April 2018

Are Platform Banking and Bank-as-a-Platform, one & the same?

The information industry has evolved from monolithic applications, to client-server technology, to thin connections, to components & services, and the latest in this trend is ‘platform’. The significance of ‘platform’-ing an application varies in different degrees for different industries. ‘Platformification’ is becoming increasingly significant in banking or in the financial industry at large. The common understanding of platform in banking industry can be well described by using key words such as ‘standardization’, ‘industrialization’, ‘open architecture’, ‘intuitive’, ‘personalized’, ‘model driven’, ‘componentized’, ‘cloud ready’, ‘API enabled’, and more. While all are required to complete the definition of a platform, the best platform is one that allows the business to innovate and differentiate.
Application Programming Interface, more commonly known as ‘API’ is a key aspect that can elevate an application from the current state to a platform. APIs empower the application to allow exposure to business rules, definitions and usability in a manner that can be easily adapted to a given scenario thus providing a seamless methodology to integrate applications and components of varying maturity implemented for different technologies. While there are several other aspects such as data models, DB agnosticism, layered architecture which play an important role in re-inventing an application into a platform APIs are the key ingredients in this journey. The more open an application becomes by using APIs, the closer it moves towards becoming a platform.
There are several standards in the API industry and slowly these are getting converged into one or two major groups. Native APIs, RPCs, SOAP APIs, REST APIs are coming together and we will soon witness most of these getting mapped to some sort of standard way of representation of application business.
The core matter to consider is that whether platform banking and bank as a platform are one and the same? Do APIs in terms of definition and applicability carry the same relevance in these two aspects?
While it appears in the current state that the two convey the same meaning, we are beginning to clearly see the distinction between the two. Platform banking will continue to evolve the way it is currently going, helping banks open up more and more services for internal and external players and to re-imagine banking business through various means. However, it will still continue to revolve around the services, offers and differentiations provided by the banks or associated entities including Fin-Techs. Banking as a platform will soon imbibe an altogether different meaning and it will allow the clients or more commonly known as ‘account holders/CIF’ of the banks to reimagine banking in a way that is highly personalized to individuals. The journey on this front has already commenced for corporates and it will spread to retailers and individuals in a short span of time.
To differentiate the two aspects in a better way, let us consider the following examples:

Financial institutions including banks would like to separate processing of payments (including non-financial messages) from the core banking applications. This necessitates the payment processing hub functionality to be separated out and configured as a platform through which banks can interface with various standardized payment gateways. The platform is expected to be open in terms of architecture, must have API support, be extendable for corporate cash management processing, be cloud ready and so on. This qualifies the definition of platform banking.
A retail customer of the bank would like to configure and personalize an investment product as per his/her requirement. This would involve user experience, modularity, abstraction, compliance and the ability to manage individual products designed by a bank’s customers. The ‘bank’ will be abstract in this case and ‘banking’ for all practical purposes will be carried out by the customer. This requires the bank or banking to be available to all customers/prospects as a platform. Re-imagined APIs will enable this aspect.

Therefore, APIs will evolve into another ‘avatar’ to enable bank become a platform for its customers. The differentiation of platform banking and bank-as-a-platform will further help APIs to drive differentiation and simplification of the industry as a whole. The eco-system involving ERP systems, cloud ISVs, Fin-Techs will harmonize more and the banking community as a whole will altogether leap into significantly higher orbit. With changes in lifestyles and behaviors, banking will become more and more visible to customers and bank by itself will remain invisible to a large extent.

