A Once-Conservative Industry is Getting a High-Tech Upgrade
By leveraging artificial intelligence, a conservative industry is blazing the trail with AI to nurture stronger customer relationships.
Financial services has long been thought of as a more traditional industry — an industry that’s not necessarily diving headfirst into the most cutting-edge technology. Until now.
Now, banks, lenders, and other financial services businesses have seemingly discovered an ideal partner to power their processes — and their success. Because, now, retail banks, lenders, insurance companies, and investment firms are all embracing artificial intelligence (AI) — and it’s paying off.
According to the 2019 Adobe Digital Trends Survey, nearly 75% of financial services respondents say they are either already using AI or have plans to use it in the next 12 months. The driver behind this quick migration is AI’s promise of increased revenue and profits, improved customer experience, and product innovation. Financial services brands are also using AI to tackle a host of diverse challenges in order to gain a competitive advantage. Below, we take a look at a few.
1. Simulating person-to-person relationships at scale
Financial services firms have always been relationship businesses, growing through face-to-face interactions with customers. Now, as more financial business moves online, how can these organizations continue to create relevant and personalized customer experiences?
We may be prone to think that banks and other financial institutions, which are highly regulated and appear stodgy and “old school,” aren’t on the cutting edge of tech. Not true. The successful organizations are connecting with customers online via AI.
One example: the use of machine-learning-guided chatbots for bank customers who prefer to interact in online text-based communications. Still in their relative infancy, yes, yet chatbots are expected to save banks more than $8 billion by 2022.
Beyond chatbots, the use of AI-powered personalization, targeting, and recommendations is also increasing rapidly among financial services companies. For example, one bank is using AI to determine the order of products presented to a web visitor, based on their profile and what they researched on the site in the past. This personalized approach increased the bank’s click-through rates by a whopping 70% on average.
2. Accelerating and improving financial decisions
A staggering amount of data is generated in the financial services industry. It’s no surprise, then, that our aforementioned 2019 Digital Trends Survey found data analysis is the most common application of AI for financial services companies.
When it is mined properly, data can help financial organizations make faster, more accurate, and less resource-intensive assessments that produce more reliable decisions. For example, insurers are using artificial intelligence to analyze geography, weather patterns, and even satellite data to determine coverage and premiums, and who are more likely to be impacted by tornadoes or hurricanes and may require significant payouts.
In addition to risk-mitigation benefits, financial traders, specifically, can use AI to make faster processing decisions and transactions. Already, 80% or more of daily stock moves are machine-led.
3. Preventing fraud and loss
By drawing on machine-learning algorithms, financial services companies can sift through data surrounding customers’ behaviors, location, and buying habits to spot — and even predict — fraudulent activity. Banks can use similar tools and triggers to prevent money laundering.
Similarly, stock brokers are using AI to anticipate upward or downward movements in stock prices, and then trade accordingly, to minimize losses and maximize gains for their customers. And, portfolio managers can use AI to scour the web and other critical resources for content and social sentiment to inform what they buy and sell for their actively managed funds. It’s a holistic approach that capitalizes on real-time trends, historical patterns, and the power of AI to connect the dots and take immediate, informed action.
4. Meeting regulatory and compliance standards
Regulatory requirements are another defining force in the world of financial services companies. Fair Lending and other laws and regulations demand that institutions give fair access to consumers regardless of race, gender, or age. While many companies have processes in place to stay compliant with these regulations, AI is providing both support and counterbalance to these regulations.
Using AI can ensure that even more bias is removed from the process — and flag instances of bias as they happen — while taking into account other fiduciary considerations. This makes AI an ideal tool for protecting both the consumer and the company with equal vigilance.
5. Cutting costs
More than half of financial services professionals say their top motivation for investing in AI is to increase efficiency and productivity. With its unparalleled speed, scalability, and ability to reduce risk, AI is enabling financial institutions to operate and serve their customers with less waste and greater effectiveness — and stay profitable in an unforgiving marketplace.
Wading into the AI waters
Right out of the gate, companies need data that’s reliable, clean, and universally accepted by the organization.
Once a company has a solid supply of reliable, trustworthy data, they can begin experimentation with an AI-powered analytics solution. Companies should start with a series of optimization and personalization exercises to test its capabilities and get a sense of what works or does not work. Then, they can start to understand what can be automated or what they could potentially level up with a machine.
From there, the possibilities are practically endless. Coming in the near future are things like hyper-personalization in content, with page layouts, copy, and other design elements assembled in real time — and according to an individual’s customer profile, past behavior, and predicted behaviors.
This is the real AI end game for financial services firms — an efficient, real-time, unbiased, hyper-personalized customer experience that builds loyal relationships with customers.
Learn more about creating winning customer experiences here.