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4 Ways Machine Learning is Transforming the Finance Sector


The information age isexperiencing a rapid surge in technological advancementsthat have changed most of themanagement scenarios of various enterprises. These advancements have transformed the whole functioning procedures by enhancing workflows and ameliorating task completion skills with automated operations. This has leveraged enterprises with the need of incorporating modern-day technologies like machine learning, artificial intelligence, etc. that assistin overall flourishing of their business.

Machine learning (ML) is a subset of artificial intelligence that is fabricating significant inroads in the finance sector.With efficient infrastructure, appropriate data sets and application of suitable algorithms, machine learning solutions can spring magic by drawing near to accurate insights and predictions. 

Some benefits of machine learning applications in the finance sector include:

1. Credit Scoring and Under-writing

Underwriting is one of the customary tasksundertakenin insurance companies that can be completed by machine learning algorithms expeditiously.As insurance companies procure massive databases, data scientists train models on the basis of customer profiles and data entries that can complete the task of under-writing real-life environments. By evaluating data based on bill payment behaviors, the system can also generate accurate credit scores.  

2. Process Automation

One of the most common applications of machine learning is process automation that replacesmanual work and automates the completion of repetitive tasks, eventually resulting in productivity enhancement. Some automation use cases include:

• Chatbots

• Paperwork automation

• Call center automation 

With the respective utilities, machine learning enablesenterprises to optimize costs, improve overall customer experiences, and scale-up the quality of services.

3. Algorithmic Trading

Algorithmic trading is a way of executing huge orders using automated pre-programmed systems that follow a defined set of algorithms or instructions. The process led by machine learning applications can simultaneously analyze multiple data’s from varied sources which help the companies to take better trading decisions. During the process, a mathematical model scans the news and trade results in real-time to detect factors that fluctuate stock prices.   

4. Security 

Increasing number of monetary transactions and third-party integrations have made the finance sectorvulnerable to security threats. According to reports, the Indian banking sector experienced a loss of almost Rs.87,357crores in the fiscal year 2017-18. However, incorporation of machine learning services offered by the leading machine learning service providers can help insurance companies in the detection of frauds. They provide financial institutions with the ability to monitor transactional parameters for all accounts in real-time. This can determine actions of cardholders and restrict fraudulent behaviors with great precision.  

Depending on the need and business requirements, financial institutions can select various pathways for adopting machine learning solutions. They can also empower themselves with big data solutions which emerges as a holy-grail of technological revolution.

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