Predictive Analytics Making its Way into Banking

Ever wondered how some companies manage to delight their customers by offering just the right kind of products and services at the right time? Clearly, they have developed some kind of mechanism which helps them analyze a user’s consumption pattern. One of the advanced analytics techniques that uses both historical and new data to forecast activity, trends and behavior is Predictive Analytics.
This unique method applies analytical queries, automated machine learning algorithms and statistical analysis methods to data sets for designing predictive models that place a score on the probability of a particular event happening. Many sectors including banking are using predictive analysis to reliably project future behaviors and trends.
Talking about the banking sector, there is an increasing need to fulfill the expectations of a growing discerning consumer base, given the number of analytic tools available in the market. Banking industry needs to shift from using analytic insights to design exceptional report of past events, to applying this data to cherish remarkable customer experiences and associations based on future needs. And this is where Predictive Analytics comes into picture. It is the future of banking industry. With Predictive Analytics banks can forecast when a customer might look for a specific financial service solution.
So, let us have a look at some of the key areas in banking where predictive analytics can prove to be of value:

Customer first

Changing customer needs and market trends indicate that it is high time banking sector moved away from its siloed approach and focused more on what the customer wants. Predictive Analytics exhibits the power to strengthen the relationship with customers and builds trust, especially at a time when digital-natives are introducing customer-centric digital solutions and are progressively gaining foothold in the financial services industry.

Fraud prevention

The Banking sector needs to design solutions not only to save their capital, but also to save the identity of their customers. Cyber criminals remain on their toes to grab any single opportunity to commit fraud. Hence, banks need robust tools and intelligent systems to avert such problems. Predictive Analytics is an excellent way to identify instances of frauds that are not very evident and analyze them further.

Application screening

Application screening process has turned much easier with Predictive Analytics. Bank staff can process applications in bulk in lesser time and increased accuracy. Also, there is almost no probability of excluding important variables during this screening process using predictive analytics.

Customer retention

With growing competition, it has become extremely tough for banks to retain customers. Predictive Analytics works as a mechanism that can help banks know when an existing customer is looking to switch to its peers, and what could be the probable reason behind it. It is done by a comprehensive analysis of customer’s spending pattern, investment inclination and other interests, service performance, and past service details, among other factors. Once the problem area is identified, banks can take timely measures to retain their customers.

Cross-selling

Getting a customer is tough and retaining it is even tougher, but if banks have the right plans to grow the share of their consumer’s wallet, cross selling of other products helps. Using predictive analytics, banks can build models and assign scores to customers, to present the probability of the customer looking to buy another product. Eventually, this approach leads to increased revenue per customer.

Conclusion

The above benefits are just a fraction of what actually banks can achieve using Predictive Analytics. However, implementing Predictive Analytics needs high level of expertise and specialized skill sets with statistical methods and the knack to design predictive data models.

