Muthoot Finance Q1 net rises to 30 per cent

With big data software companies and cloud providers using up a large amount of data, there has been a substantial increase in the practical application of AI. Artificial intelligence is already being applied in many fields to perform specific medical diagnoses, remote sensing, electronic trading, and robot control.

Financial institutions have long used an artificial neural network to detect system changes and abnormal claims while alerting and flagging them for humans to investigate. Many banks are using artificial intelligence systems to maintain book-keeping, organize operations, manage properties, and invest in the stock.

Artificial intelligence, defined as a theory and development of computer systems to perform tasks normally associated with humans, such as decision-making, visual perception, and speech recognition, has been in existence for a long time. With advancements in computational hardware, big data, and machine learning, artificial intelligence is becoming more powerful and useful every day.

Recent advances in artificial intelligence have ushered in a new era in finance. Big data and machine learning have yielded breakthroughs that resulted in improved customer experience and productivity within a short period of time.

Software plays a huge role in this breakthrough, and there remain a lot of challenges to solve. There is a need for software to be designed and optimized to fully take advantage of the underlying hardware features to improve performance. There is also a need for libraries, frameworks, and other tools to be streamlined to accelerate the development process. Some of these problems have been solved because of the advance in GPU.

Here are a few areas in finance that artificial intelligence is already having an impact:

• Financial service providers and banks deploy AI to help predict and plan how customers manage their money, thus making AI an integral part of business development strategy.

• The capability of smart machines to turn data into customer insights and improve services is transforming the digital experience. By utilizing complex algorithms and machine learning, AI can process thousands of structured and unstructured data points. Because finance professionals heavily depend on data, this capability can significantly impact how they do their jobs.

• Auditors feel freeing of responsibilities due to automation potential provided by artificial intelligence. They are using AI to automate time-consuming and manual activities, giving them time to focus on the more important job. AI can help auditors review contracts and document faster by employing machine learning technology to find key phrases from documents that take a lot of time to decipher or interpret. Currently, AI can process language in a document and produce relevant results; this has played a crucial role in improving productivity.

Muthoot Finance

• Data-driven management decision at low cost is ushering in a new style of management. In the future, managers will be able to question machines instead of a human experts. Machines will analyze data and make a recommendation that team leaders will base their decision upon.

• Embedded application rises in end-user devices and financial institutions per Muthoot servers can analyze a large volume of data, providing customized forecasts and financial advice. Applications like this can also help to track progress, develop financial plans and strategies.

The common loan ticket length reduced marginally for the zone underneath evaluation to Rs 37,196 from Rs 37,417. Gold jewelry pledged stood at 152 tonnes on the give-up of the quarter. Several loan bills recorded a boom of nine% to seventy-five lakh all through the Q1 of FY 18 compared with the corresponding zone of the preceding economy.

The board of Muthoot Finance has decided to acquire the ultimate 11.73% conserving with other shareholders in Muthoot Homefin (India) at an aggregate price of Rs 38.72 crore. With this acquisition, MHIL becomes an entirely owned subsidiary.

With big data software companies and cloud providers using up a large amount of data, there has been a substantial increase in the practical application of AI. Artificial intelligence is already being applied in many fields to perform specific medical diagnoses, remote sensing, electronic trading, and robot control.

Financial institutions have long used an artificial neural network to detect system changes and abnormal claims while alerting and flagging them for humans to investigate. Many banks are using artificial intelligence systems to maintain book-keeping, organize operations, manage properties, and invest in the stock.

Artificial intelligence, defined as a theory and development of computer systems to perform tasks normally associated with humans, such as decision-making, visual perception, and speech recognition, has been in existence for a long time. With advancements in computational hardware, big data, and machine learning, artificial intelligence is becoming more powerful and useful every day.

Recent advances in artificial intelligence have ushered in a new era in finance. Big data and machine learning have yielded breakthroughs that resulted in improved customer experience and productivity within a short period of time.

Software plays a huge role in this breakthrough, and there remain a lot of challenges to solve. There is a need for software to be designed and optimized to fully take advantage of the underlying hardware features to improve performance. There is also a need for libraries, frameworks, and other tools to be streamlined to accelerate the development process. Some of these problems have been solved because of the advance in GPU.

Here are a few areas in finance that artificial intelligence is already having an impact:

• Financial service providers and banks deploy AI to help predict and plan how customers manage their money, thus making AI an integral part of business development strategy.

• The capability of smart machines to turn data into customer insights and improve services is transforming the digital experience. By utilizing complex algorithms and machine learning, AI can process thousands of structured and unstructured data points. Because finance professionals heavily depend on data, this capability can significantly impact how they do their jobs.

• Auditors feel freeing of responsibilities due to automation potential provided by artificial intelligence. They are using AI to automate time-consuming and manual activities, giving them time to focus on the more important job. AI can help auditors review contracts and document faster by employing machine learning technology to find key phrases from documents that take a lot of time to decipher or interpret. Currently, AI can process language in a document and produce relevant results; this has played a crucial role in improving productivity.

• Data-driven management decision at low cost is ushering in a new style of management. In the future, managers will be able to question machines instead of human experts. Machines will analyze data and make a recommendation that team leaders will base their decision upon.

• Embedded applications in end-user devices and financial institution servers can analyze a large volume of data, providing customized forecasts and financial advice. Applications like this can also help to track progress, develop financial plans and strategies.