IBSi Blogs

By Simon Moss, CEO of Symphony AyasdiAI

During the Great Recession, enterprise technology businesses did relatively well, including those that served a banking and funds sector that took a direct hit.

Banks and funds that survived cut costs to balance their books as demand cratered, but CIOs felt they couldn’t scrimp on software subscriptions lest they fall behind in increasingly competitive markets where survival meant claiming more of a shrinking pie.

Some in the enterprise tech industry think that dynamic will happen again. Despite recent positive earnings from big tech companies, they’re almost certainly wrong. Now it’s the other way around.

The world is in the midst of what is shaping up to be potentially the worst economic crisis in a generation. It might not feel like it yet because almost everyone has been in a state of denial called lockdown. Sooner or later, though, we’ll open our eyes and see who’s not wearing a swimsuit now that the tide has gone out.

To wit, as Gavin Baker at Atreides Management has written, companies under duress are taking a second look at existing software contracts. Companies spend half their IT budgets on software. A responsible leader can’t keep it off the chopping block.

A false sense of security has lulled many tech and AI firms into thinking they can get away with marketing their technology in the abstract, leaving it to the customer to figure out the best use case. That approach might have worked in a world where customers had the time and money to indulge in exploration.

Customers are nervous. They’ve got more challenges at a time when revenue is a question mark. Our task is to listen and respond with real, easily understandable and, perhaps most importantly, immediate solutions that directly address their needs this week.

Customers today don’t want to know how or why a technology works. They want to know how soon they will see that it is making a measurable difference. For instance, let’s take a look at banks right now.

Banks Swimming In Uncharted Waters

The government’s $4 trillion of stimulus spending in the face of the pandemic is a bonanza for fraudsters. The politicians want to flood the zone with cash overnight. Bankers, however, are on the hook for sifting applicants to figure out who deserves the money and who is seeking to exploit the overwhelmed system for ill-gotten gain.

Thieves have plenty of stolen identities in their little black books. Shell companies abound. Under pressure to shovel out the loans quickly to forestall economic oblivion but wary of regulators eager to blame them for the pitfalls of the government’s haste, the bankers must figure out how to identify good customers from bad.

The moment seems perfect for AI. But humility is a better first response. Most machine learning today is fighting yesterday’s fraudsters. It might catch the amateurs. The professionals, meanwhile, have already been camping in their victims’ networks using sophisticated tools that represent a new generation of graft that’s likely more sweeping than those we’ve stopped in the past.

Commercial banks don’t want more layers of protection that consume their attention, either. They’re already flooded with calls and facing staffing shortages while dealing with swamped government agencies and poorly designed, malfunctioning websites.

The objective, non-biased, hypothesis-free analyses afforded by the right kind of artificial intelligence has a better shot at making banks’ challenges simpler. Auditable machine learning could, for example, provide regulators with not just what fraudsters were uncovered, but why and how.

But do bankers want to hear about topologies and the difference between supervised and unsupervised machine learning? Certainly not. They’re racing too fast for a lecture. They can’t waste time asking if they can really integrate new software into their workflows.

Bubble Bursting

As bankers face a crisis in oversight, generational changes are also afoot. Millennials in particular are poised to begin inheriting trillions in the coming decades. Many of them feel little or no affinity with traditional banks. They expect far more tech-oriented options. To satisfy them, banks are going to need to cut costs in their old systems in order to develop new platforms.

We estimate those cost cuts will comprise around 40 per cent of current spending on technology. Those changes come in addition to the coronavirus pandemic and its aftereffects.

The frothy market for software led to high valuations in recent years. Inexpensive debt helped, too. Look around now. Once-confident AI companies that are having a hard time convincing investors and customers of the value of their product in the new environment. Now customers are facing monumental risks while seeking to lower overhead. That’s a tough climate for the less-than-fit.

AI companies who can quickly demonstrate to jittery chief risk officers and chief financial officers that they can filter out the cheaters, chiselers and scam artists quickly and decisively will not only survive but prosper. That’s the prize we’re chasing. It won’t just come to us.

Simon Moss is CEO of Symphony AyasdiAI, an artificial intelligence software company serving financial services and other industries.

