June 8, 2021 – Finance, Tech & Analytics Career Resources

Last Updated on 2 years ago by Imarticus Learning

Introduction

Fintech companies are witnessing major growth nowadays because they are disrupting traditional banking services. People can now get banking services just from their smartphones and there is no need to visit a physical bank. The recent coronavirus outbreak has also forced people to adopt the digital method for payment/transactions.

People can now shop, book rides, and do many things with the help of fintech services. They also have access to their financial records more than ever due to fintech companies. The risk of hacking & fraud is also associated with fintech services and fintech players have to ensure that they secure their user’s transactions.

Let us how fintech ensures the security of transactions.

How does Fintech Work?

Fintech services can be availed via smartphone. One can download the mobile application through which fintech services are provided. Each fintech user has a unique ID and bar code. By using the two-factor authentication system, one can make payments to others. Some fintech applications also use Bluetooth for connectivity.

In the case of online bank transfers, the transferred money is encoded in multiple layers before it goes on the internet, and when it is received by the recipient’s bank, the information is decoded and is deposited in the receiver’s bank as currency. Fintech also provides online insurance and loan facilities.

Technologies like artificial intelligence, machine learning have helped in collecting the financial data of any user and analyzing it. Once you apply for a loan online, your credit history & credit score will be checked via smart back-end algorithms and if you are eligible, your loan request will be passed.

The online transfers also provide confirmation mails & calls on the successful transfer of money to notify both the parties i.e. the receiver & the sender. Many independent agencies like Automated Clearing House (ACH) also help in securing financial data transmission via online medium.

Security Measures in Fintech Services

The security measures adopted by fintech companies to secure the transactions are as follows:

Data encryption is a key feature in fintech services. They encrypt data using symmetric or asymmetric means of encryption and it is decoded at the receiver’s end. If somehow some hacker/fraud tries to access the data in between transactions, the hard encryption makes it impossible to access sensitive information like account number, banking password, etc. The most used encryption techniques by fintech firms are the Advanced Encryption Standard (AES), Rivest-Shamir-Adleman (RSA), Triple Data Encryption Standard (TripleDES), Twofish, etc.
Management of third-party services is very necessary to enhance the security of transactions. For example, one can book a cab using some fintech application and the payment will be automatically deducted from your e-wallet on the completion of your ride. The firm needs to have a strong interface so that third-party services are secure. The interface and architecture must be very secure.
Fintech firms use pair programming to ensure quality coded mobile applications. A messy and buggy code is very easy to hack.
Secure identity verification & authentication is ensured by fintech firms. They use various approaches like Role-based Access Control (RBAC), Password Expiration, Session Timeout system, etc.
Meaningful data is turned into random strings via tokenization which helps in increasing the security of data. It is an important process used by fintech firms to secure their users’ data.

Conclusion

If you are thinking to start a Fintech career, you must be aware of the security processes because security is the main aspect of fintech services. The sensitive information of clients should be preserved in all circumstances. This was all about the security measures in fintech services.

Last Updated on 5 years ago by Imarticus Learning

With the advent of technology, human has started to function by largely depending on machines and technology. To make things far easier, automated technology has been introduced in various aspects of life. Reinforcement learning is also a segment of machine learning that is based on the premise of automation.

What is Reinforcement Learning with MATLAB

Reinforcement learning is a kind of machine learning which enables a computer to function on its own by interacting with the dynamic environment repeatedly. The main aim of this approach is to reduce human intervention in machine learning and automation as much as possible so that a state of one hundred percent automatic technology can be attained.

Under reinforcement learning, the computer is not properly coded or programmed to perform the tasks but is made to act accordingly with the trial-and-error method. The environment or the outside conditions are made dynamic for the computer to explore as much as possible.

Applications like MATLAB enable this kind of function to run smoothly by providing schematic and organized results and outcomes. MATLAB is a professional tool that is fully documented and properly tested for carrying out functions like these.

With the help of MATLAB, reinforcement learning is done to get the best outcome suitable for a particular outside condition. All these functions are undertaken by a piece of software called the agent. The agent interacts with the outside conditions to produce various outcomes.

Understanding the Reinforcement Learning Workflow

To train the agent or a computer, the following steps are deployed:

Creating the environment

The first step is to provide a suitable environment for the agent. The environment can be either a real-life condition or a simulation model. For technical and machine-based reinforcement learning, having a simulation model is preferred for smooth and safe functioning.

Setting up a reward

A specific reward in the form of a numeric number has to be set up so that the agent can function accordingly. A reward is sometimes achieved by the agent after constant trials. Once the reward has been met, the optimal way to achieve the reward can also be found.

Creating the agent

The agent for reinforcement learning can be created either by defining the policy representation or through the configuration of the learning algorithm of the agent.

Training and validating the agent

For this, all the training options for the agent are set and training is started for the agent to tune the policy. In case an ideal validation of the agent has to be done, simulation turns out to be the option.

Deployment of the policy

In the end, the policy representation is deployed using coding languages like MATLAB, etc.

A real-life example of reinforcement learning with MATLAB

Automated driving is the best example of machine learning, outcomes of which can be the result of reinforcement learning. The agent in the car uses various sensors to drive the car automatically without any human intervention. These sensors and video cameras give commands to the steering, gears, clutch, and brakes to take suitable action.

After a rigorous session of trial-and-error of various outcomes, the best way to automatically drive a car can be known. Reinforcement learning uses almost the same sort of applications while parking or reversing the car.

A shortcoming of reinforcement learning

Apart from its various benefits, reinforcement learning takes a lot of time and tries to achieve the optimal outcome.

For making stable analytics and artificial intelligence career, you may refer to the professional learning by Imarticus. Various subjects under the analytics and artificial intelligence course are offered by Imarticus Learning.

Day: June 8, 2021

How Fintech Ensures about Your Security of Transactions In The Digital Era?

Things To Know About the Reinforcement Learning with MATLAB!

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