Artificial Intelligence [AI] empowers lending to a new level, and it helps both lenders and borrowers make better decisions.
Especially, lenders can benefit a lot from the use of AI in Lending businesses as AIs help to redefine business models that focus on customer experiences. And we all know customers are supreme in every industry.
In 2022, we shall come across some of the biggest trends shaping AI in lending that will change the approach to conducting business across all platforms. Whatever the trends shaping AI, they will elevate customer experience, accelerate unbiased lending practices, reduce the lending life cycle, provide better risk management, and boost companies’ growth.
8 Biggest Trends Shaping the AI in Lending in 2022:
- The massive necessity of AI in the Lending Industry
- Outlay Optimization and Scalability for Growth
- Accelerate unbiased and inclusive practices
- Increased Demand for AI experts
- Reduction in Time of Lending Cycle
- Enhancement of Customer Experience
- Improving data structuring
- Cybersecurity and Risk Management
Let us jump into eight [8] of the biggest trends shaping AI in 2022.
1. The massive necessity of AI in the Lending Industry
Gradually the lending industry is shifting towards a completely digital scenario. Whether to meet the market fluidity or fulfill customer demands, the lending industry has realized the need to incorporate AIs and ML [Machine Learning] into their businesses.
IDC has predicted that businesses investing in AI technologies will increase to 97.9 billion dollars by 2023. AI will soon become a crucial spine of any company’s structure. The ones that hesitate to migrate their businesses toward digital platforms will fall behind, and in addition to that, the implementation of AIs and ML will become mandatory.
Most banks, fintech, financial establishments, and lending industries will enforce AIs and ML simultaneously in their businesses for whatever reason [mentioned above] globally. We are destined to witness AIs and ML taking over the traditional approaches.
2. Outlay Optimization and Scalability for Growth
Financial sectors and fintech can significantly reduce their expenses [outlay] and boost a considerable company’s growth using AIs and ML. We know that digital lending has become mainstream for lending firms, fintech, and banks because of its transparency and unmatched performance.
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AI and ML perform better and faster than manual processes, which scales the companies’ productivity and generates profitable revenues. Lending companies need to invest in AIs and ML and experts to operate them, eliminating a massive human resource and other infrastructures optimizing the investment.
Significantly lower investment in AIs will generate greater revenues, which means only the lending industry’s rise. Optimization and scalability are one of the biggest trends shaping AIs in lending.
3. Accelerate unbiased and inclusive practices
Traditional lending approaches have shown biased outcomes, which has made it difficult for people of diverse backgrounds to obtain loans. Humans involved in analyzing and processing loans are affected by emotions and environmental situations, creating biased decisions. These decisions are slow and not fruitful to a lending firm.
Lending firms can incorporate AIs in their business to eliminate such human errors and emotions. AIs solely process and analyze data to generate data-driven recommendations and real-time solutions to accelerate unbiased and inclusive practices in the business.
AIs in the lending industry will serve everyone equally regardless of race and cultural background. Lenders and borrowers will both benefit from the competence acquired through automation. Providing unbiased services to customers is one of the biggest trends shaping AI in lending from 2022 onwards.
4. Increased Demand for AI experts
As the quantity of Artificial Intelligence [AI] deployment in lending industries increases with time, the requirement for AI experts to monitor and maintain the AIs will only rise. Eventually, all the businesses from all sectors will need to integrate AI, skyrocketing the AI expert requirements.
It creates a requirement for skilled and experienced IT and AI experts. Not everyone working in the lending firms can understand and cope with the abilities of the AIs. AIs come with various features and functionalities which require dedicated personnel to operate and maintain proficiency.
To cover up the persistent gap between demand and supply, we should encourage young talents to be invested and well taught on the subject. Qualified experts should be allowed to train and nurture the young generation to grow up to meet the future demand for AI experts.
The experts on AI technology can work on the AIs to become more automated and require less human intervention to perform their tasks. This technological advancement will help the lending industry as they do not have to invest more in experts as the automated AIs perform complex tasks themselves.
