March 2017 -

March 2017 -

The Invincible Machine Learning Technology

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market simplified machine learningHave you ever wondered how Facebook shows us ads that are in line with our recent likes or searches? How does YouTube display ads related to our recent internet searches? In this era, we already know that marketing trends are such that, ads and promotions are customized to the needs and preferences of the end customers. Industries have become highly customer centric and are devising strategies to make their products to be in sync with their customers’ life style and interests.

Machine Learning is the most trending topic after predictive analytics and big data. What is machine learning? ‘Machine learning is a type of AI that provides computers with the ability to learn without being explicitly programmed.’ Actually, ML goes hand in hand with big data analytics. IDC (International Data Corporation) had already estimated that “banks will spend US$17 billion in big data and business analytics solutions in 2016.”

From massive data, ML actually studies and makes patterns that are meaningful. With this, it learns and understands the trends from past data and gives us relevant results. For instance, when we type in a Google search term, we see the prompters and auto fills for the search keywords. How is this even possible? With millions of searches every day, how does Google know what we are looking for with just a few search terms that are typed in? Many times, when we mistype a search term, Google cross references this with similar ‘typos’ in the past and gives us the correct search terms.

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All of these are because of ML and big data analytics. Search engines like Google and other big streaming services like Netflix have their own analytics engines that study millions of users’ behaviour and engagement information to know what items are most viewed or what image is most searched and provides results based on that. Amazon is another example of how it tries to sell products that are based on the customers’ past searches and purchases. Facebook claims that – “it processes 2.5 billion pieces of content and over 500 terabytes of data every day. In addition, it collects an average of 2.7 billion “Likes” and 300 million photos a day. Every hour, Facebook scans more than 200 terabytes of data.” This is just one company we are talking about.

ML is a huge enhancement to big data analytics. ‘Smart machines will become an integral part of business and daily life creating insight from data in ways that, humans on their own could never do’ – Machine Learning: The real business intelligence. ML is starting to simplify user interaction with machines to the extent that there is a virtual person that has the ability to think, solve problems and give apt solutions based on historic data.

Experts of various financial institutions (FI) are developing solutions that have the ability to interact with potential customers and suggest various products and services based on buyer personas (like their income, financial goals, spending patterns and life style). For instance, a wealth management app can have an analytics engine that could track and study the patterns of the past investments of a customer and suggest various portfolio options for the user. This is just the tip of the iceberg.

At Market Simplified, we are already in this journey of designing our solutions with all of these product embellishments. When solutions are designed with such enhancements, customers would surely be delighted. Millennial customers want minimal physical interaction with their FIs. They needn’t go to the FI in person or painstakingly call a customer service help line number only to hear an automated message and wait till the ‘end of time’ before an actual executive tends to them. ML would enable FIs to run the entire financial operations with least human intervention. It is just a matter of time!

References: Tim Cole’s – Big Data is Dead: Long Live Predictive Analysis; Kai Goerlich – Machine Learning: The Real Business Intelligence; Fintech Innovation – Banks lead big data analytics spend through 2020; Market Simplified – How important is it to know your customers.
 
About Market Simplified: Market Simplified is a thought leader in revolutionizing and digitizing products for financial institutions by continuously innovating and simplifying finance. We empower our customers with cutting edge digital experience that is highly personalized and enhanced for the end users with our ‘Experience Engineering’ platform driven by Analytics, AI, Machine Learning and Blockchain technologies. Our clientele includes industry leaders like OptionsXpress (Charles Schwab), Currenex (State Street), MB Trading, Maybank Kim Eng, Kotak Mahindra Bank, National Stock Exchange of India and many others across the globe.
 