‘HANUMANS’ in Banking

‘Service is the mantra’, ‘Customer is God’. We come across these slogans very often in service industries. And banking is one of the most crucial services for any nation. For decades, bankers have enjoyed a great legacy and immense respect in society by virtue of working for a bank. For most of them, banking is the dream job.
Today’s banking marketplace is no less than a fish market, with multiple bank branches on the same street or even side by side. It is certainly difficult to keep up the momentum while staying ahead of competition. Though a bank’s brand drives its market share most of the time, it is the front-end bankers who drive both the bank and its brand to the extremes of either popularity or the lack of it.
In any product offering, customers will run towards the rewards or add-on benefits apart from the default product. However, this may be a different situation in the service industry. Most of the times, the service industry will drive through relationship rather than rewards or add-on benefits. This fits for the banking industry also. So a banker should be able to drive the key relationship factor with the customer.
Gone are those days, where one person had a specified role with a specific set of skillsets or knowledge to perform certain tasks. Even after computers replaced physical ledgers, those skillsets or knowledge continued to be cutting edge and banks used to spend higher amounts on retaining such talents. But with cut-throat competition, availability of larger number of resources, lack of other opportunities and global economic conditions, most of the unemployed are attracted towards banking. Even banks have started spending larger amounts on internal training.
‘Banker’ may be a very generic term, however, to be more specific we have teller, authorizer, assistant manager, branch manager, sales manager etc. Irrespective of a person or roles performed by him/her, the ultimate target expected out of any employee or banker is ‘profitability’ and ‘accountability’.
Profitability is the main target for any financial organization, perhaps it is a monthly salary for an employee but for an organization or a bank, it is an amount of investment they are making on a resource to earn a profit. So ROI (Return on Investment) is the obvious expectation from all the resources. Like before, doing a clerical job or posting a few transactions on core banking will not be counted as ROI. Banks are expecting their bankers to cross-sell some product or service on a daily basis to keep up the momentum and increase profitability.
Accountability is the other default expectation from any banker in various aspects. For a bank, it is a must and should have skillset. A banker should be able to take the right decisions at the right time for all transactions by keeping regulatory aspects in mind. He/she should be responsible towards adhering to the internal and external guidelines, especially by keeping the interests of the organization in mind, as much as possible. From a customer’s point of view, when a banker is acting on his instructions, one should also be accountable for secrecy and security of both the customer’s personal data as well as his wealth.
Today’s banking is driven by three different factors and in fact all of them are three different dimensions with respect to each other. Those factors are ‘sales’, ‘service’ and ‘compliance’. A banker requires a skill set to handle all three different dimensions accurately without losing the interest of any one of the key stakeholders with respect to each dimension. For example, when you are service oriented and trying to help your customers in the best possible way, one should not forego the internal compliance or regulatory guidelines. Similarly, when one is cross selling, it should not dampen one’s service or compliance requirement.
Apart from all of this, a banker should be up to date about all the latest happenings, especially competitor insights and digital channel preferences. Especially in the longer run, when a mobile app is able to service all the key requirements, a banker should be able to handle this change and be able to guide customers to switch to a digital mode.
Also behavioral skills are very important for bankers, since they service at the front-end and are subject to various pressures related to service or sales or compliance. Another important skill which a banker should possess is to learn new things or new work. As competition increases, a banker needs to have multiple skillsets and knowledge in order to perform all of the above given tasks. Multiskilling and scaling up to the next level at any time is required. This will also help in keeping yourself away from the redundant jobs which in turn might be taken over by a robot sooner or later as part of automation. So in a single line, a banker is expected to do any job or any role at any point of time and be able to perform seamlessly across verticals. Ideally banks require a character and attitude similar to ‘Hanuman’ in ‘Ramayana’ to perform any task required for a bank to scale it up further.
So any future ready banker must possess the above skills apart from regular academics, most of these skillsets will be learned by him/her as part of the day to day work. So future bankers should be ready to ‘strain’ and then ‘gain’.

Personal data everywhere?

