How machine learning is changing the financial industry

machine learning

A lot of talks, innovation, news and information about Machine learning has been prevalent in the mainstream media for quite a long time. We see new machine learning algorithms being devised for tackling new sets of problems from time to time.

Machine learning is slowly but surely becoming employed in each and every field of life. And there is a good reason behind it – these advanced learning algorithms, learning methods, and computational ways make many problems a lot easier to solve. Many mind intensive and energy consuming tasks are being replaced by simple learning algorithms of Machine learning; thus making them more accurate, faster and efficient.

The field of Finance is not void from its presence either. Instead, it would be fair to say that machine learning is becoming an integral part of the mega financial industry. It is slowly revolutionizing the finance that was once known to the world. Here are some of the ways how machine learning is having a significant impact on finance:


Whenever a customer wants to get a loan or a specific type of insurance from a bank, there is usually a specific set of procedures followed to determine the risk involved and the amount of loan and interest rate at which it can be given. This risk assessment is done by a financial agent who compares the demographics of the customer with the preset standard for loans. It is an inefficient method as it not only involves humans input, human error but also ignores the bigger picture i.e. trends of the area and other factors affecting the person.

Instead, machine learning algorithms are designed to allow computers to have access to the multitude of data points related to: macro and micro-economic trends, housing market, interest rates, trends in the geographical area where the loan is originating and the demographics of the customer. These algorithms can infer a much better and detailed picture of the underlying risk than any manual method could. They allow computers to analyze that data further on to make much better decisions for increased output.


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Security and Fraud:

Software is eating the world, and the Internet is the driving force behind it. We all are connected to wireless networks which expose us to many security threats. Similar is the case in financial organizations. There are constants cases of hacked credits cards, fraudulent transactions and compromised accounts. In the past, these problems were tackled by security teams which overviewed the processes which were marked by the system as abnormal. But that process was very slow, lack-luster and full of false-positives. Therefore, it is necessary that use of machine learning is employed to improve the security and to combat fraud.

Machine learning algorithms implemented in these financial institutions benefit from huge databases and form patterns of the processes. With the help of these patterns, any anomaly or abnormality is easily identified in almost real time, the root cause is surfaced for the experts to make sound decisions and the issues are dealt with very very quickly. It also makes sure that amount of false-positives stays low as it uses learning instead of a set standard, therefore, the customers are allowed to do their work in peace without undue stress.

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Risk assessment:

2008 financial crisis was a major mishap in the world of finance and economy. Faulty risk assessment techniques actually caused it.

The 2008 economic crisis stemmed from the crisis in the mortgage market of US. It started out with many banks giving mortgage loans to subprime clients in hopes of making money off it as the housing sector was on the boom. The problem was with the risk assessment methods which didn’t consider the risk of giving loans to subprime clients. The people in charge of assessing these risks were blinded by human errors like greed, fear, and uncertainty. As a result, when prices of house sector started going downhill due to unpopularity, many financial organizations started to collapse. Many banks went bankrupt. The economy of US and worldwide suffered a significant decline. It was because the risks involved weren’t evaluated on the major scale.

To prevent any such crises for happening again, companies are opting for machine learning techniques. The advanced learning algorithms associated with it are free from human error. These ever powerful machine learning algorithms gather the data about the matter at hand, and assess risks and dangers associated with the transaction and only then take action. This obviously decreases the probability of any mishap.

Machine learning also allows easy compliance for regulatory reasons. Different types of data of multiple sources are collected regarding an issue or a client and are then analyzed to give a bigger picture of the entire relationship with a particular entity or client. It allows us to quickly and easily understand the situation at hand and decide the required action necessary for it.


