond 2022, some aspects of Quantum Computing may start getting integrated with other cutting-edge technology of the day (such as AI and blockchain) to unravel amazing use cases in consumer experience, cybersecurity etc. The long and short of it is that, we stand at least five years away from Quantum Computing significantly impacting the financial services landscape. However, speculation abounds that Quantum Computing will mature at a velocity unseen by classical computing, and market developments and activities around it in the last couple of years endorse it. Reports say that financial bigwigs like Goldman Sachs, JP Morgan, CBA, Barclays, RBS, Allianz have already started investing in Quantum Computing technology.

The time is ripe for the penny to drop – for enterprises to start exploring investments in Quantum Computing. Those who adopt quantum early can seize major competitive advantages, including the potential to vault ahead of competition and become market leaders.

CategoriesIBSi Blogs Uncategorized

Coronavirus Impact on Banks – The Top Ten List

1. Financial Services sector stability & profitability comes under pressure – stock valuations and prices come down.

2. Central banks bring down interest rates – if a significant part of the asset book is flexible rate, then interest margins are affected.

3. Lower business and consumer transactions – lower fee income.

4. Less liquidity from government as they need to finance deficits. And deferred spending – negative liquidity impact.

5. Number of corporate banking sectors negatively affected. Example – oil & gas, consumer durable, automotive. Increased number of work out accounts, likelihood of NPAs, and reduced income.

6. SME/Commercial clients under pressure for many sectors – reduced demand and delayed payments from customers. Larger number of NPAs, work out accounts, and reduced income and a smaller trade finance book.

7. Wealth Management not so wealthy any more. Portfolio values down. AUM down. Conversion to cash preserve capital. Resulting in fee income reduction. Also margin calls.

8. Retail book stressed. Less liquidity, and asset quality under threat. Part of mortgage book impacted. Reduced spends on cards, auto and personal loans. Loss of income also resulting in higher NPAs. Also limited growth.

9. Branch utilization drops off – fear of visit, fewer transactions.

10. Basically the full revenue & cost model affected – urgent need to transform, including job losses.

Potential winner – digital channels and digital banking ? Read the fixes and the suggestions for the best way forward out of this crisis in the next memo !

Regards

Chairman, IBS Intelligence

Subscribe to the IBSi FinTech Journal to know more about the corona economic & banking crisis. Is it a challenge or opportunity for banking tech?  Subscribe today

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Zero-MDR to create sustainable business model for digital payments ecosystem

By Gaurav Tiwari, FinTech Expert & Former Head Digital at Jio Payments Bank

During the Union Budget last year, India had introduced a Zero-MDR regime to boost digital transactions. According to the system, businesses (with turnover higher than INR 500 million) should provide customers with low-cost digital modes of payment and mandated banks to levy zero charges on the same. Most of the payment companies and banks are up in arms against Zero-MDR, fearing loss of revenue, and had been lobbying with the Government to defer it for some time.  With the outbreak of the COVID19 virus, the discussions around MDR have intensified further.

WHAT IS MDR?

First, let’s understand what MDR is and what is important for payment providers. MDR or Merchant Discount Rate is the money that is paid by a merchant to the payment ecosystem used in facilitating the transaction. All the parties involved in the value chain–acquirer, interchange, and issuer get their share from this MDR, including the third party technology or operations service providers used by these parties. MDR is typically a small percentage of transaction value, somewhere between 0.8 percent to 3 percent. Essentially what it means is that when you pay a merchant INR 100 using your credit card, the merchant gets only INR 97, while INR 3 gets divided between all others involved in facilitating this exchange.

WHAT IS THE DEBATE?

Why would a merchant agree to take a cut in his/her income to facilitate the transaction? After all, it is the merchant who drives the mode of transaction and not the other way around. How often have you refused to deal with a merchant because he did not accept your credit card? You find a way to pay that merchant agrees, and you continue with your purchase. Then what is the answer? In a credit card ecosystem, the card company facilitates the purchase by offering instant credit to the customer by taking a risk on the transaction. This risk taken by the issuer enables the purchase to go through, which may not have happened in case the credit was not issued at the time of the transaction. Now, here is something for the merchant to gain; he is winning a sale, which may not have happened otherwise. That is the reason the merchant doesn’t mind paying that MDR. Now issuer alone cannot support this massive ecosystem, and a part of it is distributed among other participants in the ecosystem.

If the MDR supported the technology and operational cost for running the ecosystem, it would have been a flat fee and not a percentage of the transaction amount because the cost of processing a transaction remains more or less the same irrespective of the transaction amount. So the primary reason a merchant agrees to pay MDR is that the issuer is taking a risk on the transaction by issuing an instant credit to facilitate the purchase. Larger the amount, more significant the risk for the issuer.

WHY ZERO-MDR IS NECESSARY?

