Blockchain Leaves the Lab

Pramod Krishna Kamath, Lead Product Manager, Infosys Finacle
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2016 saw banks engaged in a frenzied race to explore blockchain and pilot applications based on the technology.  Their efforts are yielding early indications of what a blockchain enabled future might look like. A race to production is now well and truly underway.There is now consensus amongst banking and technology leaders that Distributed Ledger Technology (DLT) has great potential to bring in simplicity and efficiency in multiple business processes.

It is clear that DLT is one of many new technologies that will form the foundation of next generation banking. Cognitive Computing, Machine Learning, Cloud, and Robotics, alongside DLT, form the technology toolkit that will define the next evolution of financial services.

Transformational Potential

The transformational potential of DLT lies in its elimination of the need for individual books of record. As records cannot be changed once written, there is really no need for a custodian of trust in the ecosystem. Immutable data, which is distributed across participants in real-time, ensures that they reference and operate on a single version of truth.  This alone has the potential to significantly increase transparency between market participants. As regulators can also participate in the DLT ecosystem, they can effortlessly access transactional data on demand. This can bring down banks’ regulatory compliance costs as the regulators can access data in a frictionless manner, in real-time.

Financial institutions stand to benefit greatly from blockchain and similar technology. The distributed ledger can automate legacy processes and thereby eliminate the need for reconciliation. It can also improve inter-entity processes that suffer from inefficiencies as a result of a lack of trust. A major benefit of blockchain is the smart contract, which is based on “shared trusted” processes and contractual terms that are enforced automatically upon fulfillment of certain conditions. This greatly reduces counterparty risk in any transaction.

Legacy processes typically need intermediaries, who add to inefficiency and cost.

In contrast, processes running on new technologies, such as blockchain, not only bring down liquidity costs but also improve working capital management.

That’s not all. Because the record of blockchain transactions cannot be tampered with, the transactions are protected against fraud. Last but not least, by forging direct, peer-to-peer connections, the technology eliminates the need for intermediary chains and a centralized supervisory authority.

Applications 1.0

Banks are approaching use cases based on whether they optimize cost or spawn off a technology-enabled new business line. Pilot projects show that opportunities exist in both areas.

Use cases abound in all three primary domains of financial services, namely, retail, trade and capital markets. While capital markets represent the biggest opportunity simply because of the value of traded assets, it might take four to five years for the use cases to hit production. This is because of the nature of the ecosystem, where all participants in the value chain, from Stock Exchanges to broker dealers to Asset Managers and Custodians, must agree to a common approach for the real benefits to kick in.

On the other hand, retail and trade finance use cases offer a much more realistic path to production. Remittances and trade finance, in particular, have some notable characteristics that make them very suitable for blockchain adoption: both represent significant revenue pools for banks, have processes that suffer from friction, lack a central counterparty, and have cost-and-inefficiency-creating intermediaries.

In both these areas, banks are already seeking to subvert intermediary costs (e.g. SWIFT) in high volume bilateral relationships. Today, they are doing this through peer-to-peer direct host connections between banks, typically implemented using custom protocols. Peer-to-peer custom arrangements are however not scalable beyond a limited set of partner banks and hence the efficiency gains are limited.

DLT democratizes these bespoke arrangements and enables banks to expand their partner network relatively quickly and with a standardized protocol.

While quick win applications do exist, the most impactful applications require a greater degree of collaboration between banks, technology providers and also regulators. Aligning competing interests to a common purpose, especially in the case of market competitors, is a key challenge. The good news is that regulators across the board are showing a growing appetite for DLT-enabled processes. Regulators in India, Dubai, Singapore, Japan, U.K. and Russia are studying the technology closely and working with leading banks in their respective regions to examine practical implementations.

In the latest edition of the Infosys Finacle – Efma “Innovation in Retail Banking” study, 61 percent of the banks said that blockchain/distributed ledger would have an impact on emerging retail banking business models in the next three to four years.

Progressive financial service institutions are already on board with Blockchain and are partnering with technology providers to improve current business processes and experiment with new technology-enabled business models. 2017 will be the year when Blockchain projects come out of the innovation labs and make their way into production, enabling banks to address real-life problems, albeit in a small way and in simpler use cases.