About the author: Venkat Rangan is the Founder and CEO of Market Simplified Inc. He is a technology enthusiast. Venkat also has great interest in aviation and loves to read and learn about airplanes. Whenever he gets time, he likes to fly the Cessna Sky Hawk 172. His dream is to fly the Gulf Stream G650. Sometimes it makes us wonder – why he isn’t a pilot or running an airline business…
Gulf stream G650

Gulf stream G650

 

 

Types of Analytics Explained

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Analytics

‘Analytics is the way of extracting and communicating meaningful patterns in the data.’  In simple words, it’s converting raw data into actionable information. Along with Big Data, Analytics is now powering businesses across all verticals by improving operation efficiency, thus increasing the profit. As experts say, not all analytics are the same. To efficiently deploy analytics into the business, one must be aware of the types of Analytics and which one to use based on the requirements.

Analytics can be broadly classified into the following 3 types.

Descriptive Analytics

This type of analytics describes the data, in other words, it analyses and summarizes the complex raw data into a form that is understandable by humans. Though it is the most basic type of analytics, it is inevitable and around 90% of the organizations which use analytics rely on this technique. It is critical for the organizations to learn from their past performances and descriptive analytics comes in handy for the same.

Use case: The spendings from various accounts of a customer over a period of time are analyzed to provide a spending pattern. This tells the customer exactly where he is spending most of his income, which will be helpful in future financial planning.

Predictive Analytics

It’s a step further to the traditional descriptive analytics. Here, the data is not only summarized but the analyzed patterns are used to predict the future course of the data. The outcome of the predictive modeling cannot be definite as they are probabilistic. In simple words, it provides only the probability of the occurrence of an event based on the provided historical data.

Use case: After spend pattern analysis is obtained from historic data the predictive analytics can be used to predict the future spend of the user. Say, the user has continuously gone on vacation for 3 consecutive years; predictive analytics algorithm will highlight the high probability of the user taking the vacation in the current year also.

Prescriptive Analytics

It’s the most advance form of analytics. It uses emerging technologies such as AI and Machine Learning along with Predictive Analytics. Unlike predictive analytics, it not only provides the future course of the data but also the optimized path to achieve the best outcomes. This helps to identify uncertainties and helps to make better business decisions.

Use case: Prescriptive analytics can help in suggesting investment opportunities that are apt for the user based on their income, spend pattern and risk profile. It can also proactively help in financial planning and strategic decision making for the business.

Analytics has helped organizations in swift decision making, reducing cost and increasing profitability for different industries. It helps in mining useful information from tons of unutilized data. This would be an indispensable tool for all industries and will help them provide their customers with personalized products and services that are in sync with their needs and goals. A true revolution, yet to attain its peak!

About Market Simplified: Market Simplified is a thought leader in revolutionizing and digitizing products for financial institutions by continuously innovating and simplifying finance. We empower our customers with cutting edge digital experience that is highly personalized and enhanced for the end users with our ‘Experience Engineering’ platform driven by Analytics, AI, Machine Learning and Blockchain technologies. Our clientele includes industry leaders like OptionsXpress (Charles Schwab), Currenex (State Street), MB Trading, Maybank Kim Eng, Kotak Mahindra Bank, National Stock Exchange of India and many others across the globe.

About The Author: Gokoulane Ravi is a foodie, technology enthusiast, and a developer turned marketer with more than 5 years of experience in the space of mobility. When he is not working, he likes to read, write, run and cycle.

How important is it to know your customers?

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big data analyticsIt is so easy for customers to reject marketing contents that are uninteresting or irrelevant to them – Just a click and mailers are added to spam! How many of us have actually seen the ‘promotion’ tab in our own Gmail? If you have seen this tab, you will find hundreds of marketing emails which are sent on a regular basis. The minute we find that someone is trying to sell something; we rush to click the delete button. Don’t we always skip the ad in a YouTube video, when we have the choice to do so? Aren’t ads between interesting movies or TV shows, annoying? These days, customers DO NOT want to see contents that are forced on them.

What are the 2 approaches in marketing?