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Investing and trading:

Trade and investing is often affected by human emotions. Lack of emotional intelligence is a major cause of financial losses when it comes to investing and trading. Machine learning algorithms suited for trade can be used to remove this barrier. These algorithms can use various techniques to not only optimize the trading activity in one’s account – but can also affect the psychology of other market participants. For instance, a particular algorithm can be used to divide a large trade into smaller trades so as to cause minimal fluctuation in the prices – which are primarily controlled by supply and demand. Another application of machine learning algorithms is quick arbitrage opportunities; where machines can look for prices of one product which vary from one geographical area to another and benefit from this price difference. Moreover, we can say that machine learning is the most optimal thing for trading and investment activities as very powerful machines can use and benefit from a large number the data elements simultaneously. Comprehending this complexity with such clarify by a normal human mind is next to impossible.

Customer service

Customer service is an important part of any business. But it is also a hard one to get it right. An excellent customer service can elevate an organization or company to a beloved company, but on the flip side – a few unfortunate instances of poor customer service – can hurt a business and its brand.

Recently, the widely reported incidents by certain airlines and their behavior with the customers and passengers has caused the airline industry to step back and re-evaluate their business practices.
But getting the customer service is not an easy task. First and foremost you need a really knowledgeable and dedicated team – who not only possess the technical know-how about your product or service; but must also possess soft skills like empathy and ability to listen.

Therefore, usually most of the companies only reserve customer services for the people who have invested large sums of money or are using most of the financial services of an organization. This, however, repels the newer customers as their questions and complains are left unanswered.

Machine learning offers algorithms for dealing with this problem too. There are algorithms which analyze words, compare them with past interactions and respond accordingly. These algorithms are integral part of live chat feature offered by many companies lately.


These were some of the direct aspects of machine learning on finance. We can easily say that machine learning is radically changing the finance industry as we once knew.

The companies and organizations which are employing machine learning in their working and processes, are succeeding while the vice versa are having a hard time in attaining their goals. So it seems quite straightforward that companies should start adopting the advanced techniques of machine learning if they want to remain competitive in the upcoming years.

TOP REASONS TO HIRE A Cloud Computing Consulting Firm

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Top Challenges of Cloud Computing

Cloud computing has been a hot buzz word for last few years. But unlike most buzzwords – cloud computing is actually making a massive impact on how we use computers, applications and several utility websites we have grown so accustomed to.

Years ago, employees would rely on their desktop computers to access applications. In fact, it was common practice to download files from a central office server. This was before cloud computing changed the landscape of access to business information.

Cloud computing provides access to applications and data, 24 hours a day, 7 days a week, through the internet. When you update your Facebook status, you are using cloud computing. If you check the balance in your checking account on your smartphone, you are using cloud computing. The same scenario applies when you
check your email or use mobile apps daily. These are all cloud computing based transactions, fueled by the internet.

Cloud computing as an industry is one of the fastest growing industries of our lifetime, and it is experiencing a growth rate of 50% year over year. And the amazing thing is that this growth is not concentrated in one part of the world – rather companies across the globe are embracing the cloud. The global market for Cloud Computing Services is projected to reach $336 billion by 2020. The primary reasons why so many businesses around the globe have moved to cloud is because it increases efficiency and helps improve cash flow. However, just because cloud computing has added several layers of efficiency to business and the speed of information exchange does not mean that it does not present challenges.

Cloud computing challenges remain constant. But companies are aware of the overall value that cloud computing delivers to business and invest heavily in cloud transition and cloud maintenance strategies. Cloud computing challenges are typically grouped into four categories:

(1) Security and Privacy
(2) Inoperability and Portability
(3) Reliability and Availability
(4) Performance and Bandwith Cost

cloud computing consulting service

Security and Privacy.

The number one challenge associated with cloud computing is security. This is regarded as a huge risk. Any compromise of data can set a company back for millions of dollars. Not only are security breaches well publicized, but they also leave a stigma on a company’s reputation. Customers become fearful of providing information based on what the hear in the news; and the result is that revenue declines.