Then came the debit cards for customers to access the funds parked in their savings and current accounts. Instead of reinventing the wheel, they decided to ride on the same infrastructure set-up for credit cards to facilitate debit card transactions as well. But then they got too lazy and even copied the same MDR based business model. In case of debit cards customer has already parked funds in banks and banks are making more money from that money and it is the responsibility of banks to facilitate access of funds in his/her bank account to its customer. Banks do not want customers to line up in the branches because that is the most expensive mode of transaction for banks, to save that cost banks have set up the digital infrastructure to provide easy access to customers, and this also includes POS/Payment Gateway infrastructure.

I am of the view that the MDR model is excellent for the credit card universe. However, it does not make any logical sense for debit card transactions, and issuer banks should bear the cost of these transactions instead of passing that cost to merchants or customers in any way. Issuer banks should pay interchange and acquirers on a fixed fee basis, and then acquirers should compensate their technology and operations partners from their share. Interchanges as the bodies at the center of all this should facilitate the working of a reasonable compensation mechanism for sustainable ecosystem growth.

The payments industry had been running on this illogical model for far too long, and everyone has accepted it as a norm. The zero MDR move by the Government should work as a catalyst to drive this change and implement a more logical and sustainable business model, not designed to unreasonably favor the banks. Banks should not be allowed to only benefit from this entire ecosystem, while other partners share the whole burden of cost. I hope NPCI, the umbrella body for all payment companies, leads the way with support from RBI and Finance Ministry to arrive at an agreeable solution that doesn’t ruin the payment facilitators and force them out of business. If that happens, the customer will be the biggest loser.

(Disclaimer: The views and opinions expressed in this article are those of the author and do not necessarily reflect the views of  IBS Intelligence.) 

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Wealth management during pandemic like COVID19, stick to asset reallocation: Kuvera.in

By Gaurav Rastogi, Founder, and CEO, Kuvera.in

Governments globally have woken up to the seriousness of the problem that COVID19 (Coronavirus) poses and have put in place adequate emergency responses. On our part, we should follow the best practices and ensure to contain the spread.  The first lesson for all of us is not to be tone-deaf. While crashing markets in bad times are an excellent opportunity to buy, as a community, we must collectively wish and actively work towards making things better. So, stay healthy, sit tight, and spread awareness where you can. The second is to only rely on authentic sources like WHO or CDC. It is not the time to forward everything you receive on social media without verifying authenticity. “Forwarded as received” does not absolve you from your duty as a concerned global citizen.

Investments during the time of global crisis 

These are extraordinary times, and while markets have retraced 20% or more many times before, the speed with which this retracement has happened is a first. It took S&P 500 a mere 16 sessions to drawdown 20% and entered the bear market territory. Global markets are spooked, and so are the Indian equity market. The co-incidence of YES Bank fiasco, in India, playing out at the same time doesn’t make things more comfortable as it impacts investor confidence. However, as we have seen many times before, human and economic resilience is immense, and sooner or later markets do bounce back to reflect the constant march of progress.

Surprisingly for an individual investor, what works in peacetime also works in times of distress such as COVID19. I started working and investing during the dot-com bubble and was trading CDS during the great financial crisis.

Do’s & Dont’s for retail investors

Below are five lessons I have learned to keep one’s personal investing simple. Simplicity matters, because just as in dieting, it is better to follow a diet you can follow for decades than one that requires extraordinary effort for immediate but fleeting benefits.

  1. Stick to your asset allocation and rebalance if it gets off by 5%. We will send reminders when that happens. In a crash, you will sell your debt and add equity. It may appear counter-intuitive, but it is not. You are buying more equity as it falls.
  2. Track your wealth and not just your portfolio. At a wealth level, last month’s ~20% decline in Equity Mutual Funds is still only a 5% decline in average wealth as gold has rallied.
  3. Postpone all decisions by two days. Say you are itching to buy or sell or stop a SIP or increase your SIP. Write the resolution down and revisit it in two days. You will make better decisions.
  4. Check your wealth once a week. Yes, that’s right. The more you check, the more you will think you need to do something. Inaction is not our strength.
  5. If you have itchy hands, buy Rs 100 in any index fund. Always buy, always make it a trivial amount. It satisfies your urge to take action without making any difference to your long-term outcomes.

Stay away from false narratives

While putting a timeline on the severity of the drawdown or that of the recovery is near impossible, following these best practices will help protect your wealth and survive such market crashes. In hindsight, this week will be another example of not making investment decisions in the heat of the moment. If you got whipsawed by the price movement, then consider it a learning lesson. As an investor, don’t punt on daily price moves. Don’t fall into the false narratives of fading a big move or catching a rally early – especially if it is coming from an expert. The winning strategy is to keep it simple and stay invested.

 

(Disclaimer: The views and opinions expressed in this article on Coronavirus (COVID19) are those of the author and do not necessarily reflect the views of  IBS Intelligence. Kuvera.in is a wealth-management company regulated by the Indian financial regulator SEBI)

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The Arsenal Your Bank Needs

With digitization dotting the length and breadth of daily life, a huge amount of data gets whipped up by the hour. Every credit card transaction, every message sent, every web page opened – it adds up to 2.5 quintillion bytes of data produced daily across the globe.

