Commentaries and insightful analyses on the world of finance, technology and IT.

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November 23, 2015

Apply intelligence where it is needed the most

In my previous blog, we talked about letting the CAT out of the bag in order to make risk management more effective. The 'T' we talked about previously was 'transactions,' the other two being 'customers' and 'accounts.' With the increasing number of channels of monetary transfers - both bank-regulated as well unregulated, anonymous ones, such as Bitcoin - to scan each transaction, especially in a pre-facto scenario like anti-money laundering (where the decision making is required, prior to approving the fund transfer), becomes too daunting a task.

In a post-9/11 world, which brought financial institutions to focus on monitoring transactions in order to curb finances of terrorist organizations, the regulations and the know-how required to put them in place is still inadequate (Ref: American Bankers Association). However, good data sets can help address this. Considering the fact that it is not only a select few states funding such organizations, but also a list that includes legitimate charitable organizations and individuals as well, acting as fronts and providing monetary sustenance to them, the need for intelligent predictive and prescriptive analytics is evident.

The days of relying on plumbing are over. Banks today need intelligent and integrated platforms. A move towards big data and analytics is an obvious start, but the required ingredient here, is good data that is intelligent and that paves the way for the subsequent application of this inherent intelligence.

The technology architecture, and specifically the product suites of the modern world, allow strong and seamless integration capabilities through which, data can be sourced into a landing zone. For example, Hive can provide users limitless capability to slice and dice the data, build analytical dashboards, and develop management reports using sophisticated suites like Tableau and Microstrategy. This can be the foundation for further intelligent analytics. One way to achieve this is by establishing loopbacks at every step in the integrated chain, so that the data is enriched continuously, and made more meaningful.

One user group of such data is the operational front and the other the associated central organizations like FINCEN. The vision is to provide both these user groups with as much intelligent information as possible, in order to improve the decision making, risk scoring, and monetary tracking; by enhancing the rules and scenarios with the loopback mechanism.

All that has been achieved with the continuous efforts of the financial industry around the world needs to be implemented a bit more intelligently. The enemy in discussion here is smart enough to create fronts that look completely legitimate, and runs a dark world covertly and intelligently. The statistics teams that build scenarios to scan transactions, need more enriched, real-time data, with a loopback into the system, so that the scenarios become more foolproof, assign better risk scores, and generate lesser false positives.

The legitimate organizations involved in such transactions could be visualized throughout their relationship lineage with the bank, and could be chopped off, thereby reducing bank losses, as well as involvement, and consequent liabilities (if any).

There is a dire need to build effective and productive data farms, in banks, that can link CAT, across its internal banking relationships and provide the bigger picture for every entity. While the cost of such a system may be high, the rewards will be even higher. Good data will not only drive better business analytics and revenues, but also catch illegitimate fund placements, predict their behavior through pattern analysis, and prescribe a course of action; thus safeguarding itself and humanity at large.

November 12, 2015

It's time for the banking Goliaths to take note of the nonbanking Davids!

Within ~1.5 years of the launch of its mobile maps app, Google had erased over 80% of the top GPS companies' market capitalization. Similarly, in just over seven years since venturing into the music space, Apple became the world's largest music retailer. History is replete with examples of new entrants - backed by technological superiority and innovative business propositions - wiping out established companies in almost no time. With this in mind, can established banks today say with any certainty that this won't be repeated in their industry? Today, more and more nonbanking organizations are foraying into the banking sector. Startups like Stripe and Square have earned multi-billion dollar valuations. Today, around one-third of U.S. revenue for Starbucks is paid via its own loyalty cards.

Banks' nonbank competitors span nimble technology players, telecommunications companies, start-ups, retailers, fintech firms, peer-to-peer lenders, crowd-funding websites, internet/mobile service providers, and many others. The threat of traditional banks getting relegated to the limited back-office utilities roles by the nonbanks is quite real. If you are still unconvinced, the three news stories below from the past few months may help change your mind.

By Aug '15, Europe's largest peer-to-peer lending platform, Zopa, had facilitated over £1 billion in loans to over 200,000 people. In July '15, it had experienced over 120% YoY growth in its lending business. Zopa by now has over 2% share of the UK's unsecured personal loans market.

In Mar '15, the Chinese e-commerce giant Alibaba, announced that it is developing facial recognition technology to enable mobile shoppers to substitute their passwords with selfies. Today, China's financial sector is experiencing immense transformation owing to innovative business models from major internet companies like Alibaba that are rapidly adopting microfinance with a digital edge. Alibaba had launched in China - a third-party online payment platform involving no transaction fees.

In Mar '15, the Chinese smartphone manufacturer Xiaomi moved into the financial services arena by enabling an interest-bearing mobile wallet account. Within couple of months, it also launched an online money-market platform - Xiaomi Huoqibao. Today, online money-market accounts are experiencing high popularity in China - thanks to their heavy promotion by the tech industry entrants and also because they offer substantially higher interest rates than traditional banks.

