How MFI, NBFC, and Banks can Operate at 10x Faster Speed and Generate More Profits

The key to operating at 10x faster speed

How MFI, NBFC, and Banks can Operate at 10x Faster Speed and Generate More Profits

By using digitized technologies, MFI companies, banks, and non-banking financial companies have started to make more money. A company must adopt the right technologies to grow faster in this situation. At the same time, such businesses can reduce their operational costs to a large extent by implementing the technologies.

People have become well-accustomed to digitalized financial transactions nowadays. Therefore, the mobile banking service brings more customer satisfaction. On the other hand, digital processing of various financial services saves people time. Banks and other financial institutions can reduce loan processing by simplifying KYC verification and implementing the latest technologies. In the following section, you can find a guide on how financial institutions can operate faster and generate higher revenue.

Table of Contents

Advanced Self-Service Capability

An advanced self-service capability will help small-scale financial companies to a large extent. The banks often hire third parties to deal with various jobs. For example, a third-party service provider is required for KYC verification. Technology can help banks and other financial institutions adopt self-service capabilities. The financial companies will perform multiple complex tasks without requiring any third-party intervention.

On the other hand, banks and other financial institutions must offer self-service facilities to customers. People want banking services without the hassle of a long verification process. Moreover, people also seek transparency in financial transactions. A digitized platform ensures transparency and provides a self-service facility for customers. Financial institutions can render more satisfactory services to customers with minimal interactions.

API integration for Task Management

A financial organization may have to deal with multiple non-skilled and repetitive tasks. Hiring employees to manage such tasks increases the organization’s operational costs. At the same time, the efficiency of humans is limited. You can get an output at a particular level from a human employee.

The APIs can manage various repetitive tasks with precision and achieve higher efficiency. Moreover, API integration helps financial organizations reduce their dependence on human workers. Many tasks will be automated, which eventually reduces operational costs. As a result, financial organizations can become more profit-making institutions.

Instant Payment Processing Networks

Payment processing is a concern for both small and large financial institutions. Imagine that you run a lending company or a MFI. People expect faster loan processing from such companies. However, quicker loan processing is not the easiest thing to achieve for financial institutions.

Developing a secure payment processing channel is essential. Conventional payment processing is time-consuming, and you can reduce the time by embracing electronic payment.

A digital payment process can happen instantly. However, it may take one to three days for MFIs in most cases.

Cloud Computing for Easy Data Access

Data is the most important thing for a business, and today’s financial institutions make decisions based on data. When you collect and understand data in the right way, it will help your financial institution make better decisions. Most banking and non-banking financial companies invest in developing a powerful cloud infrastructure.

Cloud infrastructure provides easy data access to companies. Financial companies can maintain company portfolios and customer data on cloud storage. Data stored in the cloud is accessible anytime, and KYC verification is expedited. Nevertheless, financial institutions often check the data of loyal customers to provide better services. The overall financial verification will happen seamlessly with the cloud data storage.

Biometric Technology for a Faster Identity Verification

The financial industry has been developed on the foundation of trust. Developing trust is essential to improving customer satisfaction. At the same time, businesses should build a trustworthy brand by adapting to standard security practices.

Biometric technology has become a key technology in such a scenario. The technology assures seamless security in the verification process. Moreover, it brings quicker identity verification for financial institutions. As a result, loan requests have been processed faster due to digital identity verification.

Chatbots for an Automated Customer Support

Besides selling a product, financial organizations must render seamless after-sales service. The customers may have multiple queries regarding a product. Nevertheless, they may inquire about obtaining certain information from a financial company. In such cases, small financial institutions and non-banking companies need help managing a separate customer support department.

Instead of recruiting humans for customer support, implementing chatbots can be more cost-effective and productive. The chatbots deliver all necessary information to the customers without requiring human intervention. With the advent of time, chatbots will become more efficient in providing information to customers or clients.

Process Automation through AI and ML

Intelligent Automation is another key technology for MFI and non-banking financial organizations. The banking sector has already implemented automation and started reaping the benefits. Nowadays, banks can manage multiple tasks without human intervention. Small-scale financial companies should also focus on automation to reduce operational costs.

Artificial intelligence can make an organization less dependent on human resources. Various non-skilled tasks will be performed quickly and accurately. At the same time, machine learning can slowly take over a skilled job while making it easier to manage.

Facilitating Micro Services

Traditionally, the banking sector works with a monolithic approach, which refers to a uniform approach for everyone. But financial requirements vary from one person to another. A lender should check the creditworthiness of a person. Every person has a unique credit behavior, and financial companies must understand their clients with precision.

Understanding the clients helps financial institutions provide various MFI services. 

Instead of adopting one approach for everyone, financial companies can offer more customized products for their clients. Introducing such products will enhance the credibility of financial institutions to a large extent.

Internet of Things for Faster performance

Financial companies must embrace the Internet of Things (IoT) to improve performance. The technology helps with faster payment processing. Moreover, financial institutions can introduce smart notifications for their customers. The Internet of Things can also help in developing and managing digital wallets.

Advanced Analytics through Big Data

Financial organizations should adapt to advanced analytics for better decision-making. Making the right decisions is the key to running a business seamlessly. A data-driven approach to decision-making can improve decision accuracy. Moreover, business managers can make critical decisions with more conviction.

