How Machine Learning Solutions are transforming the World of Financial Services?

Posted by Parija Rangnekar On Filed under Machine learning app development No Comments
How Machine Learning Solutions are transforming the World of Financial Services?
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The Fintech sector has progressed beyond imagination. Just a few years ago, it took several weeks to get loans approved, but today, everything is processed online and it takes barely a day. Likewise, financial frauds used to occur very often and the financial safety of the user was a big concern worldwide. However in recent times, such fraudulent transactions have reduced considerably, though, online transactions have increased immensely.
How did this happen? What changed?
The mobile revolution and the emergence of trending technologies like machine learning and artificial intelligence have brought a paradigm shift in the fintech industry. Machine learning technology has undoubtedly transformed financial services in a big way.
The algorithm used by Machine Learning solutions is used to identify correlations and work patterns within the large amount of data used in sequences, operations, and events. Hence it is used successfully in process automation, customer support optimization, financial monitoring, portfolio management, algorithmic trading, etc., and much more!
So, in this blog, we will outline how machine learning services has impacted the fintech sector! Rather, we will have a glimpse at the machine learning applications in this sector. Let’s commence.

Significant Role of Machine Learning Solutions in the Fintech Sector!

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Risk Management
In the Fintech industry, risk management refers to the process of identifying, analyzing, and migrating or accepting uncertainties i.e. potential risks while making any investment. It also includes taking precautionary steps to reduce such financial risk. Machine learning solutions along with AI and deep learning can help in making informed decisions about financial reports or loan applications. The predictive analysis used in Machine learning can predict potential risks from this unstructured data, and curb financial fraud to some extent.
Detecting and Preventing Banking Frauds
Today, banks and other financial organizations are paying heavily to prevent fraudulent practices. A plethora of large financial institutes are still using outdated security measures and have no systems to deal with new kinds of threats. However, machine learning algorithms are proving beneficial in this scenario. These can be used to find patterns involved in thefts and identify the hack-prone areas or loopholes in the banking systems. Besides, machine learning models are used in image processing, data mining, language processing, etc. Machine learning provides a predictive model depending on historical data for making vital business decisions using result-oriented predictions.
Complying with Ever-changing Rules and Regulations
Adherence to regulatory compliance like HIPAA is vital for financial firms and they spend billions to comply with them. Yet, new rules keep popping up, and following all these rules every time becomes almost impossible, despite spending a lot of time, money, and effort. But, AI and ML platforms can help automate this process as they can read through the pile of regulatory documents and guidelines. They can track and monitor any regulatory updates faster while minimizing risks related to non-compliance.
Robo-Advisors
Robo-advisors are digital advisors or platforms that provide algorithm-driven, automated financial planning services with very little or no human intervention. The Robo-advisor collects data like age, financial status, current income, future goals, etc. from clients and uses this data to provide vital advice to them about the kind of investment they need to do based on their future goals. These Robo-advisors do a predictive analysis based on current market trends and the clients’ goals and find the best-suited investment plan for them. Likewise, they offer easy account setup, account services, robust goal planning, portfolio management, comprehensive education, attentive customer service, and security features, etc. Some experts also predict that these digital advisors could completely wipe out the human advisors in near future and save huge costs for Fintech app development services.
Chat-bots
Chatbots are being used by several financial institutes and they work as full-scale robotic assistants. These chatbots respond immediately to the customers, hence the customers feel satisfied. Most of the time, the customers are not even aware whether they are interacting with a non-human assistant.
Sentiment Analysis
Sentiment analysis is yet another application of machine learning in financial services; also called news analysis. Machine learning applications are majorly dependent on data. But these applications cannot depend just on the data from stock and trade prices. So in recent times, these are evolving to gather additional data from social media trends, news trends, etc. to do sentiment analysis. The algorithms can do predictive analysis using the available data, also taking into consideration the thoughts and opinions of the users, etc.
Safety and Security of User Data
Needless to say, users’ data is the biggest concern for every financial firm. If this sensitive data leaks or gets hacked by any chance, it can not only lead to financial losses but also result in defamation in the market.
Traditionally, the users are being provided with a username and password for secure access. In case of account recovery or lost password, mobile number validation is required or some security questions are asked. But in the future, with the use of machine learning and artificial intelligence, anomaly detection apps can be developed that make use of biometric data like voice recognition, facial recognition, or retina scan. Several machine learning development companies are shifting their focus towards this area. Such measures will surely improve the data security of the users to a much better level.
Influencing Stock Markets
Stock markets are impacting the Fintech sector too. Every day, huge trading operations are being carried out and they gather tons of historical data. Machine learning algorithms take advantage of this data and identify patterns of stock market dynamics to make predictions. The traders make use of such vital data and accordingly decide the strategies. Based on these patterns, they can make trading forecasts and get benefitted in the stock market world.