Insurance providers have found themselves at the forefront of the Covid-19 pandemic, but whilst the level of disruption we’ve seen at the hands of the Coronavirus is unprecedented, a quick look at the history of the sector raises the question as to whether it could have been better prepared.

by Vijayamohan Keshav, Senior Principal Business Consultant, Expleo 

The SARS pandemic of the early 2000s should have been a wakeup call to all businesses about the importance of agility. After this event, insurance companies should have taken steps to future-proof themselves, as they did their claims ,by automating vital processes, updating their digital channels, and building a digitally savvy workforce.

Instead, concerns around time, costs and potentially just a general underestimation of upcoming challenges, meant many took a slow and steady approach to digitisation. So, when the Coronavirus hit, up to 70% of providers were still relying primarily on legacy applications – applications that just weren’t prepared to deal with the unprecedented wave of activity associated with a pandemic.

Post this pandemic, insurance providers must put the lessons they learn into action and put automation at the heart of their operations. As Lloyd’s of London announces an expected pay out of between £2.5 and £3.5 bn, their biggest pay out since 9/11, we examine how technology will help bring the industry back on its feet.

Focus on what counts

Whilst costs will inevitably need to be cut over the next few years to make room for more capital, Covid-19 has focused the industry’s attention on what matters when it comes to digital innovation. Far from hindering technological progress, we can expect more investment, with insurers focusing their resources on priority areas.

Blockchain, for instance, is likely to take a backseat in the list of immediate priorities, but automating production processes – whether that be underwriting, claims or complaints – is a no-brainer. There have been far too many delays and mistakes made in recent weeks for this not to become a sector standard. We can expect investments in AI and machine learning to be primarily in the areas of intelligent process automation.

Implementing more robust security measures, meanwhile, is paramount. This has been low on the priority list for investment so far, but with hackers on high alert and remote working becoming the norm rather than the exception, every provider needs to make sure its infrastructure is infallible. For an industry centred around processing money and data – particularly personal data – there can be disastrous repercussions if there is a failure to implement cutting-edge security at the enterprise level.

Earn back trust through innovation

Insurance providers are built upon security, trust and their ability to deliver upon that trust at critical times of need. The performance and customer usability elements of insurance businesses will come under more pressure than ever.

These usability elements include enhancing the customer experience when using digital channels, making claims processes clearer, or providing additional customer service channels through more contemporary routes, like social media – all of which can be enabled by technology.

The critical need for quality covers both back and front-end processes and the clearest path to delivering this is through a quality assurance process that primarily uses automation tools to save insurers critical time and money whilst dramatically minimising risk.

Transformation, consolidation, and regulation

As part of the industry-wide digital transformation process and potentially as a result of the Covid-19 crisis, we can expect a higher rate of mergers and acquisitions over the coming years. Insurers of all shapes and sizes will look to digitally native firms, or InsurTechs to help them grow, scale up or simply survive. We’ll also see a similar chain of events occur within the InsurTech community too, with bigger players acquiring smaller players and key technologies and approaches coming to the fore.

Whether you consider the need for innovation in reaction to Covid-19, or in terms of market competition and disruption, there are few upsides to be found for insurers sticking to legacy systems and ways of serving customers.

More change to come

With entire economies crippled by the virus, for the first time in many years, the insurance industry has had to be proactive in adapting to change. And while it may have been borne out of necessity, we should see this change in pace as an opportunity for the sector to make some much-needed improvements as long as it never takes its eye off security, performance and the quality of delivery.

The road ahead will not be easy – especially with the adjustment to remote working, and accompanying challenges around security and productivity. But if insurance providers can make sure to address and update these crucial aspects of their businesses, and embrace an automation-first mindset, they have a good chance of emerging stronger.

During his 1962 State of the Union Address, John F. Kennedy declared: “The best time to repair the roof is when the sun is shining”. While the original philosophy behind the sentiment wasn’t intended for organisations, per se, it’s an apt quote when reflecting on FinTech developments in light of Covid-19. We are all aware that the pandemic has shut down our normal way of life.

by Ray Brash, CEO, PPS

Since the dot.com crash of 2001 and the financial crash of 2008, FinTech entrepreneurs have adopted a disruptive mindset in order to make headway, and survive, within financial services, launching innovative offerings such as mobile-only banks, with money management tools and personalised saving solutions. And it is this continued innovative approach that has enabled either FinTechs, or businesses using FinTech solutions and tools, to prevail during Covid-19. It is the companies that already had the agile architecture and payment platforms in place who have been in the best shape to adapt.