With cloud computing, valuable enterprise data is housed outside of the corporate firewall. This raises huge concerns. Hacking and attacks on the cloud infrastructure can affect multiple clients simultaneous, even if only a portion of the service infrastructure is attacked. These risks can be mitigated by using taking certain precautions like proper use of security mechanisms like firewalls, permissions or claims based security. To keep the data secure at rest and in flight – it is highly recommended that we use encryption to encrypt sensitive data. Furthermore, we can deploy specialized software and hardware devices which can track unusual behavior across servers.

It is difficult for most businesses to quantify the amount of a loss due to a security or privacy breach tied to cloud access. For this reason, it is imperative to have a strong Cloud Computing Consulting Firm who is competent enough to manage this risk.


Interoperability and Portability.

Your business should have the flexibility to migrate from one cloud provider to another. Beware of lock-in periods or contract specifications that jeopardize the fluidity of your cloud transition. Neither customers nor employees should feel the winds of internal IT change. In fact, transitions should remain seamless. Cloud Computing Consultants can help you resolve any challenges associated with interoperability and portability.

Reliability and Availability.

Even though cloud provides like AWS and Azure are quite robust – they still do experience an occasional outage. A reputable Cloud Computing Consulting Firm will help you monitor service being provided using internal or third-party tools. In fact, your strategic plan should include solutions that supervise usage, performance, robustness, and business dependency of these services.

Performance and Bandwith Cost

The only way to save money on your purchase of hardware, is to spend more money to increase your bandwidth. For a small business, the cost may not be significant. However, for larger enterprises, which are dependent on data-intensive applications, costs can be exorbitant. Based on this factor, many businesses have delayed their transition to cloud to meet their need to reduce the cost profile.
Cloud Computing Consulting Firms help to eliminate the roadblocks in the pursuit of cloud computing. It is rather important to give serious consideration to these issues and the possible ways out before adopting the technology.

Reasons to Hire a Cloud Computing Consulting Firm

Cloud Computing Consulting Firms provide technology services ranging from consulting to development, customization, support, and testing services. Good consultants will follow a consultative-driven approach for providing end-to-end expertise in all cloud solutions. Today, given the opportunity that exists for cloud integration, there are thousands of Cloud Computing Consulting Firms that offer the expertise and services. There are several reasons why you should hire one of these firms. Cloud Computing Consulting Firms help you define your cloud infrastructure and offer technical expertise. They navigate migration to the cloud in a planned approach which is customized to your business. These consulting firms often perform intense cloud platform management; and, they help you reduce costs by constantly evaluating your cost/risk profile as it relates to potential security issues.

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Cloud Infrastructure & Technical Expertise.

Every business needs to build a robust cloud infrastructure. It is counterproductive to slow down operations by implementing audit and controls procedures, before fully migrating to cloud and ensuring the system can sustain you. Consultants will advise you regularly about cloud architecture, engineering, and planning. The expertise in these areas offers businesses a huge advantage – because businesses can get away from incurring massive capital expenditure on hardware and turn their infrastructure costs into operational expenses. Which makes it easier to reach a cash flow positive position sooner rather than later. No wonder most startups these days opt to go with cloud from the get-go.

Cloud Migration.

Cloud migration typically involves combining scalable cloud architectures with classic cloud architectures. It is best to select consultants that have skill sets in both the engineering and legal architectures. Furthermore, a reputable Cloud Computing Consulting Firm offers best practices, guidelines, and insights to help businesses in the migration process from legacy infrastructure and storage resources to the almost infinitely scalable cloud. These professionals know exactly what questions to ask to understand your unique business and apply the correct reference architectures that are suitable for each application requirement.

Cloud Platform Management.

When transitioning to the cloud, there are several factors involved. Monitoring the cloud performance and labor cost may be the significant issues. Apart from performance – it is even more critical to design and architect cloud solutions, so that cloud usage costs do not spiral out of control. Cloud computing generally works on a pay-as-you-go model. The more infrastructure and cloud services you use in your application – the more it will cost to operate it. A professional consulting team will make monitor and optimize your investment effectively.