  • PUSH STRATEGY: This strategy involves taking the product to the customer via multiple means ensuring that the customer is aware of the brand at the point of purchase. Fliers, notices, cold calls and YouTube ads are all part of push strategy. Remember the annoying ads between our favourite TV shows?
  • PULL STRATEGY: A pull strategy involves motivating customers to seek out your brand in an active process. This can be achieved by creating rich content in social media, website and blogs where there is wide reach and prospective customers will get in touch with the company if they think that you have a solution that can solve their problems.

Push strategy in marketing is over! Marketers need to understand that trends have changed. Marketing is no longer about the company, products or its solutions. It is predominantly customer centric. Marketers need to identify the following – Who are our customers? What challenges do they face? How best will we be able to make a difference to them?

These days, customers are on the lookout for highly personalized and customized services that are designed to tackle their challenges. This is all the more important in banking and financial services. Financial institutions primarily deal with a wide array of products and services catering to different kinds of customers. It is very crucial to market products and services that are relevant to their customers and not just anything they have to offer.

Let us look at an example.

  • Scenario 1 – Richard, who has 5 Billion dollars in his bank account, gets a call from his bank asking if he would like to apply for a vehicular loan with low interest rates. This is absurd, right? Why will Richard want to apply for a vehicular loan considering his sound financial status? This is an example that shows how ignorant the bank is with regard to its customers.
  • Scenario 2 – Richard gets a call from his bank asking him if he would like a dedicated relationship manager to assist him in managing his finances and to give him a variety of investment options as he comes under the HNI category. This would be a better marketing call that is in line with Richard’s interest, isn’t it?

This is just one of the many instances where financial institutions can actually strike a chord with their customers by providing them with rich content through different media, including calls. It is evident from the 2nd scenario that the bank has done its homework before reaching out to Richard with its offering.

Before drafting a marketing content, it is essential to study the customer profiles and get all relevant information so that the solution can be tailored to their interests and priorities. This aspect is called the ‘Buyer Persona’- ‘A buyer persona tells us what prospective customers are thinking and doing as they weigh their options that address the problem.’  This helps influencing the customers’ decisions based on specific attitudes, concerns and criteria that drive the customers to choose a bank or any financial institution’s solution that best fits their goal.

How do we organize, study and take meaningful interpretations from this data? Big data and Analytics are quickly gaining importance. So, what is Big data? Big data is a massive storehouse of information. Analytics will help study historic data and past trends with which experts will be able to predict future trends of the market and industry by giving valuable insights. Combination of these 2 will yield great results for financial institutions. Predictive analytics and big data basically involve studies on customer behaviour, spending patterns, expense management, life style and other variables.

Knowing customer details – their interests, spending patterns, financial goals and personal details will enable financial institutions to devise products and services that will not just solve their problems but will also resonate with them and enable a long term relationship with their financial institutions. This is what will create true value for the customer as well as the financial institution. The process is very simple and will definitely change the way customers react to marketing content that is personal and valuable. This is what every customer wants and needs. It is high time that financial institutions resort to this technique and understand the importance of adding value to its customers.

About Market Simplified: Market Simplified is a thought leader in revolutionizing and digitizing products for financial institutions by continuously innovating and simplifying finance. We empower our customers with cutting edge digital experience that is highly personalized and enhanced for the end users with our ‘Experience Engineering’ platform driven by Analytics, AI, Machine Learning and Blockchain technologies. Our clientele includes industry leaders like OptionsXpress (Charles Schwab), Currenex (State Street), MB Trading, Maybank Kim Eng, Kotak Mahindra Bank, National Stock Exchange of India and many others across the globe.

About the Author: Girijashankar is a Classical Carnatic Vocalist and teacher who loves to perform. He is also a voracious reader and enjoys writing. He is currently working as a Business Development Executive in Market Simplified.

 

Analytics Will Be The Way To The Future

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analytics‘Analytics is the discovery, interpretation and communication of meaningful patterns in data.’

