Artificial Intelligence drives greater efficiencies and competitiveness in the financial services industry. NVIDIA reports that 91% of financial organizations use some form of AI, and 43% are piloting Generative AI to optimize financial reporting and customer experience.

Finance leaders can harness AI for greater efficiency by knowing its benefits.

Artificial Intelligence in finance transforms five key areas:

1. Fraud Detection and Prevention

Are you using a legacy Anti-Money Laundering system to detect fraud? Do your customers often report that your banking app is declining their transactions?

Traditional, rule-based Anti-Money Laundering systems generate many false positives. Even valid transactions are declined in the system. Thanks to AI-based fraud detection, the incidence of false positives has steadily dropped.

AI-powered financial solutions process data faster than legacy AML systems. AI brings more precision in differentiating normal and fraudulent customer behavior.

AI can detect and flag anomalies by monitoring financial transactions in real time. It helps keep apps and payment methods free of fraud. Using AI, banks can combat scams like illicit use of customers' personal information.

AI models use machine learning algorithms that self-learn by processing historical data. These ML algorithms can adapt to evolving fraud patterns and build predictive data models to mitigate fraud with minimal human intervention.

2. Credit Scoring and Risk Assessment

A credit score is a crucial parameter used by banks to determine a borrower's eligibility. It tells the bank whether to approve or reject a loan applicant's request.

Conventional credit scoring methods rely on credit history data, which is often limited. Due to subjective credit assessments and scoring, some individuals get excluded or underrepresented. AI promotes fairness in credit scoring by reducing subjective judgments in credit decisions.

AI can analyze large volumes of data related to borrower behavior. AI-based assessment counts an individual's past loans, debts, missed payments, and more. It helps lenders identify whether there is any potential risk in lending.

AI-powered credit scoring and assessment increase lending organizations' target audience. Through unbiased analysis, borrowers get a fair chance to prove their creditworthiness. Lenders can make informed decisions by monitoring changes in a borrower's condition.

3. Personalization of Customer Experience

Customers trust financial organizations that stand for their fiscal well-being. They want to cut the hassle of manual work, like exhaustive paperwork and bank visits. How can you deliver customers the experience they seek at the moment? The answer is right here: AI-powered personalization.

AI-driven recommendation engines enable banks to offer personalized services tailored to every individual. AI systems can tailor investment advice and banking offers based on customer journeys.

AI-powered chatbots, virtual assistants, and robo-advisors can provide contextual support to each user. Contact centers can reduce customer wait times by letting AI handle their queries.

AI applications in financial services give customers more autonomy. It saves your employees' time, helping them focus on high-value tasks. Data-driven insights and predictive analytics save financial leaders from making wrong guesses.

4. Financial Document Analysis and Processing

Financial document processing is crucial in ensuring regulatory compliance and identifying anomalies. Imagine a person sitting and scouting thousands of pages every day! Applying AI in document processing frees financial professionals for more strategic endeavors.

AI uses three primary techniques to analyze and process financial documents:

Machine Learning: ML algorithms use historical data to identify document structures. They extract only relevant data from the documents and then categorize the content.
Natural Language Processing (NLP): NLP helps machines understand and interpret human language. NLP can extract meaning from unstructured text. It identifies entities (names, dates, amounts) and comprehends the context.
Optical Character Recognition (OCR): This technology helps digitize physical documents. It converts scanned images or handwritten text into machine-readable formats. OCR recognizes characters, digits, and symbols from scanned documents. Converting physical documents into actionable digital data saves the time of financial professionals.

5. Financial Reporting and Analysis for Informed Decisions

Reporting has been a pertinent problem for banks and financial institutions worldwide. Regulators demand comprehensive reporting that requires more granularity in data submissions. Accurate interpretation of reporting requirements and data sourcing are costly and labor-intensive.

Using AI in financial reporting makes the data more transparent and accessible. Companies can use AI to simulate market conditions and cash flow predictions. With accurate reporting and up-to-date insights, companies can improve budgeting decisions.

Reporting leaders can use responsive AI visualization tools to infer insights from data. Financial auditors can use AI to reduce the risk of human errors in data reconciliation.

Today, many financial leaders rely on Natural Language Generation (NGL), a subset of AI. NGL-enabled reporting automation speeds up data retrieval, processing, customization, and report generation.

AI in Finance: The Way Forward

AI-driven solutions are now a competitive differentiator for financial services companies.

Innovative AI solutions in finance can:

Learn from new data and adapt without explicit programming.
Revise AI algorithms based on new data to make predictions.
Judge each prediction to recommend potential next steps.

Embracing AI in finance functions is the way forward for CFOs. Companies can reap success with customized software embedded with AI finance features.

5 Ways Artificial Intelligence Transforms Financial Services