Cost Reduction

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Perhaps the most valuable advantage of hiring a Cloud Computing Consulting Firm is to help your business reduce costs. The professional cloud consultants are intimately familiar with the complicated processes and the features available on the most popular cloud platforms. Cloud itself is a very new industry and is constantly evolving. The cloud computing consulting firms make it their mission to stay on top of these developments and learn about all the new offerings from the cloud providers. Consultants offer valuable assistance with making a smooth transition and rolling out basic training to streamline operations and ensure cost reductions where applicable.

Teaching computers how to see like humans with Convolution Neural Networks

convolution neural networks

Digital Image Processing:

Google’s vast index had more than a trillion images some years ago. This number can’t possibly go down owing to the ever-increasing use of internet and use of pictures in conveying the message. But that was just the amount of images indexed by Google, there is also a significant portion of images found on the internet that aren’t indexed. Similar is the case with videos, with over 1 billion videos on YouTube alone it is a massive amount of data in the form of videos.

Videos and images are not only found on the internet. There are security cameras capturing videos of their area of effect at all times. Pictures and videos are being shot for personal and business use. They also make up for a hefty amount of data.

This vast amount of data is way beyond the scope of usual human intervention. This information needs to be processed through automation. Automation, machine learning, computer vision are some techniques using which we can actually have a chance to decipher this data and make sense of it. Digital image processing is the solution for this issue. It involves the use of computational methods for differentiating between the images and videos.

Digital image processing makes this data of images and videos much more viable for analysis purposes. A widespread use of image processing is employed by law enforcement agencies. They compare the facial features of the culprit with the databases of their own and the video inputs coming from around the country with the help of image processing. Additionally, the fingerprint software used by the police and other agencies also employ the use of image processing in its working.

Neural Networks:

Computers or machines do not have same concepts about vision and interpreting images and videos like humans and animals do. Our mind features an insight learning which allows us to make sense of the visual sensory input in a much faster and accurate manner than a computer. We can infer whether the given object is a cat, a dog or a chair irrespective of the color and type. The machine takes time to produce this result as it first makes a digital interpretation of the image and compares it with the images and objects placed in its database.

A new advanced field of machine learning has given rise to the technique of neural networks, which is a machine learning method, is used in processing the image. This method lends true learning capabilities to the machine which brings it closer to the working of the human brain. Human brain receives information from sensory organs, analyzes it and generates a response. Similarly, in the neural networks, there is an input node, a hidden node, and an output node. Information is received on the input node, the hidden node analyzes it, adds value to it and sends it to an output node which produces the action suggested.


Convolution Neural Networks:

Convolution neural networks is a modified version of the neural network. The convolution neural network gathers as many inputs as possible which means we should be able to capture most if not all the pixels in an image and process for further analysis. Makes sense, right?

Well not really. Believe it or not even with the large computers and multiple core CPUs and GPUs we have at our disposal these days – this is not practically possible because of constraints of time and processing power.

Convolution neural network decreases the sample size used in the analysis. An image usually contains hundreds of thousands or even millions of pixels. With the current computing capacity we have at our disposal – it is not viable to analyze each and every pixel. It is also a fact that pixels which are close to each other are very similar to each other though vary as the distance increases. So the sample size is decreased by making groups of pixels. One pixel, a representative, is selected from each group and put up with other such pixels. These pixels are then analyzed with ease as they are small in number and can be efficiently computed.




  1. The image is divided into smaller parts in the form of tiles.
  2. These are sent to a neural network which converts them from a network of tiles to arrays.
  3. The arrays represent the area of picture numerically. They are also assigned three axes of color, height, and width of the channel which are the three dimensions. A fourth dimension of time is also assigned if the input is, in fact, a video.
  4. The multidimensional arrays are then exposed to a downsampling function which removes the unnecessary and redundant information from these set of arrays so that only the required amount is analyzed.
  5. This data is then forwarded to the conventional neural network.
  6. The computations are done pretty quickly, and the desired output is generated in the form of labels.

