Introduce new technology into the workplace if you want to keep your organization efficient and capable of adapting to the constantly changing business environment. By providing a more complex solution than a simple yes/no response to a question, artificial intelligence (AI) can aid specific processes within your financial services organization, such as RFP processing, trip planning, and fraud detection, by providing a more complex solution than a simple yes/no response to a question. Given that computers are capable of processing vast amounts of data much more quickly than human beings, the application of AI can increase productivity significantly.
Mirat.ai is now an artificial intelligence-driven cloud software capable of providing all the packaged tools under one license, offering centralized self-service capabilities with No/minimum staff and remote monitoring capabilities that presently no other competitor is able to serve. The USP of MIRAT.ai is “Automation” of IT infrastructure management that is highly aligned with ITIL and current trends.
Why are AI and machine learning important?
Company owners have discovered that artificial intelligence is a highly effective resource that helps them increase the efficiency of their work and the quality of their work.
The term “artificial intelligence” refers to any software designed to function like the human brain. Machine learning is a type of artificial intelligence that describes a program that changes itself based on the information fed into it to train it and the feedback received from the humans who built it and those who use the program. Extensive research is required to make important investment decisions, and powerful analytical tools are common when making these types of decisions.
The use of service automation software in conjunction with machine learning capabilities can assist in expediting the research process while also providing reliable investment recommendations. When this ability is applied in the workplace, it has the potential to significantly reduce operating expenses while allowing people to devote their time and energy to making the best possible, informed recommendations to their clients.
Furthermore, take into consideration the learning curve associated with artificial intelligence. An average human can only retain about 10% of the information they read.
On the other hand, a machine can retain everything and store it in memory for future reference, allowing it to cross-check information, identify patterns in information, and select important data from any point in time within seconds of reading it. The ability of a machine to analyze large amounts of data while also researching at a faster rate is what allows it to have so many practical applications in the financial services industry.
In the field of finance, look for time-consuming and repetitive processes that require a high level of concentration and analysis to identify tasks well suited to the capabilities of artificial intelligence and machine learning.
APPLICATIONS IN THE REAL WORLD
Determining the value of investment opportunities
The task of evaluating opportunities is one of those that take up a significant portion of a manager’s time each day. While sorting through massive amounts of data and comparing hundreds of data sources with one another is a challenging task for humans, the application of artificial intelligence in this area can complete the task in a fraction of the time while maintaining higher accuracy and neutrality. The implications of this are that artificial intelligence may be able to deliver the best possible results and even project the success rate and potential opportunity for each of the options under consideration. By utilizing artificial intelligence in this manner, financial services firms can devote more of their time to opportunities with a high likelihood of success and less time to sifting through data that will most likely not be looked at again.
Processing of RFQ
Opportunities are presented to financial services firms in Requests for Proposals (RFPs) (RFP). The fact that artificial intelligence can work with both unstructured and structured data sets means that the simple act of scanning your RFP will enable a machine to read it and learn everything it needs to know to provide you with the answer you seek. As a result, the time-consuming data submission procedure is no longer required. Furthermore, ITSM automation would inform you of the opportunity associated with a particular RFP. In essence, as more RFPs are processed, the data lake grows, and your machine becomes smarter and smarter due to the increased use of the machine. The machine can also make recommendations for changes to proposals based on past performance and human input, which will aid your organization in achieving greater long-term success in the future.
TRAVEL OUTLINE FORMULA
The logistics of trip planning for managers and salespeople are a complete nightmare. When going on sales trips, people are frequently constrained by time constraints and must choose which few people they will meet from among the many options presented to them. Rather than selecting those who would be the most enjoyable or easiest to meet with, people naturally tend to select those who will provide the most opportunities for an organization. As long as humans are involved in the decision-making process, this bias is difficult to overcome. Incorporating artificial intelligence into this decision-making process eliminates bias and allows for considering and comparing all relevant factors before a decision is made.
Ultimately, the decision must be made by the individual who will be traveling and attending the meetings; however, by allowing AI software to make trip-planning suggestions, managers and salespeople can devote more time to preparing quality presentations for the people with whom they will be meeting, increasing the likelihood that a favorable outcome will be achieved for the company.
DETECTION OF FRAUD
Fraud detection is one important infrastructure operation that has benefited from machine learning techniques. Machines are incomparably more efficient than humans at performing the same task on the same computer. They can track and compare numerous data points while instantly comparing the data to previously recorded transactions on the account. By detecting and reporting unusual activity on an account, this aids in investor servicing and ultimately helps to improve customer satisfaction. An example of this would be artificial intelligence identifying in real-time a transaction of $10 million on a bank account that typically only withdraws less than $100,000 per month.
Risk management is the management of risks
Because of its adaptability, artificial intelligence can also open up new possibilities for risk management. Organizations will benefit from the ability to quickly and effectively analyze nontraditional data sources such as images, product reviews, website activity, geolocation data, satellite imagery, and social media posts, which will allow them to supervise risk management and trading activities more easily. This will also allow them to make connections between data points more quickly and effectively and map out relevant trends.
The application of artificial intelligence and machine learning technology in the financial services industry will enable firms to provide clients with faster and more accurate services. By automating time-consuming tasks and allowing software programs to make well-informed, data-based recommendations, your organization can improve efficiency, productivity, and employee satisfaction. The processes listed above are by no means the only ones in which artificial intelligence can be applied. AI is only limited by our willingness to put it into action and develop it to meet our specific requirements.
Visit https://www.mirat.ai/trial.html to access your free 14 trials and evaluate how MIRAT can be useful for your ITSM needs such as the following:
• Security, Auditing and compliance: Access Validation, Vulnerability management, Baselines & Hardening (IDOM Potency), Access Request Management, Asset Mapping, Access request.
• 360 Monitoring: Operating System, Hardware, Hypervisor, Network, Storage, Application, Database Log Management.
• Event Management: Event Management and Correlation, Maintenance mode, Auto ticketing.
• Automation: Automation as a Service (AAAS), Triage Live Poll, Self-Healing, Orchestration, Workload Automation.
• Insights: Operating System Insight, Application Insight, Database Insight, Performance Capacity & Analysis.
• ITSM Suite: Incident Management, Change & Release Management, Work Request Management, Asset Management.
Our pricing plans are very cost-effective (starts at $4 per month) and affordable for startups, SMEs, MSMEs, along with enterprise-level plans for larger firms with more extensive requirements.
Visit www.mirat.ai or mail to [email protected] for more information!
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