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The financial services industry has to deal with large amounts of data and is heavily regulated. Also, the industry is under constant pressure to adapt to new technologies and customer demands. At such a dire situation; one of the most promising technologies that can help in overcoming such challenges is – Intelligent Automation (IA) in Financial Services Industry. 

Yes, you heard it right! It will allow financial firms to operate more smoothly than ever. Ensuring that all activities are documented and auditable, helping firms to avoid costly penalties. Basically, IA combines Artificial Intelligence (AI) and Robotic Process Automation (RPA) to automate repetitive and rule-based tasks. Intriguing, right? Then allow me to tell you more about how Intelligent Automation (IA) is beneficial for Financial Services Industry. 

But, Before I proceed further! I wanted to tell you that I have discussed Intelligent Automation: How should Business get started?  – in one of TheCodeWork’s previous blogs. In case you haven’t read it, please have a look to understand this blog better!

So, Let’s see what else Intelligent Automation has to offer to financial firms. 

The State of the Financial Services Industry

The financial industry represents a segment of the worldwide economy. It encompasses a wide range of institutions. Here’s a quick stat – In 2020, the global fintech market size was valued at $111.24 billion! And it is expected to grow 23.8% from 2021 to 2028. 

(Source: Grand View Research)

It included banks, credit unions, insurance companies, and other financial hubs. Since, Fintech firms facilitate the flow of funds between individuals and businesses – enabling them to borrow, lend, invest, and protect their assets – the industry faces challenges, including regulatory pressures, cybersecurity threats, and changing customer expectations. 

State of the Financial Services industry in India – A Close View By Experts in the Field

As Per Manjunath Samaga, an influential thought leader in Global Banking and International Trade,

India is the fifth largest in the global scale and one of the fastest growing economies in the world. Aiming to become $5Tn economy and 3rd biggest economy in the world soon, India has become a land of opportunities predominantly in the IT, manufacturing and IT enabled services.

Today’s financial system in India is completely different vis-a-vis a decade ago. Digitized banking and financial services are the buzz and sin-qua-non. Even the smallest cooperative bank or Micro Finance companies have adopted digitization/computerization for most of its operations and processes.

According to me, sectors like Fintech, poised for a larger growth as a support mechanism, in fact, offering a major co-operative for the financial services. A few bullet points would show the direction:

• Volume of Digital Payment transactions in Apr-2023 : 8.8 bn; projected to be 1 bn per day by 2025 and digital payments increased by 76%. Huge market growth for UPI subscribers.
• High scope for Jan-Dhan, Aadhar and Mobile banking linked business.
• Boost in the domestic consumption and strategic growth in Exports
• There is no dearth of funding for Startups with a high potentials to become Unicorns.
• Banking and Insurance sector is expected to get re-shaped – while the core focus continues to be in conservative lending.
• The impact of global slowdown might not affect much on India and perhaps Indo-Pacific region.

Potential growth trajectory for:

• Fintech, Digitization and Process Improvements
• India to upscale its regulatory framework and governance on par with international centers (in fact, already the system is quite robust)
• A new thought of bringing in “Indian Standards” in terms of financial regulatory governance.
• Make GIFT city to become on par with international financial centers
• Scope for massive process and product streamlining, reporting mechanism to attain transparency and accountability.

Solution…

To overcome these challenges, fintech firms need to adopt innovative solutions such as IA. Fintech Firms that adapt to emerging technologies and evolving customer needs are likely to thrive in the future. Talking of which, we are a group of tech enthusiasts at TheCodeWork. We thrive to implement technology with existing businesses for better better productivity and success. 

Reach out for a free consultation call, may be?

Okay so back to a very insightful case study here –

Let me tell you, how JP Morgan Chase, one of the largest banks in the world! Implemented IA to automate its back-office operations and what were the results: 

• Saved 360,000 hours of manual work each year.
• 70% error reduction in claims.
• Rapidization of loan processing. 

Stunning! Isn’t it?

 So, what are you waiting for? Contact TheCodeWork Teach Team today! A one-stop solution for all your automation needs. 

Fun Fact:

PwC found that 75% of fintech firms believe that IA will significantly impact their business by 2025.  It is highly beneficial for fintech firms! How, you ask? 