The first three steps are also termed as convolution. And from that name of this neural network comes from. There are many convolution and down sampling layers in a real system. They all are working at the same time to reduce the sample to a manageable size.

Why is it better?

Convolution neural network is better than the conventional image processing method due to variety of reasons. Conventional image processing methods include: Conversion to greyscale of images and then comparing the pixels, comparing the pixels one by one, Scale-Invariant Feature Transform (SIFT), Binary Robust Independent Elementary Features (BRIEF) and Speeded-Up Robust Features (SURF) etc. These processing methods are either totally dying out or are inefficient when compared to convolution neural networks. Convolution neural network is much more efficient as it uses less time and fewer resources. Additionally, SIFT and SURF are somewhat comparable to convolution neural network, but SIFT and SURF offer face problems of inaccuracies. SIFT and SURF use Gaussian differences and differences of scales for detecting the object and often compromise on the data for simplifying the computations which essential for identification of an object. On the other hand, convolution neural networks though employ simplification of the image, but they make sure that no important detail is lost in the process.

Convolution neural systems are now being used around the world. Neural systems are inspired by and are derived from the human brain. When used for image processing, it sorts of gives the computer a human-like vision. It is due to this reason that almost all the face detectors software is using convolution neural networks for accuracy. It also uses so few resources that even your smartphones are using this for face detection.

This technology is relatively new and yet it has endless advantages over the traditional imaging recognition. It is already being used for law enforcement, security, health, and much more. Only time will tell how more can we benefit from it.

Encouraging Women Is My Mission


A well-known technology leader and entrepreneur, Manuj Aggarwal, has made it his mission to empower woman in the technology sector. Through his site he has taught over 40,000 students in only a few years. Due to his experience, Manuj noticed that the gender discrimination wasn’t just media talk, so he decided to do something about it:

“I met my wife through computers and if it weren’t for her, I’d be working in an office for someone else right now. On my page I have dedicated a 15 % discount for pupils of this respected gender. This is the first step of many that my company and I are taking towards a decrease of the gender discrimination situation.”

Mr. Aggarwal sees this as a natural thing to do and does not think about it twice. He came from a small town in India and moved to Canada in his college years. He fell in love with computers and left business school for them. Alongside with the educational website, he is the founder of a consulting firm that goes by the name of He is passionate about sharing his knowledge and contributes with free teaching in third world countries. His opinion of the matter is, that wherever you come from or however you start you can build a life that you enjoy, and he is helping others make exactly that happen.

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Cloud Computing: Businesses are embracing the cloud

Cloud computing

Business Spending on IT Services is on the Rise

More businesses are upgrading technology services. Given the complexities of how business transactions occur today through computer hardware, mobile devices, and cloud-based services, businesses are sourcing firms with heightened IT capabilities. The primary reason why companies increase their IT budgets is simple:  They want to remain competitive with new and existing firms. Hiring small independent contractors is no longer effective. Businesses are calling in the big guys to solve complex IT and technology problems. These firms see the light at the end of the tunnel.  As technology continues to become more innovative, it is more affordable. The forecast below projects spending for IT Services at close to $700 billion for 2017.

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Business owners live in constant fear of IT disruption. It is no secret that fear of IT disruption in technology is a huge factor in spending decisions. A disruptive technology is described as one that displaces an existing technology and creates ground-breaking change in a way that may create a new industry altogether.

Perhaps the best example of disruptive technology would be smartphones. When they arrived, they disrupted a multibillion-dollar cell phone and Personal Digital Assistant (PDA) industry, while introducing new technologies to the mainstream market. With cloud-based solutions in place, disruptive technology will only impact small businesses that are not prepared for change. In fact, without the cloud-based services that newer more popular laptops connect to, they are essentially useless. Disruptive technology does not really affect them because they are connected to the cloud, which is constantly changing. McKinsey Global Institute has listed a dozen disruptive technologies in the chart below. The forecasted global output aligned with these disruptive technologies is approximately $100 trillion when projecting to 2025.


