Artificial Intelligence (AI) is slowly sneaking into all industry verticals and revolutionizing how companies handle their internal processes, logistics, communications, and other facets. It was only a matter of time before the financial sector etched AI algorithms to streamline procedures, safeguard transactions, mitigate fraud, and maximize savings.
AI for detecting frauds in the financial services industry worldwide as of 2020 is at a whopping 58% – Statista
New-age fintech or even traditional financial institutions can’t ignore the limitless potential of AI. From evaluating cash flow to automating tedious tasks to sending alerts on new invoices, capturing early discounts, managing overdue payments, or other aspects, AI has become indispensable in the financial sector. Let’s look at how AI transforms the financial industry.
The Future of AI in Finance – 2022 and beyond
AI is futurizing the financial sector. What was once a highly slow and speculative domain has become more data-driven and automated, thanks to AI. Artificial intelligence coupled with Robotic Process Automation, has managed to simplify underlying activities and make them more accurate and faster. For 2022 and beyond, AI is bound to become an integral component of financial institutions.
AI makes the financial industry more agile and helps it to scale new peaks. A strategic investment-backed AI-driven digital transformation can lower risks, elevate sales, improve productivity, reduce errors, and provide more insights. From a security standpoint or customer-service standpoint, AI is what you need in your lifecycle to elevate and sustain your business model.
Applications of Artificial intelligence in finance
Fraud Detection and Cybersecurity:
Fraudulent actors in the system and external duplicitous payment requests can drain your wealth. Plus, recovering the same leads to a loss of time, effort, and regulatory hurdles. Fraudulent internal and external payments that reduce cash flow and eat into your capital are something that organizations are proactively looking to avoid.
If there’s an activity or the AI detects a data mismatch compared to the data in the master record, it can send a notification or alert the concerned heads. The alert acts as an early intervention and prevents losses. AI can detect irregularities in real-time, catch an intrusion, detect patterns, and compare with historical assets to ensure safety.
Automating processes:
Manual processes are slow, laborious, delayed, and error-ridden. In this scenario, you need Artificial Intelligence (AI) to optimize processes and speed up operations. AI can automate routine and repetitive tasks that would otherwise require multiple resources. AI lets you accelerate predictive chores that take time and therefore delay closures.
More financial institutions are relying on AI for keying data and extracting information. Furthermore, they use AI to transfer documents, schedule jobs, send reminders, and complete other tasks involving longer cycles. AI makes it easier for employees to work on more value-driven tasks and free them from wasteful activities that don’t create any returns for the business.
Data Analysis and Learning:
Manual data analysis from disparate sources often results in multiple versions of truth and often leads to data silos. Businesses of late are entrusting data analysis to AI and ML to help ingest, cleanse, analyze, archive, and uncover valuable insights. Manual data retrieval leads to incomplete and redundant data that gives very little value.
Businesses even use AI as a data mining tool to forecast future trends based on past patterns in stock price predictions, revenue forecasting, and risk monitoring. This helps companies steer clear of any potential hurdles. AI plays a crucial role in data modeling, data governance, and data management to identify opportunities and flag bottlenecks that could potentially jeopardize the business.
Risk Assessment:
AI can evaluate unstructured data and go through several scenarios and variables to catch risky behaviors or activities in the operations. AI algorithms can scan and identify critical risk patterns and send real-time alerts to avoid incidents. AI can even warn you about compliance risks and governance issues that can cost your company a fortune.
AI and deep learning can identify oversights, errors, and gaps that no human can. AI embedded in your risk management system can detect loopholes in contracts early on, help with audit trails, and identify bad loans (lending). Furthermore, AI can handle credit risks, catch rogue traders, monitor card transactions, detect insider trading & market manipulation, and handle preliminary screening.
Trading:
Businesses use AI in quantitative, algorithmic, or high-frequency trading to analyze large data sets in real-time. AI processes data faster and sends out alerts on stocks, giving you enough time to spring into action. Hedge Funds, mutual funds, and capital management firms employ AI to track stocks that witness sudden upswings or dips for new positions or exits.