Well, for starters, it improves – 

• Operational efficiency, 
• Reduces costs,
• Increases accuracy, and 
• Enhances customer experience. 

By automating routine tasks, your employees can focus on more value-added tasks that requires human intervention. So, it leads to increased productivity, faster turnaround times, and improved customer satisfaction. 

Now who wouldn’t want that?

Role of Intelligent Automation (IA) in Financial Services Industry

The financial industry is experiencing significant change and growth with the integration of IA. As businesses seek to streamline their operations, the future of the financial industry is looking brighter than ever before.

IA has the potential to transform the fintech industry in many spectacular ways. As it encompasses a range of technologies, including Robotic Process Automation (RPA), Artificial Intelligence (AI), and Machine Learning (ML). Here’s a brief overview of each:

• Robotic Process Automation (RPA): Automates repetitive and rule-based tasks, such as data entry, customer onboarding, and claims processing. It will help firms reduce operational costs, increase efficiency, and improve accuracy. 

• Artificial Intelligence (AI): It allows machines to perform tasks such as natural language processing, image recognition, and decision-making. In fintech firms, AI can be used to improve fraud detection, risk management, and customer service.

• Machine Learning (ML): A subset of AI that involves training algorithms to learn from data and make predictions or decisions based on that learning. ML can analyze large volumes of data to identify patterns, make predictions, and automate decision-making processes.

So, if you’re looking for a reliable and experienced tech team, look no further than TheCodeWork! Contact us today to discuss your tech needs and learn how we can help you achieve your goals.

These IA tools are transforming the financial services industry! Enabling firms to automate routine tasks, streamline operations, and deliver better customer experiences. Now, let’s proceed further with the significant features of IA for your financial requirement. 

Benefits of Intelligent Automation (IA) in Financial Services Industry

So, are you ready to see how IA will revolutionize the Financial Services Industry? Am sure, You are! 

 Let’s explore the many benefits of Intelligent Automation in financial services industry:

Increased Efficiency and Productivity

Within the fintech industry, optimal efficiency and productivity play a pivotal role in achieving success. Enterprises must process substantial volumes of data and transactions expeditiously and precisely, while ensuring unparalleled customer service standards. IA represents a way to achieve these objectives, by automating tasks and allowing more emphasis on high-value activities.

Here’s How:

• RPA can automate tasks such as opening new accounts and freeing up employees for other tasks. 
• Increased efficiency will lead to reduced staff procurement costs. 
• It can provide 24/7 customer support through chatbots and virtual assistants.

According to a survey by Deloitte, fintech firms that implemented IA reported a 12% increase in productivity. Along with a 10% reduction in costs, and an 8% increase in revenue.

So, Why not join forces with TheCodeWork to create a future full of infinite possibilities with IA?

Also, let me put in a fun fact: Companies saw employees actively taking up more tasks! Ever since IA reduced the burden of repetitive and mundane tasks.

Reduced Errors and Increased Accuracy

Accuracy and precision are of utmost importance! Even a small error in a transaction or an investment decision can have significant consequences. This is where IA will play a crucial role in reducing errors and increasing accuracy. 

According to Deloitte, 53% of financial firms reported improved accuracy and reduced errors after implementing IA. For Real? Yes! Allow me to tell you how:

• Machine learning (ML) analyzed vast amounts of data and identified promising patterns, improving decision-making. 
• RPA automated data entry tasks that are prone to errors, ensuring accuracy and consistency.

• It allowed firms to comply with regulatory requirements by reducing the risk of errors and omissions in compliance checks.

Additionally, EY found that 76% of financial organizations uses RPA to improve their accuracy and compliance. Another HFS Research found that organizations using IA reported an average reduction in errors of 25-30%.

Having said this, you can see how IA significantly reduces the scope of errors in high-volume transactions. 

Enhanced Fraud Detection and Prevention

Fraud detection and prevention is a critical issue for fintech organizations! As fraudulent activities leads to financial losses and damage to their reputation. This is where IA can help firms detect and prevent fraud more effectively. IA will detect and prevent fraud by monitoring transactions in real time. And use predictive analytics to identify suspicious activities.