Cloud computing services

Cloud Computing Services are Enhancing Small Businesses


Cloud computing is arguably one of the most innovative technologies of the century. Forward-thinking businesses continue to ride the cloud computing wave as their businesses evolve. Cloud computing provides access to data wherever there is an internet connection. In today’s expanding business environment, it is critical that business owners get their cloud services mix right the first time.

Being armed with the right answers concerning what type of cloud computing the business needs, the appropriate budget for cloud computing services, and the threshold for security risks, are all required for a small business to optimize its strategy in today’s world. Reliability on cloud capabilities whether employees are using their computers, tablets, or mobile phones must be high. In the office, utilization must be just as strong as the field utilization. These metrics are best assigned by a reputable cloud computing consulting firm.

Today cloud computing consulting firms offer expertise on a plethora umbrella of services which include the following: (1) Cloud Storage, (2) Cloud Backup, (3) Software as a Service (SaaS), (4) Cloud Hosting. Cloud Storage stores and backs up files for regular access and for sharing and syncing them across devices. Cloud Backup is similar to cloud storage, but primarily used as a backup source in the event of a crash, cyberattack, or other data loss. Software as a Service (SaaS) – refers to using the web to provide a service, such as Office 365, Google Apps, QuickBooks Online, and Salesforce. Cloud Hosting supports all types of information sharing, such as email services, application hosting, web-based phone systems, and data storage.

For most businesses, the benefits of cloud computing are infinite. Cloud computing saves businesses time and money by optimizing productivity and innovation. Small firms use cloud computing to access information anywhere there is a compatible device. Rather than storing information on a computer or a server in the office, cloud computing stores data on the internet. It works by making information available from a central web-based hub. Cloud computing provides access to anyone who has verified identity. It also syncs data for all devices connected to the cloud, keeping them updated with real-time information.

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Cloud Computing Consultants Can Solve Cloud Challenges

Every business is faced with the decision to upgrade their IT consulting services. Unfortunately, this means firing a small independent contractor and hiring a more robust, competent firm to help solve challenges. Although cloud technology has added a more effective layer to doing business, like any other new technology, it is not void of challenges. Below are several cloud challenges identified by businesses in the last two years.

Cloud computing services

The primary role a Cloud Computing Services Team is managing and maintaining various IT Infrastructure technologies. Premier services packages typically include the following: Computation, Storage, Virtualization, and Backups. All businesses require problem management and resolution of issues in a timely manner. Also, troubleshooting and assessment are vital services required, given the uncertainty that companies face.

Cloud Services give business owners the power to operate using the Internet to make business more efficient. Cloud computing solutions allow employees to share, edit, and publish documents in a unified manner. As a result, employees are able to improve communication and e-mail, share access to calendars, contacts, information, increase marketing abilities, and enhance everyday business processes.

Cloud solutions are refining the business world from top to bottom, bringing big changes to organizations of all sizes. From neighborhood businesses to Fortune 500 corporations, cloud solutions offer a level of accessibility that is unmatched. Approximately 40% of firms in the U.S. have fully adopted cloud computing. By 2020, industry experts predict that over 80 percent will migrate to the cloud computing solutions. The need for businesses to align with reputable cloud computing consulting firms will only increase at this point.

Migrating to the cloud offers several benefits to business owners. Key advantages include lower costs, improved collaboration, increased flexibility/scalability, and greater integration. However, with so many cloud solutions now available for businesses, there may be difficulty in aligning with the right consulting firm to handle challenges.

Cloud integration is a major undertaking for all businesses. Every company needs a team of experts to help launch successful initiatives and ensure success. The right cloud computing consulting partner will accelerate time to market with proven strategies. To partner with the best firm, a business must be able to identify their individual needs while also having insight on the latest cloud technologies available. The decision to employ the right cloud computing partner can make or break a business in today’s economy. However, it is better to be well equipped with a firm that can treat all aspects of a problem than to be underserved with a single contractor who has to outsource to find solutions for cloud computing challenges.