Most organizations constantly generate, gather, and process huge amounts of data. The biggest challenge these firms face is transforming this data into actionable intelligence that boosts operations effectively.
Other concerns of such organizations include:
- Difficulty in identifying and deriving data from multiple sources or reporting solutions.
- Inconsistent governance at the cost of integrity, quality of results, availability, and usability of data.
- Inefficient reporting of processes due to non-standardized methodologies.
- The lack of technical capabilities to meet business demands.
Before getting to how Artificial Intelligence (AI) can help overcome these challenges, let’s consider the role of AI.
Understanding AI
AI enables machines to adapt, learn, and improve to obtain optimal results. When powered with AI, machines are able to monitor key data, action, and workflows. AI-enabled machines can discriminate between positive and negative actions and react contextually.
Lease management solutions equipped with AI employ such characteristics and keep changing with shifting preferences to deliver optimal results.
A
survey by
McKinsey & Company shows that organizations tend to implement AI in functions that provide maximum value in their industry. Note that telecom, high tech, and financial services have been incorporating AI heavily in their service operations.
Artificial Intelligence in Various Industries
Technavio has predicted that the global telecom IoT market will post an impressive CAGR of more than forty two percent by 2020. This growth is meant to be driven by AI.
According to
Forbes, sixty five percent of senior financial management trusts that AI has a positive impact on financial services. Chief Scientist and AI guru, Ben Goertzel and his team at
Aidyia, built an AI-enabled system and continue to modify it. The system identifies and executes transactions on its own. It can derive multiple forms of complex scenarios using AI. These scenarios are based on genetic evolution and probabilistic logic.
Even the manufacturing sector is catching up with other industries in employing AI capabilities to support sound decision-making. A
market research report states that the artificial intelligence in manufacturing market which was valued at around USD 1.0 billion in 2018 is expected to reach USD 17.2 billion by 2025, at a CAGR of 49.5 percent from 2018 to 2025.
An AI-powered system helps organization across industries perform thorough analyses from the volume, market prices to macroeconomic data and corporate accounting documents. These systems make their market predictions and automatically opt for the best-suited course of action.
AI Machines for Lease Management Solutions
To understand how AI works for industries better, let’s take the example of a financial firm that uses intelligent lease management systems. Typically, this system will need to differentiate between a good loan and a bad loan. Here, the AI machine depends on its experiences from previous loans that have been approved. This is a supervised AI machine.
Furthermore, an unsupervised AI machine can simply categorize piles of loan data based on their characteristics like the industry it pertains to, amount of loan required, and the credibility.
Supervised and unsupervised AI, as an integral part of lease management systems, will be able to:
- Revolutionize credit approval processes by providing insights into how well the deal fits the firm.
- Provide repayment structures that can adapt to changing customer preferences.
- Optimize and automate workflows, leading to faster decision-making.
They can also help boost efficiency in the following ways:
1. AI for Decision-Making
Let’s understand this point with the help of an example of credit decisions. AI speeds-up processes by providing an accurate assessment of the potential borrower. It costs less and is based on a holistic view of the scenario. This results in a better-informed, data-backed decision.
Lease management systems that implement AI for credit scoring are based on complex rules. They are more dependable and unbiased than traditional credit scoring systems. An AI-enabled system can help financial firms with transparency to differentiate between a creditworthy applicant and a high-risk applicant.
Furthermore, it helps move a credit request into a workflow for approval or for further review. It provides intuitive insights that help in making critical decisions.
2. AI for Risk Analysis and Management
AI processes massive amounts of data in a short time. Cognitive computing, as a part of AI systems, simulates human thinking. It helps manage both, structured and unstructured data that will take a lot of time for humans to deal with. AI-enabled algorithms thoroughly analyze the history of cases and identify potential risks at its nascent stage.
Systems powered by AI analyze real-time activities, provide accurate predictions and detailed forecasts based on multiple variables.
According to Samir Hans, advisory principal at Deloitte Transactions and Business Analytics LLP, “With cognitive analytics, fraud detection models can become robust and accurate. If a cognitive system kicks out something that it determines as potential fraud and a human determines it’s not fraud, the computer learns from those human insights, and next time it won’t send a similar detection. The system gets smarter with experience.”
3. AI for Fraud Identification and Prevention
AI in lease management systems can help detect fraud by analyzing customer behavior, location, and buying preferences. This system triggers a security mechanism to check if anything is out-of-order or contradicts the existing spending pattern.
For example, AI helps financial firms curb money laundering. AI-enabled systems help detect suspicious activity and cut costs needed to investigate such alleged money-laundering scenarios.
This
case study elaborates on how a financial firm improved operational efficiency by three percent and reduced investigative volumes by twenty percent.
4. AI for Disputes and Deductions
AI helps identify and assign reason codes or categories for root cause reporting. It also implements the necessary preventative measures. An AI-enabled system can also approve disputes and deductions, based on predefined conditions and automatically route them for resolution through advanced workflows. This accelerates the resolution cycle time and improves cash flow.
5. AI for Payment Processing
AI-enabled systems identify remittance layouts and increase the hit rate for auto-applying payments to invoices. They monitor and learn from exception processing. These systems then apply this experience to the future processing of payments, which helps eliminate errors, reduce processing time, and decrease backlog. Such systems also create more time to focus on other core activities.
As we understand, the advantages of AI across industries are endless and hard to ignore. It frees employees from redundant tasks and helps them focus on strategy and building better customer relationships. All progressive firms should look forward to utilizing this technology and obtain incremental improvements for sustainable growth.
Jack Warner is CFO at Pulpbiz.com