As more banks and financial institutions (FIs) show indefatigable appetite for solutions ranging from fraud and risk management to regulatory compliance, the FinTech segment is set for rapid growth in India. In the past year, the banking industry in India began embracing new technologies such as artificial intelligence (AI), machine learning (ML) and blockchain to leverage existing data, expand products and services, and revolutionise the customer experience. In fact, banks are collaborating with FinTechs to experiment with a variety of use-cases, from implementing bot-enabled conversational banking services to using recommendation engines for targeted marketing of financial products.

Even as the FinTech sector slowed down globally, the scene in India presented a different picture with the country emerging as one of the most promising regions for FinTech investment. In 2016, India’s FinTech segment witnessed a strong growth; a boost provided by the demonetisation of high value currency notes. On one hand, the country has the largest unbanked or underbanked population waiting to be covered, while on the other, there are regions—such as Kerala and Gujarat—with a strong technology and infrastructure ecosystem. This provided the FinTech firms the necessary room to implement new technologies and scale operations.

Exciting days ahead for AI and ML

The two terms—artificial Intelligence (AI) and machine learning (ML)—are often used interchangeably; a fact that irritates most technocrats. AI refers to smart algorithms that vary the output based on a wide range of input variables. On the other hand, ML refers to one particular application of AI that ‘learns’ from large amounts of data and makes the required inferences useful to the user.

Banks and FIs are using AI and ML applications in data analytics and customer service for the following reasons: personalising and improving customer experiences, generating better insights, and automating back-end workflows. According to a PwC study, over 36% of large financial institutions in India have already invested in these technologies, and almost 70% reported that they are planning to do so soon.

Systems using AI or ML can undertake the execution of numerous applications such as voice and image recognition, logistics, search and matching, and personalisation. As the financial sector quickly recognises the potential of these two technologies, there is bound to be major progress in the development and adoption of AI in the years to come. Moreover, with Google and Apple incorporating AI and ML features on their mobile platforms, there is a strong indication of high demand for more efficient data analytics. Watch out for this trend in 2018 – the rapid growth of B2C applications in the realm of AI.

Blockchain is here to stay

In the past year, blockchain-based Bitcoin exchanges have been growing in India. The traditional financial services sector is also coming to terms with the fact that the blockchain architecture is ideal for different use-case scenarios. With blockchain-based systems offering vastly improved trust, transparency, and native regulatory advantages, the adoption of blockchain in the Indian banking sector is also finding support from regulators.

As large players in the BFSI sector are inclined towards innovative blockchain implementations, the technology shows promise of rapid adoption in the coming years. The significant back-office savings and transparency that blockchain provides are very attractive from a regulatory and audit perspective. Within the next year or so, about three main blockchain applications will dominate the Indian market:

Payment / fund transfer infrastructure

Smart contracts

Digital identity

However, as is the case of any new financial technology, a major issue hindering the development of blockchain is the lack of continued support and collaboration between participating parties. Similar to the AI and ML segment, FinTech startups and banks must work together to develop solutions that allow blockchain to get into the mainstream.

HOW SMART TRANSPORTATION INITIATIVES CAN TRANSFORM CITIES?

As more people move into cities, civic authorities are putting in place smart transportation initiatives. These initiatives aim to reduce infrastructure costs, alleviate traffic bottlenecks, optimize routes, and foster road safety. What drives these initiatives is the data from connected vehicles. Information from vehicles helps smart cities to create holistic plans that encompass an entire city’s ecosystem.

The Internet of Things (IoT) is transforming the transportation industry. As the market for IoT is estimated to reach $1.7 trillion in 2020, smart transportation systems are creating opportunities across a wide range of industries and market segments. Opportunities abound in automating roadways, railways, and airways; transforming passenger experiences; and reshaping the way cargo and merchandise are tracked and delivered. Riding the IoT wave is a prime component in smart transportation systems: big data analytics.

Massive volumes of data are generated by smart technologies deployed within connected vehicles. According to a study by Hitachi, a single connected car will produce more than 25 GB of data per hour of use. Putting this data into perspective enables businesses and civic authorities to see patterns they can use to develop a range of innovative services towards building a connected infrastructure.

CONNECTED VEHICLES ARE THE NEW “EYES”

As IoT can create connections between the smart vehicle and the transportation infrastructure, it offers several benefits, including a coordinated system designed to get everyone safely to their destination on time. Sensors installed on the vehicles could send a signal that alerts nearby vehicles about any problem, enabling them to slow down or take an alternate route. In-vehicle sensors and systems create valuable information flows:

Smart Parking

IoT-enabled parking garages can monitor capacity. They can report on the location and number of available parking spaces in a facility to the drivers who enter.

Predictive Maintenance

In-vehicle sensors can analyze engine loads, driver behavior, road condition, etc. This can then compile a vehicle history that can be used to optimize scheduled maintenance.

Optimized Routing

Analysis of traffic conditions, fuel consumption and vehicle idle time between routes can determine the most efficient route for vehicles to follow.