This is as big an opportunity as it is an overwhelming statistic – an opportunity for even temperately clever businesses to lap up and capitalize on. Of all, Banking industry is sitting on a large piece of the pie since it generates a colossal volume of data inhouse.

The long and short of Banking digitization

It would not be a stretch to say that banking has picked up the gauntlet of digital revolution and responded with mobile and internet banking. It literally is ‘banking on the go’ with smart interfaces offering a host of banking conveniences. Some of these banks have gone a step further towards digitizing their mid and back office operations to build efficiencies and deliver seamless customer experiences. This spawn a set of scenarios:

  • In their bid to go digital, front-end as well back-end, banks are throwing off data by the terabytes.

  • This data, available on tap without any auxiliary effort remains largely unused and underutilized.

  • Analytics – mining this data for authentic business insights leading to better decision making is still not a priority for a lot of banks.

  • Digitisation to grow numbers and cut costs without insighting is taking banks only so far. To run along further, they need something more.

Data, the Differentiator

While from 1980s to early 2000s, it was IT systems that transformed the ways bank operated, today, data wields transformative potential. While it still presents itself as an untapped opportunity, it can be a critical differentiator, the one that will set the forerunners apart from the pack.

Data and Analytics holds potential in the following key areas:

  • Enhancing productivity – Detailed analytics can help identify lag in processes and improve efficiencies therein. It can help teams take analytics-backed decisions and respond to problem situations faster and more accurately.
  • Better risk assessment and management – Data analytics can help identify potential risks associated with money lending processes in banks. Based on market trends emerging from analytics, banks can variate interest rates for different individuals across various regions. Fraud detection algorithms can help identify customers with poor credit scores and erratic spending patterns to help banks take more informed decisions regarding extending loans. It may also help track dubious transactions that may be fuelling anti-social activities.
  • Help meet compliance and reporting requirements – Data presented in a certain way can help meet compliance, audit and regulatory reporting needs and address issues arising therein. With a super dynamic and ever-changing regulatory climate, banks and financial institutions need a robust backing to be able to meet all requirements on time and with precision, and data and analytics can play a decisive role in this.
  • Delivering an omnichannel banking experience – With customers interacting with banks through multiple channels, a seamless and consistent experience at all points in the chain is crucial and data analytics can help drive this with efficacy.
  • Detailed nuanced understanding of customers – Analytics can enable a detailed profiling of customers based on inputs received from their spending trends, investment patterns, motivation to invest and personal or financial backgrounds. This opens opportunities to personalize banking solutions, integrate customer acquisition and retention strategies and cross-sell & upsell. It can also be a crucial input for risk assessment, loan screening, mortgage evaluation etc.


Realising the Data Dream

Data and Analytics can prove to be quite the enabler for banks that are ready to reinvent themselves. But the data dream can be as elusive as it is promising. A piecemeal approach that moves from one project to the next under can yield results below encouraging. It is important that the business leaders envision what problems they want to solve with data and analytics and get involved every step of the way. A great analytics approach starts at asking the right questions to guide the discovery process, before data is dived into for the sake of it.

By Kiran Kumar, Co-Founder and Executive Director of Profinch Solutions

CategoriesIBSi Blogs Uncategorized

Coronavirus Impact on Banks – The Top Ten List Fixes

1. Immediately reassess sector macros & micros and identify sectors that have become short-term unattractive (e.g. auto), those that are now positive (e.g. pharma), and map your clients and portfolio to the new reality.

2. Segment clients as per new sector matrix, and identify clients already troubled in risk sectors and those likely to be affected.

3. Allocate above group to an expanded & high quality work-out team to co-manage the clients with existing RM’s and provide short term business guidance. Don’t necessarily do a drawn-down. In fact provide additional short term capital if needed. Refocus corporate RM teams to account monitoring, rather than new account acquisition for next 30-60 days. I would not release corporate RM headcount at this time.

4. Do all of the above for SME/Commercial accounts at a higher level of aggression. Understand the supply chain impact on your SME/Commercial clients. Get transaction banking going for SME and also corporate clients.

5. Significantly strengthen your risk, especially credit risk teams, and immediately redo the credit scorecards and algorithms.

6. Protect your liability book. Strengthen size of the corporate liabilities unit. Relook at your retail liability products and make them more attractive. Pull wealth customers in as quickly as possible.

7. On the retail side, assume 15%-30% reduction of liability and asset book, and transform operating, business and resulting cost model.

8. Digital, Digital, Digital. Strengthen your banking technology & FinTech platform & offering, and use this opportunity to aggressively move many of your customers and their transactions to digital and acquire new ones. This black swan moment is now a once in a lifetime opportunity in this area.

9. Assume 20% of the branches will need to be temporarily shut-down. Redirect customer to the other open branches. Save on branch operating cost.

10. Based on the above, make careful cost calculations by business unit from a people, process and technology perspective. Get ready to drop 15%-20% of the headcount with generous exit packages. Also compensation alignment for the remaining may be necessary.

Good Luck. And let us know if we can help in anyway.

Regards

Chairman, IBS Intelligence

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