Banking on analytics in 2017

Venkatesh Vaidyanathan, Vice President, Product Management & Analytics, Infosys Finacle
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From a sluggish economy to disruptive digitization, banks have managed to survive and evolve along with the current environment. Most of it has been possible due to progressive banks showing the way and adapting to the environment for a truly digital transformation. Of all the major trends for banking transformation, analytics has made a consistent appearance year after year; and it is no different in 2017. As the hype surrounding big data and analytics has matured, banks are looking at ways to implement technologies to be more effective in terms of return on investment (ROI) and business value generated from analytics.In the past year, there has been an unmistakable shift towards fast & real-time data and its adroit management. Skillful manipulation of data has become more important in this day and age of rapid digitization and fast-paced consumer lifestyle.

Banks now have clarity in terms of where and how to use data; and this focus in terms of analytics implementation will be the foundation for disruptive technology, such as artificial intelligence (AI), internet-of-things (IoT) etc.

It is evident to banks that as data moves from being descriptive to prescriptive, a competent execution of an enterprise analytics strategy is required to leverage technologies for a complete banking transformation.

Analytics has become pervasive across all functions within an organization and there has been a definite move towards its democratization – i.e. all employees within an organization, partners, and customers get access to insights acquired from analytics. This in turn will allow organizations to serve their end-users better and create unparalleled business value.

2017 and beyond will see big data and analytics interweaved into every level within an organization.

These key factors – consumers, technology, and insights for all – will be the drivers for the next wave for analytics implementation in banks:

Consumer expectations and technology advancements will drive banks’ analytics investments

As a result of the rapid digitization, consumers have become used to a fast-paced life and they expect personalized, contextual products or services instantly. The challenge that banks face at this point is that they can no longer depend on descriptive or diagnostic analytics to dwell on the whys. Now banks have to shift their focus towards the “hows” and use fast and real-time data that can predict the consumer journey and provide its consumers with relevant products or services.

With the latest technology in the form of AI or smart devices banks can look to provide personalized consumer experiences based on context and life-events to please even the ficklest consumers.

For example, imagine a banking application that understands consumers, their expenditure patterns, saving habits, and social preferences; now imagine this app will also provide a comparison between similar demographics and provide financial advice based on this comparison. This kind of tailored customer experience is now made possible, built on the foundation of analytics and will provide banks with an unbeatable competitive advantage.

A simple use-case for personalized customer experience may be in the form of banking apps that most millennials access from their mobile phone to carry out payments and other transactions. When a user logs in, analytics helps the banking application understand what the consumer is most likely to do, and creates a user experience on-the-fly that is optimal for this consumer at this point in time. This would be based on machine learning algorithms powered by predictive modeling, understanding the consumer’s financial habits, as well as social preferences.

Themes based on personas can be another use case for analytics implementation for customer experience.

Analytics helps with understanding the life events of consumers. This is used to determine the optimal user experiences for them at a certain point in time.

For example, customers with college going children would see themes based on savings for higher education, whereas getting married would see themes related to travel and vacations.

Technology will be powered by analytics

It has started to dawn on banks that while analytics offers valuable inputs to humans for business decisions, there is a certain section of technology that benefits from it as well. And insights powered by data and improvement in automation have made sophisticated AI technology easily accessible – more so for institutions that weren’t able to implement it initially due to lack of internal resources and dearth of R&D skills. With analytics and process automation as the driving force behind it, the modern AI platform has the ability to transform traditional banking institutions for the digital era. Progressive banks are already looking to effectively leverage data and advanced analytics modeling that will put them in a position to capitalize on newer technologies such as machine learning and automation.

For example, Wealthfront utilizes AI capabilities to understand how consumers are investing or spending, and then provides pertinent financial advice to them. Sentient Technologies continuously uses AI powered by insights to create investment strategies for users. Banks such as RBS have implemented AI in the area of customer service in the form of Luvo. It is a smart assistant that supports service agents who are answering customer queries. Luvo can search at higher speeds through a database to provide faster answers; it can also continually learn over time from gathered data to be more efficient with each interaction.

Banks also have to be aware of the fact that it is not only the internal processes that need a facelift in the digital era.

With the number of smart devices flooding the market, there will be an increased need for newer model-driven analytics implementations.

As the number of consumers with connected devices increased, banks will get access to more data than ever. This, in addition to the payments data arising from a decided push towards cashless economies, will make it an imperative for banks to implement a unified analytics strategy across all functions.