In today’s world, data is wealth. Most firms store massive amounts of data so that it can be put to good use in future. The future has finally arrived! Many banks and Financial Institutions (FIs) are trying to engage their customers better so that it can lead to a more personalized approach and enable customer retention. So far, these institutions have been using push strategy in marketing where materials are pushed to customers on a very generic basis without any study in relevance. This strategy is more or less like taking a chance. Some customers will find it relevant and some might not. Ultimately, the ones finding it not to be of their interest will unsubscribe to the mails or might permanently add the mailers to spam. To avoid this, FIs have started using data analytics to analyse and derive meaningful inferences and then devise marketing strategies to personalize the experiences for their customers.

This is where Analytics comes into play. Companies are forced to anticipate customer needs in order to provide them with better services that are in sync with their financial goals. Is it possible to determine the patterns on a wide customer base? According to studies, most financial organizations have massive store houses of data, but a very small portion knows what data is important, or how to leverage this data for increased revenues and lower costs. FIs should necessarily figure out unique strategies to engage customers in interactions based on their needs, life stages, aspirations and account spending. Analytics provides the golden opportunity to look into the future. Here is how the process works!

To do an analysis, FIs and banks first need to ask the following questions.

  • What type of data is needed?
  • Based on the collected data, what type of analytics should be used?
  • What type of marketing model is best suited to determine a product or service for a customer?

Once these questions are answered, the company will be able to determine a more personalized approach designed exclusively for different sets of customers.

According to Aite Groups, these are some of the most important areas in which analytics can make a difference to customer acquisition and retention.

  1. Channel preferences: By identifying the banking channels used by the customers, FIs can connect with them through these channels based on the majority.
  2. Social Media: Studies also show that two thirds of customers use social media. This can be a great insight to study customer behaviour and life events.
  3. Mobile data: Understanding how often an app is used or the amount of time spent on an app will give insights to add/remove features based on user analytics.
  4. Customer ratings and reviews: This is the best way to know and understand what apps and services a customer likes or dislikes.
  5. Bill payments: Understanding regular or periodic payments of a customer can be a valuable insight for the FIs in order to devise ways to engage them through push notifications and reminders.
  6. Personalized Financial management: This is the most important part of predictive analytics. FIs should know the financial goals of its customers. This will help them hand-hold their customers to reach these goals by recommending products and services that are in line with these goals.
  7. Geo Location: Location based services have gained much importance after the disruption of digital banking and the advent of smart phones. This could be a great value addition since information on nearest ATMs, customer care centres and other services will come in handy when customers are in unfamiliar locations.
  8. Weather and other services: If majority of customers choose digital channels for their banking, weather forecasting does very little. However, it is still a value addition.

Here are a few testimonies from top banks in the US.

Bill Hoffman, Chief Analytics Officer, US Bank, Minneapolis – “I had a front row seat to both the amazing power of good decisions and the destructive power of bad ones. I developed a visceral dislike for bad decisions, which has powered my professional passion: to enable good decision-making. At the end of the day that’s really the fundamental mission for anyone in a data analytics role. Keep the customer at the centre in whatever you do. Focus on creating value at the intersections. Quite often an organization’s data analytics “power plants” are up, but the lines are down. The biggest sources of value from data analytics will come from the power lines that connect a holistic understanding of – and insights on – your customers’ relationships with you across business lines, across products and services and across all channels.

Rajendra Patil, Head of Data Strategy & Decision Science, Bank of New York Melon, NY – “You can’t improve anything unless you are able to measure it and analyse it. Culture change is about improvement. You have to start with user needs and wants and make sure that the things we work on and the questions we ask are relevant to addressing them, directly or indirectly.”