Video Surveillance

By linking dashboard cameras and other video sources with cloud storage, organizations can stream video for immediate review.

Rider Services

Bus and train services can provide real-time route data to customers’ smartphones, showing where the next bus is and when it is due.

HOW CONNECTED INFRASTRUCTURE CAN TRANSFORM URBAN TRAVEL
As smart cities evolve, different systems in the city will be able to communicate with each other. Connected cars help cities to monitor their transport infrastructure. This in turn can enable the development of allied services that are adaptive, and the introduction of predictive tools that allow the best transport service to be offered, based on forecast and real-time environmental, traffic, and other related data. For instance, data from connected sensors can give many insights such as how citizens use transport, what planning is required, and what information can be shared with citizens to enhance their travelling experience. By combining multiple sources of data, such as weather and traffic information, complex analysis of travel patterns can be undertaken.

When vehicles, passengers and infrastructure can communicate with each other, it becomes possible for the city to adapt and integrate different systems, enabling new services to be deployed. Traffic lights can automatically turn green for emergency vehicles, buses can ply routes where more people are waiting, vehicles can pay tolls for distance driven, and pedestrians can have priority over vehicular traffic in some areas.

To make the most of IoT in transport services, the onus is on the civic authorities and service operators. Understanding how best to utilize the data and connectivity options available to them will allow civic authorities to redefine the urban infrastructure landscape to greater effect, and for common good.

 

 

IoT in urban environments brings in a number of benefits. A well-planned IoT implementation helps in managing and optimising traditional public services; increases transparency and promotes better civic response to citizens; stimulates the active participation of citizens in public affairs; and fosters the creation of new services—all of these without drying up the city council’s treasury.

Therefore, local and regional administrations keen on making their city smart keenly follow the developments taking place in the world of IoT. However, any successful implementation requires more than just rolling out a slew of technologies; it involves the public, private and civic bodies to participate in devising a common action plan for their city.

Below is a list of recommendations for implementing, optimising, and evaluating smart city initiatives for all stakeholders:

1.Vision: There term “Smart City” refers to computerisation in the public sphere, i.e IT convergence, digitalisation, connectivity, etc. A smart city is capable of reinventing itself with new standards for the welfare and wellbeing of its population. In IoT parlance, a Smart Cities project refers to the interconnection of key industry and service sectors, such as Smart Governance, Smart Mobility, Smart Utilities, Smart Buildings, and Smart Environment. Therefore, the vision for a Smart City should consider the prevailing social-economic conditions and civic readiness to arrive at the objectives for the Smart City model.

2.Technology Adoption: Creating a scalable, manageable and secured broadband and IoT infrastructure is the foundation for all communications requirements of any smart city. Apart from the above prerequisite, a Smart City project also requires allied technologies as enablers. To better appreciate the level of maturity of enabling technologies and their adoption, it is important to have a synoptic view of all services in terms of technical, infrastructural and administrative constraints.

3. Open Data Policy: Smart cities use public data and information from government and other sources to help solve civic problems and create new business opportunities. Defining the rights and privileges associated with collected data, data governance, and data usage assists in fostering transparency and providing value-added services.

4. Public-Private Initiatives: Categorising the “need to have” and “nice to have” applications (which will be delivered by public-private partnership) sets the parameters for incorporating smart requirements into publicly funded infrastructure programs and in areas such as mobility, healthcare, security, lighting, environment, energy, construction, and communications.

5. Cross-Domain Initiatives: Establishing the framework for a holistic approach across sectors and applications require expertise and standards that span many different sectors—from smart transport to smart buildings. This holistic and layered framework addresses the multiple needs of a smart city, leverages urban data to boost economic competitiveness, and builds effective solutions to many challenges.

6. Stimulate Ecosystems: Cultivating a collaborative culture with private partners plays a key role in developing the smart city eco system. Project developers, utilities companies, service providers, technology vendors, system integrators, and application developers collaborate through initiatives like city labs, developer contests, and application playgrounds to build the smart city. It would be beneficial to create a common network infrastructure and a secure IoT architecture that serves the needs of partners and the city council.

7. Milestones: Defining a framework with quantitative and qualitative indicators is important, and it must be customised for the city’s specific objectives. The evaluation should not only cover technical aspects, but also consider parameters like digital economic growth, sectoral sensitivity, accessibility of open data, digital service adoption, and more.

8. Education: A smart city project should reflect the inclusive, participatory, and social nature of its civic initiatives. Connecting with citizens and keeping them informed about progress through communications and social media is important for the success of any initiative. Through end-user education, field trials, surveys and open house sessions, the administration should reach out to the public.

9. Community Connect: It is important to make innovative companies collaborate with local communities on concepts, end-to-end prototypes, business models, and market trials. Although technologies such as broadband Internet and IoT are important building blocks of the government’s vision, the citizens’ acceptance and engagement will eventually determine success or failure of any smart city initiative.