5. Reduction in Time of Lending Cycle
We all know manual analysis and recommendation on digitally processed data takes time and is erroneous. The traditional approach is based on manual work culture, which is extremely slow. It may take days or even weeks to process loans using a conventional method.
You can reduce processing loans from weeks to a few hours using AIs. Usually, the documentation in the initial phase of loan processing consumes a lot of time, but the implementation of AI will automate the process digitally. Digital data collection and processing are fast and more reliable.
AI Lending companies can enable automation throughout the lending cycle to reduce time consumption and generate accurate recommendations. These recommendations are data-driven, which firms can easily trust and act upon whether to further work on it or discard it.
AIs and ML, in conjunction with NPL, can ease your lending company’s overall task and reduce the lending cycle without compromising on efficiency and effectiveness.
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6. Enhancement of Customer Experience
Service providers will digitalize every service within a few years to match the market fluidity. Businesses should leave conventional methods behind and embrace modern business approaches. If not, they will fall behind, and competitors will have an edge on them.
The next thing is lending firms should consider their customers’ needs and reshape their company’s structure to enhance customer experience. Customers want every task available on their smartphones ranging from personal to official.
Lending businesses should meet these demands on time, keeping customers happy and willing to invest in their firm. McKinsey states that many fintechs have remodeled their businesses to redefine and meet customer expectations.
Customer demands and expectations give rise to complex processes that involve cross-platform operations and numerous cross-functional teams. These processes increase the investment of lending firms with a low ROI [Return On Investment].
AIs and ML provide useful recommendations to lending companies to work on for better customer experience and data-driven decision-making. A well-integrated AI technology with an ML model will enhance the lending process by reducing investment and increasing ROI and efficiency.
So AI implementation will help lending firms to elevate their reach and functionality, considering the customers’ demands and expectations at the same time.
7. Improving data structuring
AI has an enormous capability to work on both structured and unstructured data to produce meaningful patterns and information, which helps the lending businesses to identify threats, and new opportunities, build schemas, and improve customer experience.
Lending establishments can utilize those technologies to create or demand an RPA [Robotic Process Automation] technology from the service providers, which helps automate transactional activities in the sales automation.
AI will eliminate the limitations of RPA to access any types of data that eventually benefit the lending industry to provide predefined output using the RPA. Businesses will be able to use unstructured data like videos, audio, images, log files, etc., to their advantage and produce meaningful patterns that will help them with risk management, data-driven analysis, and decision making.
Improving data structuring is one of the biggest trends shaping AI in lending.
8. Cybersecurity and Risk Management
As everything gets digitalized in the lending business, it becomes difficult to detect and control threats in real-time manually. Even if it is possible to eradicate threats manually, you cannot cope with them as they keep evolving and increasing. AI comes into the equation for these kinds of problems.
In 2022, the global risk report by World Economic Forum has placed cybercrimes as potentially carrying a more influential risk than terrorism.
Implementing AIs and ML in conjunction with NPL makes everything easy and more convenient in managing risk and improving cybersecurity. Artificial Neural Networks are extremely efficient and effective in analyzing and evaluating interactive and linear patterns, and AIs use these patterns to assess threats and loopholes in the system.
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It warns you about the dangers and recommends solutions, and even carries out operations to eradicate the problems.
Lending firms can use the data-driven patterns and recommendations for training purposes and provide feedback to the AI developers to work on those for better updates. A constant upgrade on the AI technologies can handle all types of cyber attacks in real-time, saving lending firms and their valuable data.
AI uses a similar method to build an AI-based, automatic credit decision system. This system edges over conventional underwriting operations with more data points to access risk management. The AI used in the system will provide you with accurate and effective details to make decisions efficiently on time which facilitates your customers and benefits your establishment.
Cybersecurity and risk management are the other reasons for the biggest trends shaping AI in lending in 2022.
Bottom line:
Lending platforms will benefit immensely from an AI incorporation in their businesses. The need for AI will only rise with time as customers’ demands stack up with time which requires AIs, MLs, and NPL to address them collectively. AIs power holistic experience by eliminating silos to aid lenders and borrowers with better data-driven decision-making.