Customers are always on the lookout for personalized services that are relevant to them. Data Analytics will be a sure enhancement to help industries get a demographic concentration of the total population based on their interest, life style and financial goals so that their products and services can be specific to their needs and preferences. The next big thing is data analytics which is yet to be tapped to its fullest potential. In the years to come, we will be able to see the intrusion of predictive tools, big data and analytics apart from AI and Machine Learning.

About Market Simplified: Market Simplified is a thought leader in revolutionizing and digitizing products for financial institutions by continuously innovating and simplifying finance. We take pride in giving the best User Experience with highly personalized and enhanced transaction experience for end customers with our ‘Experience Engineering’ platform that is driven by Analytics, AI and Machine Learning technologies. Additionally, the solutions are also powered using Blockchain technology. Our clientele includes industry leaders like OptionsXpress (Charles Schwab), Currenex (State Street), MB Trading, Maybank Kim Eng, Kotak Mahindra Bank, National Stock Exchange of India and many others across the globe.

About the author: Venkat Rangan is the Founder and CEO of Market Simplified Inc. He is a technology enthusiast. Venkat also has great interest in aviation and loves to read and learn about airplanes. Whenever he gets time, he likes to fly the Cessna Sky Hawk 172. His dream is to fly the Gulf Stream G650. Sometimes it makes us wonder – why he isn’t a pilot or running an airline business…

Gulf stream G650

Gulf Stream G650

 

ShipIt – 24 Hours to turn Innovative Ideas into Real Solutions!

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At Market Simplified, ShipIt has been a customary event for the last 4 years where the employees form groups to come up with innovative business ideas and turn them into business solutions in just a day. About 15 teams participate in this ‘24 hour hackathon’ every year by presenting their solutions in front of a jury. The teams are ranked based on ship-ability, usefulness, solution’s ability to generate revenue, innovativeness and presentation skills. The event took place in February this year.

IMG_20170209_105033367-min

‘Artificial Intelligence (AI), Machine Learning and Chatbots’ are the most trending topics of discussion in the BFSI segment since the beginning of 2017. Keeping this in mind, most teams conceptualized their ideas based on AI and Chatbots. After the daylong event, the jury chose 4 winners.

Here are the most innovative and interesting ideas of this year’s ShipIt.

  • Friday (name inspired from Iron Man) is an all-powerful engine based on machine learning algorithms which when configured into any user’s mobile has the power to read, analyse, suggest and transform the banking app much more than anybody could ever think of. The key feature is that it has a behaviour tracker which suggests products to its customers based on the transactions made and type of products owned by the customer. This engine even works with low internet connectivity.
  • ‘Smart Wallet’ is a wallet that is based on credit mechanism. We have come across various digital wallets where we load money and use it for convenience in spending. Customers can use Smart Wallet just like credit cards. They can choose to pay back on a monthly basis and need not worry about loading money into their digital wallets.
  • Autobots is an AI-powered-suggestive-banking application and an automated support desk for customers and institutions. The chat application has the ability to login, show account overview, list term deposits available, show account balances, create fixed deposits and handle multiple accounts.
  • Knack is a Virtual-Assistant (VA) enabled solution that is aimed at providing hands-free banking experience to its customers. The VA is called Avatar that has the capability of responding to questions instantly (Not just banking related!). The solution is configured to work on multiple form factors.

ShipIt has and will continue to be a wonderful arena to explore and work on ideas based on technology innovations and turn them into real solutions. This is something we always look forward to!

About Market Simplified: Market Simplified is a thought leader in handcrafting custom solutions by continuously innovating and simplifying finance. We have maximized the revenues of industry leaders like OptionsXpress (Charles Schwab), Currenex (State Street), MB Trading, Maybank Kim Eng, Kotak Mahindra Bank and National Stock Exchange of India by providing enhanced and sustained user engagement through Experience Engineering.

About the author: Girijashankar is a Classical Carnatic Vocalist and teacher who loves to perform. He is also a voracious reader and prefers to read books on crime and mystery. He is currently working as a Business Development Executive in Market Simplified.

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