Here is an article by one of our Top 5 Budding Data Scientists, Praveen Parthasarthy. Read about the rise of High-Tech companies in the coming decade.

Fin-Tech, Mar-Tech and Auto-Tech are the Buzz Words and are there to rule us in this decade

{2020-2030} for sure. It is about to enter the other spaces as well like Retail, Healthcare, and others sectors sooner than later.

Fin-Tech

The financial services and insurance industry follows technological advancement with each passing day. Big banks such as JP Morgan have been early adopters of disruptive technologies like Machine Learning, Artificial Intelligence.

Artificial Intelligence (AI) is a paradigm-shifting technology that is seamlessly changing the way we live, move and interacts with each other, shop and trade. Financial Services and insurance is no exception, and the industry has just started to peak and the tip of the iceberg is sure to be seen in this decade.

Fin-tech is the name given to proven use-cases of cutting-edge technology and impactful business models to the end user in the financial sector.

Various real-time use cases are seen across the industry

Client Risk Profile – More Credible and Reliable Scores for decision making

Underwriting and Risk Assessment – Loans will be disbursed basis complete data analysis and no iota of doubt across departments.

Churn Prediction – We can accurately predict the customers who will pay to our services.

Algorithmic Trading and Money Management – Latest Generative Adversarial Networks (GAN) as future of Trading. Having use cases in asset and derivative pricing and risk factor modeling.

Valuation Models – Model can quickly calculate the valuation of an Asset using data points around the asset.

Verdict:

The good thing is that the industry veterans have also understood that only with strong data-backed decisions we will be able to survive in this ever-changing landscape. This will be possible only through use of data and various models to test the past scenarios and do try out different combinations to come out successful and cost-saving and benefitting in more than one way to the Business.

Mar-Tech

All companies are competing to gain and retain their market share.

In recent years influential companies like Microsoft, Oracle and Apple have dedicated almost 20 percent of their revenues to marketing, and a few are inching towards 50 percent just for marketing expenses to deploy DIY techniques rather than use the normal sales channels.

Digital marketing now dominates over traditional marketing channels, mainly because they allow businesses to interact with their customers in real-time and in an engaging manner.

Businesses have realized that digital marketing has a better and broader reach and is also highly cost-efficient.

Key pointers:

Mobile ad spending at a global level has crossed USD 7 billion in 2020. Close to 96 per cent of smartphone search traffic is routed by Google.

About 85 per cent of consumers want the brands to create content for their products. The same percentage of people will not buy the product if they believe the website to be fake or unsafe.

Various use cases are seen in this space

Improvising Search Experience – Customers will be able to get crystal clear search results basis all past data

Product Recommendations – Collaborative filtering used by Amazon, Netflix and spotify have benefitted by Data pairing systems

Consumer Segmenting – AI helps in personalizing offerings to the Target audience

Social Media Data – Most obvious form of Martech and AI automation marketers can point to. Hoot suite and Sprout social are leading the pack in this using data from multiple sources.

Content Management – Strongest marketing strategy – Tools to manage content creation and dissemination are more sophisticated.

Verdict:

The industry is rapidly moving to AI and automation and is at present being used by the market leaders. Slowly the ones who follow the leaders will also need to take action and get into using their data effectively to get much more revenue and to ensure they stay afloat in this business.

Auto-Tech

In the automotive industry, machine learning (ML) is most often associated with product innovations, such as self-driving cars, parking and lane-change assists, and smart energy systems. ML is poised to become as much an organizing principle as an analytic ingredient for sophisticated marketing campaigns across automotive industries. This is especially true in the automotive industry, a capital-intensive, high-tech sector driven by disruption.

From parts suppliers to vehicle manufacturers, service providers to rental car companies, the automotive and related mobility industries stand to gain significantly from implementing machine learning at scale. We see the big automakers investing in proof-of-concept projects at various stages, while disruptors in the field of autonomous driving are trying to build entirely new businesses on a foundation of artificial intelligence and machine learning.

Most manufacturing operations in automotive industries are still largely dependent on experience-based human decisions. The emergence of Big Data, in conjunction with machine learning in automotive companies, has paved a way that is helping bring operational and business transformations, thereby leading to an increased level of accuracy in decision-making and improved performance.

Various use cases are seen in this space

Quality Control – Image Recognition and Anomaly Detection

Enhancing Overall in-vehicle User Experience – Facilitates Personalization and smart assistance

Predictive Maintenance – More precise and evolving maintenance recommendations

Supply Chain Optimization – Identify demand levels for different strategies – Sales, price and location

Verdict:

The automotive sector is the most competitive sector at the present moment.ML and AI are the new frontiers enabling businesses to discover hidden value propositions. Open-source community is the engine of innovation which is why most executives embrace a platform that leverages innovation to stay ahead of the competition.

Digital media platforms are disrupting traditional dealer relationships, making the process of buying and selling cars more data-driven, while new entrants like Tesla and ridesharing services like Uber and Zipcar are altering customer expectations around automotive value. Bringing Machine Learning and Artificial Incentives in line with investments will help companies remain competitive amid all these momentous changes.

From IT to HT

High-Techs are here to stay!

The high-tech industry which is a combo of all technological advancements in the above  sectors has been a leading adopter of artificial intelligence (AI), so much so that it influences  the digital transformation trends in most other related and partnering sectors.  Technology giants are not just building AI solutions; they are acquiring smaller AI companies to build more capabilities and finding new use cases outside the IT department, in addition to our offices and homes. Yet, as per leading research reports these firms are still lagging in the overall AI adoption when compared with other digitization efforts.

This is the future and will be the needle mover to ensure each player stays in the space and improves on it to become either the Innovator, early adopter or early majority, late majority or a laggard who gets rapid death at the end of the day.