According to a report by Cognizant, IA has helped a top-tier North American bank to detect 90% of fraudulent activities. Enhanced fraud detection and prevention through IA helps financial firms to detect and prevent fraudulent activity more effectively. Also, it reduces the risk of financial losses and reputational damage. Let’s see, How: 

• ML algorithms can analyze large amounts of data to identify patterns that may indicate fraudulent activity. For example, multiple transactions from different locations within a short period of time. It can detect if the transactions are significantly higher than the customer’s average spending.
• RPA will automate the process of freezing compromised accounts, reducing the time it takes to respond to fraud incidents.

• IA can help firms to comply with regulatory requirements related to fraud detection and prevention. It may include Payment Card Industry Data Security Standard (PCI DSS).

So, with the power of IA tools and predictive analytics, firms can now deal efficiently with fraudulent cases. Also, it will allow them to take swift actions to prevent further loss and comply with regulatory requirements.

Cost Savings

Intelligent Automation (IA) possesses the potential to deliver substantial cost-saving benefits. How? Well, by automating processes that previously required human intervention, firms can reduce labor costs and increase operational efficiency. And there’s more to it!

Here are some key ways in which IA can lead to cost savings:

• Reduced labor costs: Automating repetitive and low-value tasks can reduce the need for human labor, leading to significant cost savings. For example, a bank might use RPA to automate the process of account reconciliation.

• Increased operational efficiency: A wealth management firm might use ML to automate the process of analyzing investment opportunities. It will reduce the time it takes to identify profitable investments.

• Improved accuracy and quality: IA improves the accuracy and quality of work, reducing the costs associated with errors and rework. For example, an insurance company might use ML for claims processing, ensuring that claims are processed accurately.

• Reduced infrastructure costs: Firms can use cloud-based services to automate their back-office operations, reducing the need for expensive hardware.

Additionally, McKinsey & Company estimated IA technologies can lead to cost savings of $1 trillion in the financial industry by 2030.

By following these steps, your business can be leveraged with the power of automation paving a clear roadmap for success.

Case Studies of Successful Implementation of Intelligent Automation in Financial Services

Here are a few case studies of financial firms that have successfully implemented IA to improve their operations, customer services, and overall profitability:

a) American Express: The company has implemented ML algorithms to analyze transaction data to identify potential fraud. By using IA to detect and prevent fraud, AMEX has reduced their losses and improved profitability.

b) Bank of America: BOA has used RPA to automate the process of mortgage processing, reducing the time it takes. They also used chatbots to improve customer service, enabling customers to easily get answers to their questions.

c) Allianz: The insurance company has implemented ML algorithms to analyze claims data and identify patterns that can indicate potential fraud. 

d) Charles Schwab: Charles Schwab has used IA to improve its customer service capabilities. By using IA to improve customer service, Charles Schwab has been able to improve customer satisfaction and retention.

To sum up, Just like these firms, you too can optimize your operations and achieve a competitive advantage in the marketplace.

Future of Intelligent Automation in Financial Firms

IA has already made significant inroads in the fintech industry, but its impact is only expected to grow in the future. 

Here are a few ways in which IA is expected to continue to transform the industry: 

• Enhanced Risk Management: Another area where IA is expected to have a significant impact in risk management. By using ML and other IA technologies, financial firms can better identify and manage risk across a range of areas. It includes fraud detection, cybersecurity, and compliance.

• Greater Accuracy and Precision: ML and IA tools are expected to become even more precise and accurate in the future. This will enable financial firms to make better decisions, reduce errors, and improve the quality of their output.

• Adoption of Advanced Analytics: Technologies like predictive and prescriptive analytics will allow firms to gain insights into their operations. It will open up routes for better decisions and improve profitability.

It is clear that firms embracing IA will be better positioned to meet the changing needs of their customers. Additionally, it will manage risks effectively, increase efficiency, and achieve a competitive advantage in the marketplace.

Bottom Line

So, You see how revolutionary Intelligent Automation can be for financial services firms! 

Since, I provided you with real-world case studies of firms that have successfully implemented IA to boost their operations- You are now aware of how exciting the future of IA in financial firms is! And how it can improve risk management, precision, accuracy, and advanced analytics.

So, Don’t miss out on the competitive advantage that Intelligent Automation can bring to your firm! Contact TheCodeWork Today!