Early morning, I received a call on my cell phone from a consumer finance company explaining to me some consumer finance/EMI offers. After a few hours, I received a call from one call center of a bank selling credit cards about life time free card with other offers. In the afternoon, I received a call from an Insurance company about some insurance offers and insurance tied with investments. These are a few calls each one of us typically receives on a daily basis. I don’t consider myself to be a high net-worth individual/very important person/person in the public domain to be receiving these calls so often. Obviously I have not registered myself in the “do not call” registry website and immediately felt the need to do it.
In the afternoon, I checked on to a web site of a travel company provider to look for some options for travel during holidays and these were very casual checks, not planned ones. When I went to another site using the same laptop/IP address, immediately popups for travel destinations I had looked up earlier appeared. Yet another instance was while trying to make a mobile payment – checking the quick payment options on a google engine search returned multiple results about relevant websites. I tried opening a website I had visited earlier and immediately my mobile number and mobile account number popped up without any registration or login. Since the earlier payment was through credit card, the entire credit card information except for CVV was auto-populated into the screen though I have not enabled autofill or saving of credit card data on any sites I visit. Though CVV is captured in encrypted format and credit card payments are further authenticated using multi-factor authentication techniques, this is still a grave concern to me.
There are other sites where one registers for making purchases/online shopping/ecommerce and the access could be browser based or through mobile. In most of these sites, apart from name and e-mail address, mobile numbers, residential address with PIN and other credentials are given. There is also an increasing tendency to source PAN details, Aadhar, KYC or other forms of identity details relevant to country which are shared for completing the registration process/formality. There is also a message to comply with KYC guidelines asking for mandatory documents to register users on many online shopping /establishments. In the urgency to complete the registration, we tend to furnish this information in an ad hoc manner without a recheck. People are also lured by the freebies /discounts being offered through the ecommerce platform for a particular event and are not sensitized by the confidential personal information being captured/shared.
A few social media sites are mediums where data once used/searched by an existing user gets stored and in seconds, the search data is shared or used by multiple other websites for sourcing some other information. Needless to say, there is an analytical engine running over these sites which enables collection of the data, analysis of the data, tracking the IP address and the next time when the user logs into a website it surprises them with the information one is searching. There is also a tendency to upload photographs/images, update of status by an individual for important events like birthday celebrations, awards and ceremonies or important places visited which could be misused.
The mobile numbers are possibly shared by service providers/agents of the companies to different sources with/without a fee. The data on mobile numbers possibly gets extracted secretly, gets shared with other like-minded companies and is used for calling purposes. Personal data is available on mobile/laptop and used/shared through the network making the data really vulnerable.
The extent of data that is tied to or associated with mobile/credit card/PAN/Aadhar is enormous. Some of the data may not be known to immediate family members but might be available to a select set of vendors/company, and is potentially at the risk of getting compromised for malicious intent.
The EU parliament approved the GDPR (General data protection regulation) in 2016 to harmonize data privacy laws across Europe, and to protect and empower the citizen’s data privacy. However, this is in a very early form and all citizens across the globe are susceptible to data theft/attacks/breaches in cyber world currently. It will take time to have laws framed in terms of controlling the data, sharing the data, protecting the data, using the data, processing the data and till that time, it is up to the individual to safeguard to the extent possible.
To conclude, with digitization and communication revolution rampant across the globe, an individual is vulnerable to a data threat/piracy of personal information – mobile number, card number, identification details, bank account number (in a few rare cases) and the like. Though there are in-built security measures for accessing sites and for conducting financial transactions that may require multiple authentication modes, the threat still looms and one needs to be wary of the information being shared in the cyber space. Till cyber security and protection reaches a stage of maturity where there is a collective rule/regulation encompassing the devices and websites with technology assistance for controlled data sharing and processing across countries/geographies, it is up to the individual to ensure adequate measures in using/sharing personal data over the web.

Building a culture of analytics for all

Knowingly or unknowingly, we all do analysis and decision making in our daily lives. It could be deciding whether to hit the gym, which doctor to go to, which school to put your kid in and even for that matter whether to reward a bonus to your maid or not. The only difference when it comes to corporate life, we somehow are trained into the habit of taking instructions and following the same.
Corporates are readily equipped to build analytics driven products, but to build an analytics-driven culture is not easy. Culture cannot be brought in from outside, it has to evolve from within. It has to be lived. We can start by questioning ourselves – is it there at my workplace? Are we enough curious enough to understand the what and the why of what we do on a daily basis at our workplace? No points for guessing. Yeah we are still not there.
Internal clients – “Ohhoh… I am always left out”
To put it in simple words, analytics means structured problem solving. Not many at workplace acknowledge in the first place that there is a problem at hand to think and solve. Most workplaces understand and are geared up to provide analytics solutions to their external clients. But what about internal clients and where does analytics fit in? Will try to put across by way of examples – Do we use decision models to decide which clients to pursue? What is the expected client traction for the current product roadmap? Was analytics used to determine which category of opportunities resulted in best results? Can I prescribe what product features are required if I expect a % of turn around? This is where leaders can make a difference and educate their internal teams to identify the problem statement and inculcate the habit of applying analytics in the daily jobs being done. Walk the talk is the mantra.
“Curious for data and knowledge… I might just burn my fingers”
Once we cross the first hurdle to bring the team on common line to identify the purpose of analytics at workplace, the next road block is when teams have to overcome their own perceptions and fears. Some f the common myths that teams hold are – “The data is not there “, “It’s a lot of junk data and results may not be accurate”, “I will lose the power if I share the data”, “it’s too time-consuming, and the cost required to analyze is way too much”. A lot of us ask the right questions but how many of us try to get the right answers? I think the best bet here is to simplify the problem statement and encourage all to find answers. Organizations must transparently reward people to encourage sharing and analyzing data. Once a few rewards are won and the process is in place, the skeptics start losing ground.
“Old ways are always the best ways… why are u disturbing the set up!!!”
Then the next hurdle, once everything is in place, is to implement the outcomes of analytics and to get the team to adhere to new processes. That’s when the trouble doubles up. At times mix and match of teams and cross-skilling can deliver surprising results in overcoming resistance. The changes may not necessarily be only in numbers or end results, but also in identifying training needs, staffing needs etc. Here team leaders and managers need to support the team by giving them the training required and should give a quick view into the results as well.
“Trust Anchor”
The quality of data driven decisions in itself acts as a trust anchor for everyone. Decision making process does not always have to be behind closed doors. It can be more transparent and should involve employees at all levels who embrace analytics. For example, base level employees can contribute to data collection and can apply the tools to come up with the diagnostics for the higher-ups to view. A sense of ownership and a view into the entire decision making process results in increased employee engagement. A data-driven culture evolves and matures through such engaged employees.