Insights for all – every time, everywhere

Till recently the insights derived from data were available to only the top management. But with changing customer behavior and technology that is driven by data, it is important that data is made available to all for optimizing internal as well as external processes. If banks want to cultivate a culture of innovation with analytics, it is important that they implement an enterprise analytics strategy. This in turn means that everyone should be provided with significant data management capabilities, and a talent base within the organization that will assist in deriving insights from data. For example, a few bank leaders came together to find solutions for difficult policy issues through a crow-sourced effort to use new data sets. The Bank of England has hired a Chief Data Officer, and has established guidelines around the instatement of an advanced analytics group and a bank-wide data community within the organization. It has also created a data lab to understand how these various streams of data can be combined to form actionable insights.

And it is not only internal processes that can be improved with analytics. A case can be made for making analytics capabilities available for customers too. US Bank’s Payments division had created an application, InfoApp, that allowed their small business customers to analyze their expenditures and other corporate payments. It provided the small business owners with a consolidated view of their finances, as a result of which this app was an instant hit.

This just goes to show, how democratization of analytics is just another avenue for providing a differentiated and personalized customer experience; and this in turn allows banks to stay relevant in today’s digital world.

Even though the consumers, technology, and insights for all are the key factors for driving success with analytics, banks will need to understand that the ultimate goal of any analytics implementation is to simplify the consumer’s life. To do this efficiently, all these initiatives will have to apply analytics models to create seamless connections between various solutions. A good example of this is Uber that has managed to integrate data obtained from location apps, real-time pricing analytics, and payment interfaces to provide a frictionless transportation experience.

2017 will be the year when banks will look towards gaining the competitive edge through investments in big data and analytics. While previously the cost of investment was one of the barriers for enterprise wide analytics implementation, it no longer is the case with open source technologies, such as Hadoop. As these open source stacks bring down the cost of investment, banks will start to see effective ROI with these investments in analytics. But it does not end with investments in analytics alone; banks will have to cultivate a robust, analytics driven culture within their organizations and foster a bent of mind that will be insight driven. The success of these implementations will of course depend on the competent execution of technology, employee empowerment, and democratization.

Blockchain – It is time to move from hype to reality

Indrani Mantripragada, Product Marketing Manager, Infosys Finacle
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2008 marked the introduction of bitcoin, and with it the emergence of the underlying technology – blockchain. Since then, not a day has passed where there has not been an intense debate on the potential of blockchain in banking – be it at a conference, webinar, social, or digital platforms. These debates have made their way to the board rooms of both, global and regional banks.

According to World Economic Forum, more than ninety central banks have engaged in distributed ledger technology discussions worldwide.

Ninety plus corporations have joined a blockchain consortia, and more than 2,500 patents have been filed in the last three years.

All these debates and discussions have created a huge hype around blockchain. But the ground reality is a bit removed from this hype and has a more measured approach; while banking technology leaders are convinced that blockchain will be foundational for the future of banking, few have found answers to questions surrounding the practical implementation of this technology. The joint research by Infosys Finacle and Let’s Talk Payments (LTP) (surveying more than hundred business and technology leaders from over seventy-five financial institutions) was conceived to answer all these questions and provide some clarity to banks looking for a blockchain adoption strategy.

In the following sections we expand on the details of our research:

Invest, invest, invest

While 50 percent of the respondents in our survey indicated that they are waiting for the technology to reach a more mature stage, about 35 percent identified business cases for blockchain that are suitable for their organizational strategy and are looking to invest in the near future. About 15 percent, who are classified as true innovators, have already started blockchain initiatives in full scale with either dedicated teams, or through partnerships with technology startups or companies. Investments in blockchain projects in 2017 is expected to be US$1 million on an average.

Innovators have already invested funds over US$10 million to support blockchain initiatives, and also explore use cases beyond the traditional realms of cross-border remittances, clearing, and settlement.

Many banks are still exploring how to effectively use blockchain to leverage its benefits that are relevant to their business. It is in the banks’ best interest to start small, experiment with the technology in a controlled environment to discover the value it can add to their business; and only then commit towards production deployments. An example of a successful blockchain pilot is the one implemented by ICICI Bank Limited, India’s largest private sector bank by consolidated assets, and Emirates NBD, the leading banking group in Middle East, using the EdgeVerve Blockchain Framework.

