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With the fluctuation in the finance industry, the lending environment is rapidly changing for banks, credit unions, and other lending institutions. Historically, banks have been relying on demographic data, including age, education level, gender, race, and geographic location to segment customers. However, the rising younger workforce has rapidly changed this traditional dataset used by banks, pushing them into a new era of customer behavior.

Banks that have adapted to using customer behavior to determine the borrowing habits of their consumers have found new ways to segment customers based on their consumption habits, needs, and preferences. The changing preferences of the young generation, coupled with technological innovations, are paving the way for banks to adopt a strategic approach towards consumer segmentation. Significant drivers are facilitating the transformation of analyzing behavioral data, thus helping lending institutions understand their consumer habits and abilities. These drivers can be categorized into the following areas:

 

Machine Learning

The rapid adoption of machine learning models enables banks to use predictive analytics to detect patterns within big data. This modern approach gives banks the ability to look at their customer’s historical activities to identify which trends would be of most importance to them as compared to relying on demographic data to predict consumption patterns.

Big data has redefined the banking sector to the point where loan opportunities are identifiable through data analytics. Big data and analytics are helping banks locate and target the right people for financial products by analyzing signals based on life events, behavior, and passive information.

Behavior-based signals are some of the concrete actions that consumers take to indicate that they are ready to purchase new financial products. For instance, transactional data can send signals to the bank that there is a potential customer for a mortgage or a loan to purchase an asset. A consumer’s data builds a profile of predictive signals that banks can utilize to provide different financial products.

Digital Services

The explosion of digital services and products that consumers use daily creates an opportunity for banks to acquire data sources to get a better understanding of their customers’ consumption behaviors. This technique is not new in the US, where companies were reported to have spent $20.2 billion acquiring third-party audience data and activation solutions to support their marketing activities. The banking sector will follow a similar approach to segment customers in ways that yield deeper insights, leading to more effective customer service strategies.

Changing Customer Base

Traditionally, banks and other lending institutions succeeded in demographic segmentation due to the customer classification that existed before the eruption of technology. Generation Z and millennials joining the workforce have transformed the banking sector by being socially aware of the technological advancements, which they use for most of their daily functions, including shopping. It is estimated that 61 million of the millennials will join the workforce by 2022, which is an excellent opportunity for banks to take advantage of the tech-savvy customers to sell their products. Given that the younger lot has little patience for brands that do not demonstrate an understanding of their desires and needs, banks will need to do an in-depth analysis of their consumption patterns to appeal to these consumers based on refined and personalized marketing strategies.

How Banks Can Leverage Buyer Persona

1 – Get A Clear Picture Of The Customer

By understanding customer behavior based on their needs, tastes, and preferences, product managers can utilize this information to acquire a higher customer base for specific products. Understanding website behavior, product interest, social media engagement, and email preferences combined with offline activities such as phone calls can help banks leverage digital technology to create products that appeal to their customer base.

2 – Prioritize Personalization

Today’s consumers demand that brands treat them as individuals through personalized marketing. IT executives in financial institutions can help in classifying data based on customer behavior as a way of helping product managers to develop products for a specific consumer niche. Personalizing each product and consumer can be daunting; hence, with the help of Risk Management Executives, the process can be split into categories to be accomplished in bits.

3 – Create A Seamless Customer Journey

Once personalization is complete, the next step is to tie the customer experience together across channels and devices. Banks must leverage in-house transactional data to help in building a continuous journey with customers. The secret is for the entire banking team to keep learning and looking for new ways to apply analytics for fun and profit.

Looking Into The Future

For the future of financial institutions, data will be the greatest asset that these institutions can utilize to build products for their markets. Banks that can combine internal and external data sources to create value will find themselves well adapted to the digital market that will make up for future generations.

For financial institutions, knowing their customers’ actual financial situation is more critical now than ever. Contact our team at IFM to learn more about how we have emerged as the leader in large scale transactional/behavioral analysis for generating detailed knowledge to better understand your customer.

 

 

Among the more recent technologies, Artificial Intelligence (AI) could have the most significant impact on the financial services industry.

First discovered about 70 years ago, AI has transformed many industries already. From supply chain to retail and travel to education, AI has completely changed how work is done in these industries. The technology is predicted to have a similar impact on finance.