Final Words:

Machine learning development services have influenced the world of financial services in myriad ways. It is playing a significant role in improving several processes like loan approval, risk management, portfolio management, financial analysis, etc. It prevents fraudulent practices and helps in stock forecasts too. Besides these benefits, machine learning developers and experts all over the world are experimenting to invent several other applications that can empower the fintech industry to serve their customers better, outsmart the competition, enhance productivity, and save costs effectively.
So this read ends here! I hope it was insightful.
Have you leveraged Machine learning services in your business endeavours? We would like to hear about your experiences.
In case of any technical assistance concerning the development of machine learning solutions reach out to Biz4Solutions, a highly experienced outsourcing software company in India. We are a leading Machine learning Company in India and USA and excel in delivering high-end services to the global clientele.

Why Should Companies Adapt to AI?

Posted by Parija Rangnekar On Filed under Artificial Intelligence, Machine learning app development No Comments
Why Should Companies Adapt to AI?
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AI, big data, and machine learning technologies are increasingly ingrained in our daily lives. It is no longer the future but rather a present reality. AI allows you to make decisions much quicker and more precisely than before. While it is still a novel idea, it already has many businesses uses.
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It is altering the way things are done and making people more productive. In fact, 86% of CEOs say that AI is a mainstay in their workplaces as of 2021. It’s becoming vital in unforeseen ways, from forecasting customer behavior to decreasing data entry.
Even if individuals have mixed opinions about AI, it is hard to deny that it provides us with enormous prospects. It is particularly true from a financial perspective since commercial enterprises and government agencies are interested in this field.
Before considering why companies should adapt to AI, let’s look at what artificial intelligence is.

What Is Artificial Intelligence?

Artificial intelligence (AI) is the foundation for simulating human thinking functions by developing and deploying algorithms in a dynamic computing environment. Computers are pretty good at evaluating these algorithms and coming up with the best decision. Artificial intelligence (AI) and machine learning (ML) are the core future of commercial decision-making.
Machine learning algorithms are used to build and deploy AI. ML refers to the tools and techniques used to create a model to identify patterns. Machine learning model operations are required in businesses where multiple models are deployed.
Developing, analyzing, changing, and implementing predictive models are part of machine learning model operations. It keeps track of inspections, pauses, routines, statistics, and versioning to ensure repeat testing. It makes the machine learning lifecycle so much simpler.
All modeling operations attempt to make ML models as efficient and productive as possible. It’s worth noting that we’re dealing with two different aspects of machine learning model maintenance. AI is used in various domains, enabling our lives to be more accessible than ever before. Artificial intelligence can aid any company in the following ways:
  • Process management optimization
  • Using market research to get insights
  • Including models in the manufacturing process
  • Involvement of stakeholders in the findings