Preferences for adoption – Private blockchain vs partnerships

Banks have the option of choosing between public, private and hybrid blockchain for adoption. The public model completely decentralizes the consensus process, allowing anyone to join the blockchain network. Hybrid is the intermediate type of distributed ledger, seen in consortiums where the consensus process is controlled by a preselected set of nodes. Finally, the private blockchain allows the bank to define and restrict the rights to few users.

Our research only reiterated the most popular blockchain adoption methodology for banks, which is private permissioned blockchain. A clear majority of 69 percent of the banks were in its favor.

This seems to be a natural choice as the security of customer and transactional data is paramount for banks. Private blockchains also provide an added advantage of greater flexibility, dependability, and adaptability compared to public blockchain infrastructure. About 21 percent of banks are choosing to adopt, or planning to rather to go forward with hybrid blockchain. But with the operational risks and security concerns, it does seem that private blockchain is a safer option.

Another popular choice for blockchain adoption is the partnerships route.  About 50 percent of banks are either working with a fintech startup or technology company to augment their blockchain capabilities, while another 30 percent are opting for the consortium model. This is a good option for banks that are burdened with legacy technology infrastructure and lack in-house talent required for blockchain implementation.

Commercial adoption will be a reality soon

The World Economic Forum (WEF) has identified blockchain technology as one of its six mega-trends in a report aimed at defining the impact of software advancements on the digitally connected society of today. In this survey, 58 percent of the respondents expect that 10 percent of global gross domestic product (GDP) would be stored on a blockchain by 2025. However, the groundwork for commercial blockchain adoption will be laid out much earlier.

According to the Infosys Finacle – LTP blockchain report, one in every three banks expects to see commercial adoption by 2018, while 50 percent of the surveyed banks expected to see commercial adoption only by 2020.

2017 will see a race to production among progressive banks, albeit in a small way and for simple use-cases.

Priority use cases and the logical way forward

The top use cases chosen by banks for implementation include the usual suspects, such as cross-border payments, digital identity and clearing & settlement. These are closely followed by line of business use cases like invoice management and letter of credit, and these use-cases round out the top five blockchain implementation priorities for banks. However, as with any technology implementation, banks will have to move forward judiciously.  Banks should take into account their current business requirements and map out the areas where blockchain can help. Based on the outcomes of this research, banks should create an objective roadmap for blockchain implementation. It is important for banks to consider the fact that while blockchain offers a lot of opportunities in cross-industry and cross-functional collaboration, it is up to the bank to determine the area where blockchain fits best in their transformation strategy.  We believe that only after banks have taken all of these factors into account, they should initiate efforts to apply the technology in real-world processes.

The research has helped us to lay out a logical progression plan of use case implementation as shown in the diagram below. The first use cases that will see the light of the day in the next couple of years are intra bank use cases, or use cases, which can be tested with incumbent inter-bank relationships. These are most likely to be in the common areas of digital identification and cross border payments.

The next 2-5 years will see more of inter-bank use cases, and cases that involve regulators – such as trade finance.

Beyond five years, there will be widespread adoption of this technology in the financial services and banking ecosystem. By 2020, the adoption of blockchain based applications will increase in several businesses outside of the financial services industry. The larger part of the ecosystem adopting this technology will include players like the government, corporations from other industries, and possibly even end consumers. It is at this point that the true potential of blockchain technology will be truly realized as a key driver for business transformation.

Based on the findings of this report, it is no longer a question of whether banks will adopt blockchain; but more of when and how they will implement it. This research reaffirms our belief that banks must experiment with the technology in a controlled environment, in the form of pilots, to discover the value it can bring to their business. Banks should take measured steps based on the outcomes of these pilots to commit towards production deployments for blockchain. We hope banks will find this report insightful while crafting their organization’s blockchain adoption strategy.

IoT in Banking – Enabling Banks’ Digital Future

Ethan Wang, Product Manager, Infosys Finacle and Pramod Krishna Kamath, Lead Product Manager, Infosys Finacle

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Banking on Things

IoT is the interconnection of uniquely identifiable embedded computing devices within the existing Internet infrastructure. IoT is expected to offer advanced connectivity of devices, systems, and services that goes beyond machine-to-machine (M2M) communications and covers a variety of protocols, domains, and applications. In the financial services space, the interconnection of these embedded devices is expected to usher in automation in several legacy processes.

