The new era of banking: Pivoting from transaction to engagement

Monday, 3 March 2014 01:56 -     - {{hitsCtrl.values.hits}}

Key insights into big data and analytics from IBM By Kinita Shenoy In conversation with the Daily FT, Ajit Nair, Director of Banking and Financial Markets, IBM Asia Pacific and Chrishan Fernando, General Manager, IBM Sri Lanka discussed the nature and promise of big data and analytics, as well its impact on the banking, financial services and insurance sectors. A concept still new to some sectors, big data has nonetheless made its way into common parlance and business practice. Popularly defined as the exponential growth and availability of both structured and unstructured data, its implications on modern business are vast, helping organisations better understand their customers, partners and regulators. The banking industry relies on information on their vast number of transactions in order to better track trends in customer behaviour and needs, with over 71% of banking and financial firms surveyed by the IBM Institute for Business Value reporting that the use of big data and analytics gives them a competitive advantage. In his role as Director of IBM’s Banking and Financial Markets in Asia Pacific, Nair works closely with client teams in the various regions of the IBM Growth Markets. His priority is to assist large financial institutions in their transformation by forming strategic partnerships with IBM to deliver business outcomes that significantly improves their performance metrics. In this role he shares IBM’s insights on how best in class financial institutions have achieved superior performance compared to their peers. He also collaborates closely to bring the right IBM skills, capital and experience to help key clients scale their operations while improving efficiency and achieving higher levels of transparency. Following are excerpts: Q: How can banks leverage big data to gain a competitive advantage?   Nair: In the past, banking has been behind many other industries such as retail, which have been very savvy at leveraging data. The reason for that is banking has been very transaction-focussed. They create products and then put them forward to the consumer. However, industries such as retail, travel and hospitality start with the customer first. When they gather data it’s not just transactional data which is often static but increasingly looks at client interaction. A lot of data today is unstructured, especially via social media such as Facebook and Twitter, but valuable insights can be gained from this ‘chatter’. For example, what are consumers saying about banks, what kind of products do they like, what are their needs! Thus, big data is all about the ability to leverage both structured and unstructured data to get insights. The competitive advantage that big data provides is based on client insights. Those that are able to get innovative and leverage this data will benefit greatly. Furthermore, banks are now seeing the value in big data as the face of banking changes completely from branch-centric to personal gadget-centric. It is self-serving for banks to become more innovative, create more offerings, make engagement easier, and delight clients with the best services. It is simply addressing the reality that the customer is empowered, in control, and has a lot of choices and channels. Some of these trends are more entrenched in other markets more than Sri Lanka, but time will level this. Q: What kind of analytics help organisations go from unstructured data to valuable insights? Nair: Analytics and cognitive systems are both at play.  While analytics helps gain intelligence out of data, the explosion of data now available makes it impossible to write enough programs that would be able to analyse all of it. So the future lies in cognitive systems, which learn as they engage with the data. Cognitive systems such as the IBM Watson system are used. The Watson system was first used in the medical field to help oncologists with diagnoses of cancer patients. However, we now have a couple of pilot system with banks, where Watson is now helping them develop insights of their high net-worth clients and help wealth advisors with what would be the right kind of offering for their clients in a much faster method which would be able to make valuable recommendations by analysing massive amounts of data. Q: What are the prevalent big data/analytics trends in the global banking sector? Nair: Banks were more insular in the past, more focused on themselves, their branches and products. Banks are now going to be a lot more customer-centric, creating offerings that put customers at the core, with individualised products. For example, the navigation system of ATMS will be customised to an individual’s usage pattern. The client is now empowered, and will be at the centre of the bank’s processing, which will create a lot of channels in terms of client interaction. As customers now rely on their personal tablets or mobile phones to carry out their banking services, the bank itself is no longer at the core of the transaction or relationship. The reality of the future is going to be heterogeneous as one client could use more than one channel. Thus, the focus is going to go from ‘how do we transact with the client?’ to ‘how do we engage with the client?’ Collaboration with clients is now key as customers can switch to another bank with ease without losing any benefits, and are no longer dependent. Decisions like this are often made on social media peer recommendations and reviews, which means that banks need to learn to engage with millenials and younger people, as they are making up a growing section of their client base. Q: What is IBM doing for the banking, financial services and insurance sectors? Nair: IBM has been continually rebalancing our offerings in growth areas by investing heavily in areas that are relevant and important to our clients. Apart from big data, analytics, and cognitive systems, we believe that banking has to become a lot more flexible and nimble, for which cloud networking is extremely important. Previously, a lot of investment was needed to launch a new financial service. But today the barriers are going away and a lot of new entrants are present. We believe that with new technologies like cloud, anyone can start a service that may be attractive to many clients that previously had to rely on banks. So banks have to be a lot more responsive, faster, and price competitive. Cloud started off with increasing economies of sale and standardising offerings, but has now evolved into ways to offer a more attractive business model, with the ability to create more services which would otherwise be too difficult or uneconomical to deliver. Q: Do you find that being part of a more traditional industry, banks are slow to adopt these new technologies? Nair: Compared to other industry sectors, yes banks have been slow. But there are valid reasons for that. There are a lot of regulations in banking as compared to other industries. Compliance for example is extremely important, with a lot of rules surrounding data privacy and security. Many central banks have regulations regarding taking data out of the country, and the privacy and confidentiality of its citizens. Thus adoption in banking has been more cautious than other quicker-evolving industries such as retail and manufacturing. Business models that are nimble and economical are attractive, creating the platform for new services and innovative ideas to mushroom. We believe that the model is going to be a hybrid; not a homogenous model with everything existing on the cloud. Banks need to look at the applications and offerings they have, and which ones will be in the data centre, which ones will be in a private dedicated cloud with a vendor to run it, or a public cloud. The time it takes to set up depends on the project itself – the innovativeness of the bank and the areas they have targeted. Q: What is IBM’s strategy in Sri Lanka? Fernando: With a presence in Sri Lanka since 1962, IBM’s biggest thrust has been the banking and financial sector. We have worked with all the banks and financial institutions in Sri Lanka, maintaining almost 99% of the mission critical banking environments in the country. Our strategy is to take them to the next era of computing – cognitive computing. I believe that the relationships built up over the last two eras of computing will help us partner these institutions into concepts like cloud and analytics.  Our first customer was the Sri Lanka Insurance Corporation, whom we set up here to serve and still have a proud unbroken relationship with after half a century. Almost all Sri Lankan banks, whether state-owned or private, have IBM systems. We’ve also embarked on some new areas of IT and computing with banks in the last couple of years. For example, IBM is implementing Hatton National Banks’ ATM switch solution. There’s also a lot more in the pipeline in the near future. In fact, Ajit’s presence in the country is to help launch the third era of computing to the banking industry. So far, we have seen tremendous support from the board levels to embrace the new technology and become more customer focused. Q: What do hope to achieve in your current visit to Sri Lanka? Nair: A lot of trends in banking can be pervasive, and applicable to any market. One of IBM’s advantages is that globally, the banking and finance services sector has been one of its key areas. Having worked with banks for many decades, and our focus area and segments are very large. Some of the perspectives we have are based on the cumulation of interactions with banks all over the world, and which we are happy to share with individual banks. Furthermore, customers are keen to listen to IBM because of our experience with a variety of sectors. Previously, there was an insular attitude that other industries processes were of no interest. Now however, it is important to learn what the best practices are in other industries. While banking is advanced in some areas, such as self-service, other industries such as manufacturing are brutally efficient, with their ability to squeeze out cost from the supply chain. So banks must learn to think like retailers and act like manufacturers in order to be integrated enterprises. Banks’ biggest expenses involve maintaining legacy applications, whereas manufacturing has gone way beyond that and spends most of their money on research and development of new innovations that will bring costs down. Retailers on the other hand are great are predicting client wants by looking at spending patterns and other data, before the customer even expresses it. Banks also need to look at risk not only in broad terms but at the risk of individual clients and projects. The financial crisis saw banks in trouble because of their inability to assess the impact of individual risk on the holistic picture. These are issues that big data addresses.

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