Common Challenges in Finance Marketing

Although financial service providers face many marketing challenges, most providers struggle with three fundamental problems, namely:

Commoditization

As the financial services market grows (thanks mainly to digitization), so does competition. Today the competition is so high that many financial services providers find themselves offering the same products.

Commoditization is a situation where the products and services offered by multiple market players are pretty much the same. When this happens, products from competing players can become interchangeable. As a result, consumers feel that they can move between service providers without losing value. Where there’s high commoditization, it’s very easy to lose customers no matter the quality of your branding.

Lack of Consumer Trust

For a long time now, financial service providers have complained about the lack of trust among clients. In a 2016 survey by the National Association of Retirement Plan Participants, for instance, over 90% of respondents said they did not have faith in their financial services providers.

Again, the chief contributor to the increased distrust is technology. After witnessing so many cyber-attacks and data breaches in the last few years, the majority of consumers feel that their data and money are not safe. The financial crisis of 2008 also seriously eroded the little trust consumers had in financial companies.

Automation

In most of the industries where technology is revolutionizing work, automation is one of the major highlights. In these industries, you’ll find many tasks being automated. You’ll also likely find robotic machines working alongside humans to complete tasks faster and with fewer mistakes.

Unfortunately, the finance industry has lagged in automation for several reasons, one of them being the delicate nature of the landscape. In finance, even one small mistake can have grave and far-reaching consequences. Compliance and regulations also make automation a big headache, often forcing providers to stick to traditional, familiar methods.

How AI Solves the Perennial Challenges

Although it’s impossible to solve all the challenges in finance completely, experts predict that Artificial Intelligence can ease many of the problems. Here’s how;

1 – Smarter Credit Decisions

More than three-quarters of consumers prefer to pay via credit and debit cards. Indeed, only 12% of today’s consumers still prefer to pay in cash. What this means is that the credit card segment is more important to financial institutions than ever.

Artificial intelligence provides for a faster, more accurate assessment of loan candidates – at a lower cost. Better still, AI-powered credit assessment solutions account for a wider variety of factors, leading to better-informed, data-backed decisions.

2 – Risk Management

In financial services markets, risk can be deadly if not given proper attention. Accurate predictions are critical to the protection of businesses.

AI will play a starring role in risk management going forward. Using superfast computers and AI solutions, providers can handle vast amounts of data in a short time. Cognitive computing (a branch of AI) helps to manage both structured and unstructured data, making it possible to catch potential issues early.

3 – Analysis of Customer Behavior

In the financial services industry, institutions find it difficult to develop the same deep relationships with customers that may exist with companies in other industries. Through transactional and behavioral analysis, artificial intelligence is empowering the finance industry with the ability to analyze money movement at scale so F.I’s can anticipate the future financial needs of an individual customer. Service providers such as IFM can work with banks to foster the development of A.I. solutions via IFM’s cutting edge technology that cleans and categorizes bank customer electronic financial transactions in near real-time. IFM’s data analytics service enables financial services firms to offer timely products and services to their clients and strengthens the relationship between a customer and the F.I. With IFM’s capabilities, a financial services firm can analyze client behavior and money movement – in near real-time – and can also trigger security mechanisms if patterns of transaction activity seem unusual.

4 – Personalized Banking

Personalization is the new way to market – even in finance. In multiple studies, consumers have made it clear that they are more likely to buy if the experience is personalized. In one study, for instance, 44% of respondents said they are likely to become repeat customers if a brand offers customized services.

AI currently offers some of the best solutions for personalizing the marketing of financial solutions based on consumer behavior and transactional analysis.

Bottom Line

Financial Services firms are faced with three common marketing challenges: Commoditization of products and services, lack of consumer trust, and the ability to automate solutions. Artificial Intelligence will help to solve these perennial challenges by providing an opportunity for smarter credit decisions, improved risk management, and a more in-depth analysis of customer behavior to provide a more personalized banking experience.

What strategy should your institution move forward with to solve these marketing challenges? Data Science experts believe that the key to developing A.I. solutions that guarantee better productivity and ROI rests on access to clean and categorized transaction data that can be utilized to power A.I. related solutions.

Reach out to our team at Insight Financial Marketing today to learn how IFM’s Intelligentsia™ service could have a positive impact on your institution’s ability to market the financial solutions of the future.