As IoT led digitization begins to take root, new business models and products are emerging. This is opening up new frontiers of innovation that can potentially reshape customer experiences, and throw up clear winners or losers in the financial services sector.

IoT Use Cases – Shaping Banks’ Digital Future

IoT has the potential to impact traditional business processes in banking such as KYC, lending, collateral management, trade finance, payments, PFM, and insurance. Coupled with other emerging technologies, such as digital identity and smart contacts, IoT can create new P2P business models that have the potential to disrupt banking in a few areas. Listed below are 12 use cases that may be adopted in banking in a time span ranging from near-term to long-term.

#1 Account Management on Things

As more devices acquire digital interfaces, the term “mobile” or “digital” banking will acquire new meaning and customers will be able to access their bank accounts from practically any “thing” that has a digital interface – for instance, from entertainment systems in autonomous cars or planes.

Banks will be aware of the context of the channel and can provide appropriate contextualized service or advice enriching the interaction experience. Biometrics – voice or touch – can simplify account access in these new “anywhere” digital channels. Processes requiring physical signatures could use “Wet Ink” technology, i.e. The customer can remotely sign through any touch screen device and the signature can be cloned onto physical paper with “Wet Ink”. This will eliminate barriers associated with in-person, paper-based transactions and enable clients to conduct business even when they cannot be physically present.

#2 Leasing Finance Automation

Real-time monitoring of wear and tear of assets as well as metrics like asset usage and idle time could provide important data points for pricing of leased assets. This could lead to introduction of a new daily leasing model for a wide variety of digitally enabled assets – effectively turning even traditional products into services. Terms of leasing could be simplified and automated as the bank wields greater control over the leased asset. For instance, in case of contract termination or default, the leased asset could be locked or disabled remotely by the bank.

#3 Smart Collaterals

IoT technology can enable banks to have better control over a customer’s mortgaged assets, such as cars, and also monitor their health. In such a scenario, a retail or SME customer could possibly raise short-term small finance by offering manufacturing machinery, cars, or expensive home appliances as collateral. The request for financing as well as the transfer of ownership could be automatic and completely digital. Enabled by digital identity for people as well as things, the transfer of ownership of an asset can be achieved in a matter of seconds. The bank can then issue the loan immediately, and monitor the collateral status in real-time without the need to take physical custody of the asset. The bank can remotely disable or enable the machine/motor anytime based on defined business rules. For instance, in case loan EMIs are not paid, the engine could be disabled. The quality of the collateral can also be monitored in near real-time.

#4 Automated Payment through Things

When moving on to payments, integration of IoT and payment functionality will lead to greater number of payment endpoints.

Beyond the clichéd milk ordering refrigerator, we are already starting to see the beginning of the use of connected devices and wearables, for instance, payment through Apple Watch or the fitness band Jawbone. When machines are able to perform transactions with machines in real-time on a marginal cost basis, the traditional concept of payments will become obsolete in many use cases as transactions become automated and integrated into other services – virtually any “thing” could include an automated payment experience. Though the IoT raises certain security concerns, personal biometrics and digital identities could potentially increase security in payments, if done right. Eventually the opportunity extends not only to the end user, for whom automated payments will lead to greater convenience and smarter transactions, but to banks, payments companies, retailers, and technology manufacturers.

#5 Risk Mitigation in Trade Finance 

Tracking of high value goods delivery using RFID is already reality in the trade finance space. IoT will accelerate this to include fine-grained tracking of the asset, for instance, monitoring temperature of the container for shipments involving temperature sensitive goods such as pharmaceuticals and medicinal molecules. Alerts could be triggered if there is a chance of spoilage during the shipment process – say one of the parameters being monitored goes out of bounds. These implementations can result in risk mitigation and more informed decision making at banks for scenarios involving trade finance.

#6 Wallet of Things

As an extension of automated payment through things, when more devices become digital and “smart”, it will be possible to have wallets associated with each device. For instance, an autonomous car could potentially pay for parking, gas, rental or even maintenance service using its embedded wallet. Each and every home appliance or consumer equipment could eventually host an embedded, pre-funded wallet that is capable of managing its running expenses on its own.

From an owner’s perspective, a digital identity based “wallet of things” might provide an integrated view of costs and expenses associated with owned or leased devices.