Cryptocurrencies – a fad or here to stay?

Cyptocurrency, a buzz word in the recent times has gained significant prominence since 2009 with the advent of ‘Bitcoins’. As most of us know, bitcoin was conceptualized by a person or a group under the name Satoshi Nakamoto. Following Bitcoin, many other cryptocurrencies have come into the market. These currencies work in an economy parallel to the existing economy which does not revolve around the Government, central banks, regulations etc. Cryptocurrency transactions are effected on block chain using the concept of a distributed ledger. Transactions are made secure using the concept of Hashing. The use of private key and public keys allows the transactions to be discreet.
In the absence of a regulatory body, these cryptocurrencies give a free hand to transact. The transactions are hashed and the private key concept makes the transaction viewable only by the recipient. The transactions are difficult to track. Due to no monitoring or guidelines, there is a concern that these currencies could be used for activities such as money laundering to evade tax, and other kind of frauds. Many countries / Central Banks across the world have either warned or banned the use of cryptocurrency. In the recent union budget 2018 in India, cryptocurrency has been classified as ‘not a legal tender’. But this has not deterred people from transacting in cryptocurrency. Cryptocurrencies have a high market value making them an attractive investment option. With the investor interest cryptocurrencies have enjoyed so far, one wonders if the cryptocurrency market has already reached a saturation level, and if it is advisable to make investments. With the volatile situation of cryptocurrencies, it may turn out to be a risk to invest given that regulations are not uniform across the globe.
Central Banks can look at considering cryptocurrencies as regular currencies and the cryptocurrency transactions as any other digital transaction. Just as multiple different currencies exist across the world with each country having its home currency, cryptocurrencies can exist in parallel to regular currencies. Central Banks can formulate guidelines to bring about regulations for the cryptocurrency market. There are advantages of having co-existing virtual currencies. Some of them are – cost effectiveness due to the complete digitalization, the market value of the cryptocurrencies gets regulated thus protecting the interests of the people. With regulations in place by the Central Banks, fraudulent transactions can be tracked and monitored. The underlying blockchain technology ensures that the transactions are more secure. Ultimately it becomes people’s choice whether to transact in regular currency or in cryptocurrencies. Also, if the cryptocurrency market is regulated, untapped population may invest / transact in cryptocurrencies.
The debate about whether cryptocurrencies are here to stay is on. The future for cryptocurrencies looks uncertain. And with their growing interest and popularity, how Central Banks will handle the volume of cryptocurrency transactions, is also highly unclear. At some point, a uniform and consistent decision on whether to accept or decline cryptocurrencies needs to be made across the globe. Varied stance and disparate policies across the world only serve to cause confusion and make people vulnerable to risk and fraud.