Benefits AI Can Provide to Companies

  • Improves Customer Service
    •
    Chat will have surpassed all other customer support platforms by the next few years. By automating client contacts, AI-driven chatbots enable businesses to deliver 24/7 customer assistance. AI advancements have enabled bots to pick up on conversational nuances and precisely imitate human language.
    AI-enabled chatbots can bridge customer service voids for small organizations that don’t have the funds or human resources to hire a customer care staff.
    AI can also help in customized alerts to specific users. Personalization allows it to be tailored to particular users, assuring that they obtain the most suitable response at the right time.
    Machine learning techniques are now being used in SEO services too. It is used to analyze the purpose behind query phrase picks and the content of queries.
    Artificial intelligence in Customer Service
  • Save Time and Resources
    •
    Companies can benefit from AI’s increased efficiency and production because manual processes take time and cost. Automation has substantially impacted all corporate sectors by reducing repetitive and tedious processes and conserving time and resources. Processes include:
    • Operate robotic lines in manufacturing
    • Monitor warehouse balances
    • Process payments
    • Respond to customer queries
    AI can complete jobs at a rate and level that no person can achieve. When humans are not obliged to execute repetitive and tedious jobs, they may focus on higher-value activities that machines and computers can do.
    Once the initial startup expenses are covered, automating activities results in fewer labor hours, less paperwork, and improved customer satisfaction. As a result, you’ll be able to increase your profitability and reallocate cash to produce more revenue.
  • Helps in HR Processes
    •
    The selection process is another place where artificial intelligence may enhance productivity. AI can accelerate the applicant assessment process by automating filtering calls and examining applicant submissions. AI also aids in the elimination of human bias in pre-employment checks, which is a positive thing for employee engagement.
    Human resources frequently manage interior employee assets. According to the Harvard Business Review, internal services for addressing problems in IT and personnel regulations can be made easier with artificial intelligence.
    One of the causes is that artificial intelligence may be used to drive natural language search for discovering answers to specific questions. AI improves each time, allowing it to respond to requests more rapidly and correctly.
  • Improves Cybersecurity
    •
    Artificial intelligence is an attempt to mimic human understanding. In the sphere of cybersecurity, it has immense promise. AI platforms can be trained to provide threat warnings, discover potential malware, and protect critical data for companies.
    It can be used to detect cyber dangers and potentially dangerous behaviors. Conventional software solutions cannot keep up with a large amount of new malware released each week. Therefore, this is an area where artificial intelligence can help.
    Systems are trained to identify malware and execute predictive modeling using sophisticated algorithms. It can provide information on new anomalies, cyberattacks, and countermeasures. After all, hackers are subject to the same trends as the general public, so what’s trendy with them shifts regularly.
    Artificial intelligence in Cybersecurity
  • Easy Insights
    •
    A startling amount of companies have yet to tap into their data riches. Companies usually have all the information about the consumers but don’t know what to do with it or draw essential insights.
    AI helps firms make intelligent, strategic business decisions by combining large volumes of complex data, analyzing it, recognizing patterns, and uncovering insight.
    For example, AI is being used in the financial services industry to organize, categorize, and pattern massive volumes of economic data. Its goal is to deliver more personalized and customized advice to clients. In a few minutes, AI can process vast amounts of data.

Final Thoughts

You may have observed that all of the highlighted advantages are rather broad. Different companies in various industries may use AI to achieve multiple goals in practice. AI may increase efficiency, reliability, and customer support and assist a firm in developing by spotting patterns and maximizing sales prospects.
Another benefit of artificial intelligence in the company is marketing personalization. Algorithms can spot interconnections and repeating patterns in the behavior of prospective and actual users. Based on this information, making particular offers for certain persons makes it feasible.
The list could continue indefinitely. However, the real benefits of AI are not contained in what most people believe in. So, it’s crucial to figure out how it might benefit your company specifically.
Would like to build an impeccable AI/ML solution for your business? Well then, the Machine learning Services offered by Biz4Solutions are worth a try! Our team of tech nerds has the proficiency, experience, and expertise required to tailor highly functional AI/ML apps/solutions for clients from diverse industry verticals.