#7 Contextualized PFM

Early incarnations of PFM focused on little more than expenditure categorization and generic insights for users – such as benchmarking finance management with “People like Me”. The future generation of PFM tools can offer more contextualized alerts and advice by accessing IoT data from the customer’s owned or leased devices. For instance, alerts on parking fees or air conditioner electricity consumption could be contextualized based on real-time data. These alerts could be based on the owner’s estimated personal budget for electricity consumption or parking fees. This paradigm will enable usage of devices and services to be capped to a pre-defined amount and has the potential to facilitate better management of service consumption and operating expenses.

#8 Frictionless Customer Onboarding and KYC

Banks crave holistic insights into customers’ financial behavior. Having this information during customer onboarding can help them profile the customer correctly and cross-sell relevant products.

However, information available at the bank’s disposal at this stage is scarce and does not provide a comprehensive view of the customer’s financial behavior. In a world where all of the customer’s devices are linked together with the customer’s digital identity, having access to the customer’s unique digital footprint might help uncover usage patterns of different devices and provide insights into financial behavior as well. People already use their Facebook / Gmail id to login to different Internet sites; this might be extended in the future to have a blockchain-based unique digital signature which is used for most transactions. This universal blockchain-based digital identity may also help with KYC processes in the future. Knowing about the financial inclinations of the customer through the digital signature, banks can offer relevant products at the time of onboarding – for e.g. offer a co-branded credit card designed with rewards from a particular petrol station that the customer frequents.

#9 Tailor-Made Auto Insurance

Insurance Companies are already offering devices that plug into the on-board diagnostic port of cars and send driving behavior data back to them. Based on driver habits, the owner is eligible for discounts. However, innovative products, such as those from Tesla Motors, promise to take digitization to a whole new level in the automotive industry. Tesla Cars even have a Linux-based OS that automatically upgrades features “over the air”. This digitization will throw up newer metrics that can be used to provide tailor-made insurance to customers based on driving habits, engine health and general wear and tear of the vehicle. Additionally, by overlaying GPS data on the actual speed of the vehicle in speed sensitive zones (such as schools or residential areas), insurance companies can gain critical insights into the likelihood of accidents and price insurance premiums appropriately.

#10 Real-time Life Insurance

Companies across sectors are looking at connected programmable products and services that can generate customer-specific data, which can eventually be aggregated to build our digital twins.

While conventional thinking might lead us to believe this is intrusive, business models have begun to emerge that embed incentives for customers to share data willingly. E.g. Fitbit is offering integration with Wellcoin to enable users to purchase rewards based on sleeping habits, exercise routines, beverage preferences etc., with the Wellcoin virtual currency. All this may mean that while today it is almost impossible to issue life insurance automatically, IoT may empower users to do just that. By combining health metrics from wearables with medical history and a biometric digital identity stored on blockchain, people will be able to request, and get life insurance instantly anywhere, anytime. Time required for underwriting could also be drastically cut from months to near real-time.

#11 IoT enabled Smart Payment Contracts

Smart contracts are computer programs that facilitate, verify, or enforce the negotiation or performance of a contract. IoT, together with smart contracts and digital identity, can make payments partially or fully self-executing and self-enforcing. For instance, pay after a trial of 7 days for home appliances, or control access to a house based on timely payment of rent. This model of IoT-assisted smart contracts holds huge potential in terms of process automation and also mitigation of operational risks. More importantly, this can plausibly create new product options which offer better customer experience.

#12 P2P Finance on Tangible Assets

Peer-to-peer models have proved to be a disruptive trend for banks in areas such as lending. A futuristic application of IoT might extend the P2P model to several new areas and impact traditional financial services products such as leasing.

In the future, it might be possible to lease assets to individuals or businesses through 100 percent online services that directly match lessor with lessee.

Leveraging digital identity, the leasing process can be completed in real-time as the ownership of the asset can be switched from lessor to lessee in a second after payment is confirmed. This has the potential to unleash a completely new business model, whereby any financial dealings based on digital objects can be carried out peer-to-peer, disrupting banks in areas such as leasing and mortgage.

IoT has the potential to reimagine banking as we know it completely. And it is more important than ever for banks to look at providing services and products on the channels that their customers prefer. In 2017 and beyond we will see progressive banks take it a step further and provide “banking on things” – which can be anything from a smart car, to smart walls.

Would you like to discuss your bank’s strategy for IoT with the experts at Finacle?

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