How Banks Can Leverage Artificial Intelligence
Blog: ProcessMaker Blog
Are banks ready for artificial intelligence? Digital transformation has been a hot topic in banking circles for decades. But many are still trudging through the transformative tech of the late aughts—only 15% of banks who say they started the process before 2018 are complete. A surprising 56% are less than halfway through their transformation. This begs the question: are banks ready to scale AI initiatives?
Banks are in a unique position to take advantage of the vast potential of artificial intelligence (AI). By leveraging AI, banks can streamline their operations, reduce costs, improve their customer service, and better manage their risks. Here are a few ways that banks can use AI to achieve these goals:
- Fraud detection
- Personalized customer service
- Credit risk management
- Compliance and regulatory reporting
- Automate data collection
For incumbent banks, the same barrier that’s held them back for decades will make or break their success with AI: their existing legacy infrastructure.
If anything, AI prompts banks to push the accelerator on strategic digital initiatives. Artificial intelligence projects require advanced computing resources (encouraging cloud adoption), unsiloed data (incentivizing process automation and orchestration), and an IT structure that hastens time to market (championing API integration and modular architecture).
From a data perspective, banks have an ace in their pocket. AI is a perpetual learner, garnering new insights and improving its method as it churns through more and more data—one thing banks have no shortage of. While some stalwarts view the flood of data as an encumbrance, AI finds opportunity. Lower costs, increased revenue, and groundbreaking personalization can crop up from preexisting data. For global banks willing to take the leap, AI can unlock $1 trillion in new revenue.
5 banking functions benefiting from artificial intelligence
To roll out a successful AI strategy, you can’t view the technology as a one-off use case.
The banks uncovering the biggest benefits are those integrating AI into the whole of their operations, moving towards an “AI-first” bank. This means more than a single department dipping their toe into the AI waters, but everyone plunging headfirst into artificial intelligence.
Let’s explore five distinct areas of your bank that can benefit from AI.
Banks are prime targets for fraudsters. With AI, banks can analyze large volumes of data and identify suspicious patterns in new and exciting ways:
- Biometric analysis: Passwords are a dying breed, quickly getting replaced by fingerprints and facial scans.
- Real-time pattern recognition: Passwords and PINs can be easy to guess, but a person’s nuanced behaviors are more challenging to replicate. AI can build a profile of how a user navigates an app: how they swipe, type, and tilt their device. By comparing real-time activity to a customer’s behavioral profile, banks can readily identify fishy conduct.
- Automated KYC: Banks can enlist the help of AI and its machine-learning counterparts to run database checks bankers used to perform by hand.
If this analysis reveals unusual account happenings, then AI can flag activities worth investigating further. AI can also discover oddities that your team may not have on their radar. By automating this process, banks can reduce false positives and improve their detection rates.
Personalized Customer Service
Mass messaging doesn’t move the needle anymore—customers now demand personalization. Their expectation is so high, that 76% of users are frustrated with banks that lack personalized treatment.
AI can help financial institutions analyze customer data to proactively target needs and preferences. Banks can then use this information to develop customized products and services.
For example, banks can use AI to comb customer behaviors to match them with a product. A person might come to your bank’s app through a credit-reporting BaaS product, or a marketing platform pinpoints an obsessive Zillow scroller. AI can weigh such behaviors to identify customers most likely to tap a bank’s mortgage services—and churn out a pre-approved offer instantly.
With chatbots and other AI-powered tools, banks can provide customers with instant, personalized help. AI-related tech like natural language processing (NLP) uses algorithms to read deeply into text and respond conversationally, without human intervention.
Credit Risk Management
Banks need to manage credit risk effectively to ensure their long-term stability. AI can enhance traditional approaches to credit risk management by analyzing data in ways that human beings can’t. The strategy is so powerful that almost 60% of banks are already using AI for risk assessment.
A bank’s ability to predict which customers are likely to default on loans will help it achieve faster accruing loans and more efficient asset recovery. With AI algorithms trained on historical loan performance data (e.g., payment history), banks can develop models that predict future defaults with high accuracy rates while reducing costs associated with manual reviews.
AI also helps banks tap into new data sources to build a more vivid picture of creditworthiness. In many countries, social media behaviors and cell phone usage are guiding lending decisions.
Compliance and Regulatory Reporting
Banks are subject to a range of regulatory requirements, and meeting them can be a complex and time-consuming process. AI can also streamline regulatory reporting, making it easier for banks to provide the necessary data in a timely and accurate manner. These include:
- Anti-Money Laundering (AML) regulations like KYC (know your customer), CTF (currency transaction report), and SAR (suspicious activity report). Surprisingly, almost 30% of banks still conduct KYC checks manually—a process AI can profoundly accelerate.
- AMLD IV/5MLDV II/6MLDVI includes reporting anomalies that might indicate terrorism financing or other criminal activities.
- FATCA requires foreign banks operating within US borders to disclose information about US citizens who hold accounts overseas.
- Banks must ensure their clients do not engage in business dealings with individuals or organizations on OFAC sanctions lists.
Banks can enlist the power of AI to stay on top of these requirements. AI-infused platforms can monitor customer activity at an aggregate level to detect patterns associated with money laundering schemes or other illegal activity—before it’s too late.
For example, AI can automate the collection of information from various systems such as ERP, CRM, or other sources by extracting the relevant data into one central repository for analysis. This leads to faster reporting and fewer errors than manual processes, helping personnel focus on what matters most: ensuring compliance with regulations across multiple jurisdictions.
Automate the data collection process
Digital onboarding for corporate clients can take up to 120 days—an unforgivable timeframe when targeting demographics hungry for instant gratification. What makes up the meat of this lengthy timeline? Information processing and data collection.
The data collection process involves various activities, like data entry and consolidation across multiple sources. Banks need to gather vital records like articles of incorporation, partnership agreements, and perform background checks on signatories and stakeholders.
Thanks to artificial intelligence, you can automate this process by collecting data faster and accurately, with less manual intervention. AI can pinpoint bottlenecks, like the all-to-common instance of asking a customer to resubmit an already processed document, to slash onboarding times dramatically.
Artificial intelligence can be the competitive advantage your bank needs—if you’re ready
Banks have a lot to gain by leveraging the power of AI. Right now, it’s a magic wand waved by the behemoths—nearly 75% of banks carrying over $100 billion in assets are using AI. But as the technology casts a wider and wider net, it’ll catch smaller institutions, who currently report 30% lower adoption than their ‘big bank’ counterparts.
There are still some obstacles to overcome before AI becomes mainstream in the financial sector. But it’s a strategy that can help incumbents further compete with fintechs that are already using the technology at a staggeringly higher rate than traditional banks. The immense powers of AI should give banks one thing: a strong kick to accelerate a much-needed digital transformation.
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