Loan behavior:
To evaluate loan eligibility, financial institutions may need to run a host of credit history checks and complete a risk assessment of the candidate. The AI in place can improve loan underwriting and decide based on the lending-decision rules. Plus, AI can monitor already given out loans in the system to identify if installments are arriving on time.
Customer Care:
AI can also handle mundane and tedious tasks such as customer queries, grievances, and other standard queries. AI can answer inquiries on failed payments, non-payments, account setup guidance, and finance hacks with minimal employee input. Free up your resources and have them focus on value-driven projects that drive innovation. Chatbots and Virtual Assistants using AI at the core can manage and speed up customer-centric tasks 24/7, without any breaks. Companies can feed AI solutions generic questions and possible answers to help customers navigate their problems.
Benefits of using AI in Finance
Time-efficiency:
Bulk interactions, transactions, contracts, paperwork, customer bank details, and other such data can prove overwhelming for humans. An AI tool with complex algorithms can instantaneously analyze different conditions, variables, and unique patterns. An investigative workload like this would otherwise take forever. AI can run through this in a fraction of a second.
Enormous processing power and cognitive computing within an AI tool allow it to process vast amounts of unstructured data in a short time. Algorithms can analyze risk cases, identify mismatches, catch redundancies, and flag incomplete info and other irregularities on several documents in near real-time.
Accuracy:
Manual errors and oversights from employees on financial records or spreadsheets can ruin compliance procedures, lead to regulatory fines, and possibly break your bank. From contractual obligations to invoices, you want to let AI oversee the document in the preliminary stage before it’s cleared. Data entry mistakes can also prove costly if you don’t run them past AI.
Most companies employ an AI in the earlier stages to avoid leaving the error-ridden data keying to resources. AI can better detect & populate data and automate the key processes to overcome manual intervention. Artificial Intelligence pulls, validates, and records the correct data in the proper sequence.
Regulatory hurdles and Compliance: Data security, privacy, and having a detailed audit trail of the role-appropriate actions taken across the organization can help during regulatory checks. Financial institutions can rely on AI to build a governance model that detects compliance risks early and preserves integrity in line with the rules and regulations.
Personalization:
Hyper-personalized financial instruments or investment schemes tailored to your wealth creation goals, risk appetite, and securities can help reduce the workload on employees/customers. No need to manually develop a suitable plan for their unique profile. Feed the data into the AI tool. It will consider various parameters to suggest the best investment strategy and options. AI, as an omnichannel force can deliver these custom recommendations across any touchpoint. The decision-making layer with AI collects a 360-degree view of the customer, analyzes the granular data meticulously, and creates personalized messages.
Overall Savings:
Reducing the resources, improving operational efficiency, and lowering the time will lead to monetary benefits. Banks and fintech apps will realize more profits through hyper-personalized offers. Plus, failed transactions, loan defaults, and fraudulent payments come down. Your workforce can now invest in strategic activities that create incremental value addition.
Financial Firms That Are Using AI
Bloomberg:
Devised Alpaca Forecast that uses AI to detect fluctuations in the stock market for recommendations
Crest Financial:
Used AI to analyze quality risk data points, keep records & logs, and remain transparent and unbiased about
Plaid:
Uses AI for fraud monitoring and detection for anti-money laundering, financial screening, and ongoing customer diligence
Bank of America:
Mobile app running on AI helps to plan expenses, provide reminders, and make interactions much smoother
Wrapping Up
Unlock more value from your financial ecosystem by embedding Artificial Intelligence (AI) at the core. AI technologies can help accelerate processes, detect bottlenecks, suggest possible solutions, identify opportunities, lower costs, and enable rapid innovation. AI could even scan the market to identify trends to help launch something along those lines.
Becoming an AI-first institution is a challenging road that requires you to identify potential areas where AI can play a significant role. Thus, establishing a monetary logic of re-engineering the right mix of diverse processes. Either way, you need a comprehensive roadmap, stakeholder alignment, and a reliable ally to see this through – who better than the experts at ISHIR?