The organisations which had “repaired their roof while the sun was shining” – in that their digital operations were continuously innovating, pandemic or not – have been most effective in helping their customers and reacting to the demand. After all, if you have a clear vision of an agile roadmap that is able to constantly evolve, it makes it much easier to adapt, rather than restart.

FinTechs and challenger banks aren’t adapting on their own though. Rather, partnerships have never been more important. In fact, an outcome of Covid-19 is likely to be the continued acceleration of these partnerships that make the impossible, and even the improbable, possible.

UK supermarket chain Sainsbury’s was able to work with PPS’ team of experts to launch its Volunteer Shopper Card just a few days into the lockdown, enabling others to shop on behalf of vulnerable citizens. Sainsbury’s is seeing a whole range of digital vouchers coming into their own in the era of remote food distribution. Another traditional brick and mortar customer of PPS, Tesco, has experienced increased adoption of its Tesco Pay+ payment app which allows for QR code payments and gifting of money to dependants across the country for essential purchases in Tesco stores.

FinTech Tide, has adapted to help its small business customer base. Responding quickly to the UK government’s Bounce Back Loan Scheme and with financial support from PPS, Tide has adapted to become an accredited lender, lending from £2,000 to 25% of an SME’s annual turnover, up to a maximum of £50,000 for up to six years. And Coconut, an accounting and tax tool for self-employed people, launched online tools and carried out successful government lobbying initiatives to help support the small business community.

Digital banking app, Monese, has higher transaction volumes now than ever before, with a large portion of its customer base being key workers – many of whom will likely not have been eligible for a bank account with a traditional bank – but include the ‘heroes’ getting us through the pandemic.

Enhancements such as these highlight how, due to the economic disruption, financial inclusion has been pushed further up the global agenda, showing the importance of serving people who could have been left out of the financial system. And there is a possibility that the lasting legacy of Covid-19 may lead to greater financial inclusion initiatives, with FinTech continuing to play an important role through ongoing strategic partnerships with retailers, governments and financial institutions.

While the digitisation of financial services has been under way for decades, the pandemic has accelerated the timeline exponentially. But it is the companies that have best access to agile and adaptable platforms, through the right partners, that have been able to navigate the ongoing landscape most effectively.

Going forward into the ‘post-Covid’ world, it will be important for FinTech players to maintain their disruptive mindset in order to continue to lead, rather than follow the new normal. We saw this with the likes of Amazon after the ‘dot-com bubble’, and the many storms it has weathered over the years to become the world’s largest retailer. We will see similar performance in FinTech too, while things re-adjust. There will always be some casualties along the way, but ultimately, the FinTech powerhouses that are the most agile, with a ‘roof’ ready for any crisis, will succeed.

By Andrew Warren, Head of Banking & Financial Services, UK&I at Cognizant

In addition to responding to changing customer expectations, higher operating costs, new technology, and an evolving regulatory landscape, financial services organisations now also face the uniquely challenging business environment created by COVID-19. The economic consequences that are unfolding rapidly and unpredictably mean that banks must double-down on both their efficiency and customer experience agendas. In light of this, the need to modernise legacy banking platforms will gain sharper focus as banks emerge into the post-COVID-19 landscape, driven by the need to focus on value for customers and agility to change and shift operations quickly.

If banks are to remain strong and stable and make real progress with their efficiency and experience agendas, transformation is non-negotiable – but it can be risky and have high rates of failure. So how can banks pursue their transformation agenda, while addressing the very real risk that modernisation of legacy banking platforms presents?

Focusing on value

Banking transformation may have traditionally been the domain of the IT function, but the impact on current and future value means it should be on the agenda of a much wider set of senior executives. This includes the CIO and COO but should also be as far-reaching as the Chief Risk Officer, Chief Financial Officer, Chief Digital Officer, and Chief Experience Officer.