Whether it's lending, payments, cards, wealth management, insurance, or any other banking functions (except deposits where there are regulatory constraints for nonbanks); the nonbanks are making rapid strides. The following are a few examples:

1.Payments: Google, LevelUp, Apple, PayPal, Sage, Starbucks, Square, Walmart, Alibaba, WorldRemit.
2.Lending: Funding Circle, On Deck Capital, Lending Club, Amazon, Kabbage.
3.Money/Wealth Management: Nutmeg, Moven, LootBank
4.Mortgages: Zillow, Quicken Loans, loanDepot
5.Invoice financing: Payplant, InvoiceFair

So what gives these nonbanking players a competitive edge over the traditional banks? In my view, there are three key factors:

1.Digital superiority: Non-banks have aggressively proceeded with digital innovation, ranging from leveraging real-time predictive analytics, open APIs and ecosystems, multi-channel portals, ultra- automated decision engines, cloud, IoT, geo-location and biometric capabilities, and more. Unlike traditional banks who have typically managed their systems via closed structures like proprietary data and communication networks, nonbanks have been aggressively leveraging their APIs and related ecosystems to ensure openness. Zillow and Apple, for example, have a large number of APIs that let their partners integrate into their digital platforms. Similarly, nonbank SME lenders such as Kabbage, Fundera, OnDeck, have digital access to external databases that have a vast amount of information on SMEs. These lenders are capable of real time risk profile assessment using traditional as well as alternative data sources e.g. Yelp reviews, Quick Books entries, etc. Their cloud-based credit scoring capabilities and lending decision engines are underpinned by predictive models that leverage thousands of data points. Further, many new entrants don't follow the limiting linear digitization strategies of traditional banks. For example, Atom bank in UK started with the mobile banking only and planned to add internet banking capabilities only later.

2.Superior customer experience: Many nonbank entrants are globally successful digital companies who are capable of providing superlative user experience. Nonbanks have been proactive in enabling needs-based, simple, and hassle-free solutions to customers. They are capable of servicing market segments that traditional banks have been reluctant to service due to high costs or for other reasons. LootBank's offering of mobile money management with prepaid cards for students, Amazon's lending to its merchants, Payplant's invoice finance servicing for app developers are a few such examples. Nonbanks are able to provide value-for-money to customers. For example, PayPal offers select merchants fixed rate loans which get paid as a percentage of their daily business sales on Paypal, obviating the need for minimum monthly payments. In its foreign exchange business, Transferwise has enabled formidable pricing strategy. Many nonbanks have also seamlessly integrated their product merchandizing, media content, payments/ordering services and other key financial features into their digital channels - all of which are backed by a real-time personalized customer experience provisioning. Biometric authentication, beacons usage, one-click payments, social media integration, to name just a few, also aid in enabling superior customer experience. CityFalcon has leveraged Twitter to provide investment insights to traders; PayPal and Moven have aggressively leveraged their superior digital technologies to acquire tech-savvy millennial customers. Thus, it is no wonder that PayPal is the number one online payment service in many countries.

3.Agility and speed: Unlike traditional banks, digital nonbanks are not subjected to stringent regulatory requirements. Consequently, they can capitalize on this by aggressively innovating. Thus, their continual and frequent innovation, high risk appetite and operational productivity, and sharp focus on value-addition are part of their mantra. They release new innovative service/product with remarkable efficiency and speed and respond to customer needs much faster than traditional banks. PayPal and Square, for example, allow their merchants to start accepting payments within one day (almost a week faster than most traditional banks). OnDeck Capital can decide in less than 24 hours, the credit worthiness of a business customer, and it takes only two weeks or less for fund disbursement (with good number of loans getting disbursed within 48 hours!). QuarterSpot allows business owners to apply for loans online in just a few minutes. Similarly, the balance transfer between the Yu'E Bao investment account and Alipay account can happen in just one click.

I believe it's high time that traditional banks take note of the lessons in the David versus Goliath legend! Don't you agree?

November 5, 2015

Financial services slowly swings towards connected things

The tale of the rabbit and tortoise is known to everyone because it has been told many a time. If we draw an analogy in the business world, financial services (FS) would be the tortoise when it comes to adopting digital technology when compared to other industries.

As with most digital technologies, FS has been slow to embrace the Internet of Things (IoT) whereas other industries have taken to it as a duck takes to water and appropriated a space for themselves in the IoT world.

IoT is simply real-time communication and sharing of information between devices connected to the Internet. Though the definition is simple, the impact that it carries is profound because the information thus collected would be used to predict needs, solve problems, and boost  efficiency with the use of big data, analytics, predictive modeling, and artificial intelligence (AI). Some examples are Apple Watch, Google glass, and Nike+.
Though the FS industry has been slow to move towards IoT, the emergence of technologies such as wearable and sensors have the industry's interest piqued. So much so, that FS is one of the top ten industries investing in sensors for devices.

Apple Pay is one of the most quoted examples of IoT in FS. Another example is telematics, which is used to communicate information about the location of a vehicle, crash notification, and such other vital information to the driver, insurer, and the concerned authorities.

The entire ecosystem, which is being created by these objects with sensors, is bringing in a fundamental change in the way financial institutions interact with customers. With the use of technologies such as big data, artificial intelligence, and analytics, these institutions are beginning to get more personalized data about their customers, which in turn, help them tailor and offer their products and services in a more personalized form to the customer.

Ads, webpages, and product recommendation based on customer data bring convenience, which in turn create better customer experiences. With smooth transactions and continuous customer engagements at many touch-points, the business model and revenues are likely to see a more positive impact. That said, the moment one hops on to an inter-connected digital world, the hounds from hell come chasing to target security and privacy loopholes. This gives cybersecurity a whole new dimension for all the stakeholders involved in this world of IoT. With digital vulnerabilities expanding exponentially, the challenge of keeping the space safe is going to keep all concerned on their toes. The financial industry, already under severe attack would have to be doubly cautious and more prepared to ward off this challenge.

So should the rabbit of our story win? Perhaps continuing slowly and surviving is a better option than getting into a mindless race where survival itself becomes doubtful. Out running is not a choice for our slow friend, he can use the tracks left by his faster partner to be more prepared of the possible way-lays that may lie to hunt him. So slow and steady may not win the race but certainly, survive for another race.