Conclusion

So, these are the technologies that MFI, non-banking, and banking institutions can adopt to improve productivity. Technology helps financial companies render better services to their clients. Moreover, adapting to the latest technologies improves organizations’ security of sensitive data. As a result, NBFCs and banks can reduce operational costs and improve revenue. The overall profitability of such organizations increases drastically.

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How Intelligent Automation Is Transforming Financial Services

Intelligent Automation Watering the Seeds of Digitization in the Financial Services Sector

How Intelligent Automation Is Transforming Financial Services

Companies in the financial services industry have long embraced automation. Businesses today consider it a necessity to explore the potential of Artificial Intelligence (AI) to generate value through enhanced revenue, customer service, efficiency, and risk management.

According to surveys, the financial services sector accounts for 29% of the total market for Robotic Process Automation (RPA), which is more than any other industry. So, it makes sense that the sector is an early adopter of Intelligent Automation, which combines RPA and AI. And the future looks even more promising!

“Intelligent Automation,” which combines the benefits of Robotic Process Automation (RPA), Artificial Intelligence (AI), and Human Intelligence, will drive the future of financial services organizations. This entails the skillful application of a variety of automation techniques and tools, ranging from the incorporation of simple robots to the complete digitization of systems and processes.

Financial institutions have embraced a variety of use cases for Intelligent Automation, ranging from straightforward cognitive service connections into RPA systems to, in a few instances, AI-powered decision-making. Sounds interesting right? So, let’s dive in to experience the top applications of Intelligent Automation in the financial sector.

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Applications of Intelligent Automation

Curious to know about the magic spilled by Robotic Process Automation in banking? There are many applications for Intelligent Automation in the financial services industry. Let’s list some top ones here:

Detection of money laundering

One of the primary applications of Intelligent Automation in the financial industry is fraud detection because it not only expedites procedures but also improves the effectiveness of finding instances of money laundering. It gathers client and counterparty data from a variety of sources and issues warnings about possible AML transactions.

Automated financial consultants

These computer systems, also referred to as “robo-advisors,” offer financial advice with little to no human interaction. Using Machine Learning, they develop a unique financial strategy for each client based on characteristics like age, investment objectives, and risk tolerance.

Automated trading

It is a type of financial trading where automated choices are made using sophisticated algorithms. To trade equities, bonds, foreign exchange, and other financial instruments, banks, hedge funds, and institutional investors use this.

Transaction analysis and risk monitoring

In financial services, Intelligent Automation enables quicker data processing, precise forecasting, and the early detection of possible issues.

Document processing and scanning

Several manual operations can be automated thanks to Intelligent Automation, including the creation of customer accounts, which take a lot of time to complete. By extracting important data and information and examining legal papers, its use in financial reporting enabled data verification and improved reporting. Financial services organizations may change manual and data-intensive procedures with Intelligent Automation while still adhering to constantly evolving regulatory standards.

Personal finance management

AI is being used by an expanding number of personal financial management (PFM) apps to assist users in managing their finances. They can keep tabs on your spending, provide budgeting guidance, and provide recommendations for how to spend your money. Further “round-up” functions that automatically invest your spare change are now available in several PFM programs.

Blockchain

A decentralized, distributed ledger that records financial transactions is known as a blockchain. It is safe and impervious to tampering, making it the perfect platform for financial institutions. Companies utilize it to improve security, cut expenses, and streamline business processes. Banks, for instance, use blockchain to settle international payments and trade finance agreements.

Accounting closure

Supporting a financial closing is one of the top RPA in banking use cases. A sub-ledger must be maintained for all of the year’s spending, receipts, and transactions, which takes a lot of work. Companies can automate the process of data extraction and recording in the appropriate sub-ledgers thanks to RPA technology. You don’t need to account for hundreds of invoices, receipts, and paperwork. RPA assists staff members with closing yearly and monthly accounts by delivering the appropriate data at the appropriate time and in the appropriate format.

Peer-to-peer lending (P2P)

People can borrow and lend money through P2P lending, a financial technology, without using a traditional financial institution. Borrowers can get money more quickly and affordably, and lenders can make interest on their loans.

Enriching customer services

Intelligent Automation simplifies locating the most suitable financial products for customers while maximizing sales and customer support. A few examples of use cases in this area include – the introduction of chatbots in financial services, which decreases waiting times and gives clients a self-help option, enhancing the customer experience.

Nearly one-fifth, or 17% of financial services executives, confirm that investing in innovative digital capabilities is a must to prepare for the future. 

By automating application logins or commissioning procedures, financial organizations also empower customer service representatives to enjoy their jobs with the minimum workload, allowing them to provide consumers with better, quicker service.

Advantages of Intelligent Automation in Financial Services

Let’s now concentrate on the advantages of employing Intelligent Automation in the financial services industry:

Automation Intelligence Leads Financial Institutes to the Tech-Ready Future

RPA technology is required due to the increased complexity of financial operations and the ever-increasing demand for excellence from customers. With automation at play, the team can concentrate on direct revenue-generating tasks and innovation.

Truly, the future of the financial services sector appears promising with the development of AI and automation. These innovations will improve transaction efficiency and accuracy, freeing up staff time for higher-value activities. Financial institutions that adopt this cutting-edge technology will be competitive in the future.

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