When we talk about value in the context of transformation it can mean multiple things. In monetary terms, transformation can reduce the total cost of a bank’s IT infrastructure, with legacy equipment 55 per cent more costly than cloud data. More importantly, however, transformation often results in moving from highly manual-orientated processes to more efficient, automated – and therefore accurate – processes. In turn, this can lead to more informed and tailored products and services, internal process efficiencies, enhanced cybersecurity, advanced analytics, and reduced risk, especially around fraud and malicious activity. These all add significant value to customers, as well as operational and regulatory imperatives.

Furthermore, viewing transformation through a value lens should tie it to a range of specific financial and accounting metrics that ultimately measure success. That includes both those that reflect the protection and extension of current value, as well as measuring the extent to which transformation will support the capture of future value. Financial services organisations have a huge opportunity to create greater value for customers from innovation in products and services. Changing market dynamics are creating a basis upon which banks and others in the industry can evolve their offerings and organisations.

In much the same way as we have already seen in retail, for example with Amazon and AliBaba, and media platforms, such as Facebook and Netflix, customers are adjusting to a new way of banking that is changing expectations. To keep up, banks need to increasingly provide easy-to-use digital-first services across their products, as well as introduce new tools to help customers manage their money in the 21st century. And there is no doubt that the fall-out from COVID-19 will likely further drive the degree and extent of digital adoption.

Traditionally, financial institutions take many different approaches to transformation, such as developing sleek new customer experiences to compete, or developing new platforms and partnering with FinTechs. But achieving success for more mature banks is more challenging given the obstacles presented by their legacy platforms. Comprising complex, customised systems, these are expensive to run and very costly to change.

Transformation: not if, but how

To truly transform operations and experience, many banks are now having to face up to the reality that they cannot move forward without banking platform transformation. That means they must – in one way or another – replace their historic systems with more modern, cost-effective, and flexible platforms. That is going to be essential to stand up the capabilities required to enable digital products and deliver the truly revolutionary experiences that customers demand.

Recognising the inevitability of change, many banks are now considering their options. Some have already started down the challenging path and hit bumps in the road. A very small number have successfully executed their ambition to create a platform for the future. All banks contemplating transformation should take lessons from both the successes and the mistakes. These will be critical to inform their plans.

Moving forward

There are a number of essential transformation steps to consider that will help realise value from investment as rapidly as possible, provide an appropriate level of delivery confidence, and manage exposure to the operational risk normally associated with such changes. These include:

1. Business strategy must inform every step of transformation – ensure that the approach to platform transformation is tightly aligned to the wider business strategy.
2. Design a strategy-aligned roadmap for delivery – a transformation roadmap should clearly set out the logical order in which business outcomes will be delivered. Here again, that needs to align with the value that the organisation is seeking to achieve, with incremental progress determined by business priorities. This involves making appropriate use of modern delivery methods, such as agile, and making sure that everything that is done satisfies and is frequently assessed against the relevant value criteria.
3. Assess technology selection against business value – organisations often undertake detailed and exhaustive market, functional and technical assessments when reviewing new products and suppliers. This often means either the technical assessment dominates proceedings and/or new technology platforms are selected without a clear line of sight to the value required. Poor product selection is a risk as a result, as well as a lack of understanding of how products should be deployed to inform the sequence of delivery required by the transformation roadmap.
4. Assess your readiness for change – unsurprisingly, given the sheer scale and velocity of change that business leaders must deal with, resistance to change is often a key reason given for the failure of banking transformation projects. However, it is crucial that the ability of the organisation to deliver and adopt the operational, technical, and cultural changes required to support transformation is comprehensively assessed and done early.

The impact of COVID-19 paired with and the demands that financial services organisations face from all directions, make change an inevitable necessity for the most. The approach to delivering a successful banking transformation, underpinned by a modernised platform, will vary dramatically from bank to bank. However, above all, businesses need to ensure that value drives every aspect of change explicitly linking transformation strategy and investment with the realisation of value.

Andrew Warren
Head of Banking & Financial Services, UK&I at Cognizant

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

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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.) 

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