Data and Banks: What works -Dams or Bottles?

Pratima H

INDIA: What will happen to Fast-and-Furious sequels? Where would that hard-earned driving license go?

The interpretation of Self-Driving cars seems to depend on who they affect. So the question for someone from Technology space would be different – if intelligent cars do pour onto our roads, what would happen to all the metal?

They are right. We are talking of vehicles where hardware will cease to be the 70 to 90 per cent of a car's constitution and value. Software is going to take over – think of in-car content, on-the-move cloud for data, C2X apps, personalisation services, content, telematics, sensors, vehicle-to-vehicle communication etc. and it’s not hard to imagine how hardware is going to be relegated to the background in a place where it was utterly implausible – a car!

But people in the data and storage space aren’t too bewildered watching steel being mercilessly replaced with code. They have already dealt with the blows that Software-Defined-Everything has wrought upon this space in the last few years.

Data has moved from hardware enclosures to software ether, and at a brisk pace at that. Most industries have followed this de-tour. But when we think of BFSI, have banks been able to keep up? Specially when security mishaps like POS frauds, EMV migration hassles and demonetisation’s hangover attach a brick to every step they take forward?

What about old-school banks? What about the effort of handling the data potato for regulators as well as for business users – when one needs it boiled and the other needs it sliced and fried.

What about it – asks back Vinod Ganesan, Director Sales – BFSI, Hitachi Data Systems. He recommends buckets, lakes and a grip on the ‘whom for’ when it comes to data. Like he says - if you torture data long enough, it starts to confess.

Let’s allow him to explain that in detail.

There is a growing shift to software in this space – as much as 70 per cent by 2019 as some analyst firms have augured. How does this new composition-mix translate for players like Hitachi?

The industry continues to evolve. As customers change, we too need to re-invent ourselves. Data was a pretty manageable asset for many years. But from 2000 wherein 25 million devices were talking to each other, to 2010, when it became a landscape of 250 million devices and now we can expect anywhere around 35 billion devices by 2020 – we have seen this world gallop towards exa-bytes and zeta-bytes very strongly. All this humongous data being generated, which also can’t be managed by humans alone, means a lot of things. How to make software more intelligent so that customers deal with only relevant data – for instance. We would have to move carefully and not fall in the 'one size fits all' trap.

When you say devices, how ready are we for fog computing/edge computing in reality – specially in India?

The capabilities in this side are being offered but skill-sets do not form a mature pillar here. So there is a going to be a huge demand for specific skill-sets. In India, the space will grow at its own pace because of limited proliferation for the same reason – not enough skills.

Software and hardware are indeed striking a new interplay. How radical and relevant is Open SDS?

Take the example of payment space. At the end of the day, all offerings have to work with a focus on seamlessness. With the rise of smartphones and apps, banking transactions are undergoing a new wave. If some banks are offering feature-rich services or their own wallets, it's a new shift. But what about the inclusion question again? That's where the beauty of Aadhar and innovations around this would surface. Suddenly, we can see how even a shop-keeper from a village can partake in the loan space by displaying his credit-worthiness and how banks can access his cash flow for lending criteria. Such transformations would need innovation with an open-orientation.

Vinod Ganesan, Hitachi Data Systems

Also, we have seen lot of new terms dotting the scene – converged, hyper-converged, cloud-ready – but not all workloads are the same. Placing data in the right bucket is important. No one size fits all. The cost-to-efficiency ratio has to be looked into. Irrespective of what technology or platform is in the buzz, we provide all capabilities and the highest level of functionality. That is surrounded with scale and flexibility.

Has data stepped up to the revenue-centre-respect rung?

Data is clearly one of the key assets for banks. Like it's said – if you torture data long enough, it starts to confess. Data, so far, was trapped in different silos. The need of the hour is a computing architecture that can truly mobilise this data. And then we need a framework of governance. Data that is no longer tied to the core but is fluid and freely available to users – that’s the new way.

From what you can see from your vantage point, what would you say has particularly changed in the BFSI space in the recent past?

As per a KPMG report, the Indian banking industry is growing to be the fifth largest by 2020 and even the third largest by 2025. If you look at 2016 specially, it has been a specifically-challenging and action-packed year for this industry here. From the traditional challenge of more financial inclusion, that saw a new shift this year, to of course, the impact of demonetisation; 2016 has been huge. Banks experienced a cash challenge but senior executives handled the scenario and soon we saw a palpable shift to digital side. So, obviously technology has been at a fore-front in this industry.

What about challenges around technology per se that banks have to deal with – like what we have witnessed with POS frauds, changes with EMV, Blockchain breach or worries around Robotics? How much do security and compliance affect adoption curves?

There is a fine balance to everything, more so in a highly-regulated industry like BFSI where banks have to ensure the right balance. Yes parallel technologies are on an advent. Whether it is DBS, HDFC, ICICI, YES bank – and apps, bots, AI - banks are looking at new technologies aggressively. Yes, there have been security breaches like the POS one but these are unfortunate incidents. Risks will be there but they do not deter technology adoption.

Is this pace of adoption going to be as easy for legacy banks too - those with old-data monkeys on their backs?

We are entering a bi-modal era in many aspects. Despite new data across social platforms, apps etc., the legacy data still has to be used and tackled smoothly in roll-outs. That's why banks need to devise innovative ways and that explains the rise of CDOs (Chief Digital Officers). Legacy core modernisation, building interfaces and on-boarding new assets – that's going to be challenging but has to be done. Digital players may have a head-start and PSU banks may have some challenges due to intensive RFPs and processes. There can be a relative delay but everyone is going to be part of this new world.

So what would be the biggest challenge that banks face in this new data-defined world?

Analytics. Banks have been the earliest adopters of data warehouses but most would admit that this money was somehow not well spent. Ingesting data from multiple sources is not easy. Then there was the painful process of extract-transform-load too. By the time data was delivered to business, the latter's requirements had already changed. Data warehouses, hence, did not meet expectations.

Today, the world has moved to data lakes. This is where both unstructured data as well as historic and also real-time data can co-exist. We are helping banks in this new transformation. The regulatory side for banks will stay stringent and with so many reports required, and so many copies to be maintained; the dicing and usability of data for business users becomes all the more challenging. How can I create one unified framework – one common repository where anyone can find the relevant data in their format of use? The less time banks can spend on auditing and reporting, thanks to technology, the more they can devote it to innovation.