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The banking industry faces innovative retail banking trends in 2020 with powerful forces reshaping the sector and creating an imperative for change. Banks and other financial institutions must choose what course of action to take – to either lead the change, follow trends, or manage for the present.

Whatever their strategy of choice is, it’s critical for banks to develop new, innovative solutions by taking advantage of big data, transactional and behavioral analytics, digital technologies, and novel delivery platforms.

From making transactions move faster and smoother to the changing and evolving role of retail banks, it’s not entirely clear what the trends discussed below will mean for the sector and the financial industry as a whole. However, the consensus is that the retail banking trends for 2020 discussed below will favor consumers.

6 Retail Banking Trends for 2020

1 – The Expansion of Open Banking

Many view open banking as a European issue and a threat to traditional business practices – the latter is correct. It refers to any initiatives by banks to open their APIs to third parties, giving them access to the bank’s data and functionality. You can use the term open banking interchangeably with API banking, open APIs, banking-as-a-platform, banking-as-a-service, or ecosystem banking.

The concept for open banking encompasses the need for banks and other lending institutions to respond to consumer pressure for painless and straightforward financial experiences. For instance, to buy homes, transfer and receive payments, or manage their financial lives. Fintechs and other big tech companies have already started leveraging the API banking ecosystem to offer financial services.

2 – Real-Time Financial Products

Banks and consumers alike are driving demand for services and products that they can interact with in real-time. This development will see real-time payments become the expected banking norm in 2020. What’s more, the conversation is sure to shift from how banks can set up for a real-time experience to what they can do to become more competitive and attract clients by leveraging real-time payments.

APIs will play a significant role in real-time growth since the fintech community requires them to interact with the banking services that their customers need. Therefore, retail banking trends for 2020 will focus on setting up new, innovative real-time payment services that attract fintech companies and consumers.

3 – Commitment To Digital Delivery

2020 is already shaping up as the year of enhanced digital banking consumer experiences. The industry is ripe for change thanks to the development of new, incredible technology both within and outside the sector that supports digitalization.

For those still mostly offering traditional banking services, they will shift their primary focus to the integration of new technologies and the enhancement of digital offerings with an emphasis on more value and personalized client experiences.

4 – Always-On “Invisible” Banking

As the business world enters the post-digital age, financial institutions will seamlessly integrate their financial services into the daily lives of consumers. This trend has taken the moniker “invisible banking.” An example of an invisible banking transaction is direct deposits.

Technology has created what experts refer to as an “always-on” world where business opportunities appear and evaporate quickly. A time will come when it will not be enough to have the right products and services, but banks must also recognize the exact moment when consumers need them.

5 – Intelligent Assistants and Voice Banking

Thanks to the rapid consumer adoption of voice and digital assistants, it’s now imperative for banks and other lending institutions to seriously consider the implementation of these services. Statistics support this assertion with a 78% growth of voice assistants and smart speakers users in the U.S.

Already, a handful of large banks have invested in digital assistants, including Capital One, Barclays, BofA, USAA, and U.S. Bank. Some smaller institutions like Mercantile Bank of Michigan have also followed suit.

6 – AI-Driven Predictive Banking

The ability to observe, analyze, interpret, and catalog the actions of your bank customers (while respecting their privacy) allows you to design and deliver rich, individualized experiences that will help build customer loyalty during the post-digital age.

Therefore, the banking industry is leaning towards the consolidation of all internal and external data to build predictive profiles of their customers in real-time.

Banks with a competitive edge in the market will go a step further to help their customers optimize their spending, give them preferred access to excellent deals, and nudge their behaviors in a way that creates a better long-term financial health.

One AI challenge that many institutions face is finding a balance between privacy and proactive insight, which is where transactional and behavioral analytics apply.

The Bottom Line

As the financial services industry undergoes rapid change and retail banking trends in 2020, institutions must invest in transactional and behavioral analysis to remain competitive, increase customer experience, and meet strategic goals.

Since 2002, IFM has been providing clients with cutting edge technological solutions, near real-time insights, predictive machine learning-based intelligence, and behavioral-based triggers. IFM’s proprietary processes is what allows them to provide banks with a data standardization solution and near real-time behavioral insight.

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.

 

 

Data trails have become an integral part of the modern consumer’s lifestyle. Every day, people leave traces of data on the internet, through bill payments, and even when making phone calls. 90% of the data present in the world today was produced in the last two years. For attentive lenders, these data trails can be a great lead generation tool.

Behind these sets of data sits information that can guide lenders into establishing the risk profiles of potential borrowers as well as unearth new business opportunities. The science lies in identifying the type of data on which to concentrate. The art is determining the kind of insights for which to look. Luckily, with the help of big data analytics tools, machine learning, and the right resources, it can be easy to use such data to revolutionize lead generation and customer retention in the mortgage industry.

Here is how big data can revolutionize lead generation in the mortgage industry:

 

Building the Right First Impression

The customer journey that lenders take potential customers through will have a significant impact on their final decision. Nowadays, digital properties have been playing a pivotal role when it comes to interacting with potential customers, as well as presenting the nitty-gritty details of loan offerings to them. In many cases, the customer’s experience with the company might start with a personalized marketing campaign that drives a prospect to a lender’s website.

If the experience raises some red flags or seems tedious to them, then the chances are that they will look for another business with which to work. For instance, asking customers several random questions only to offer them generic loans might put off some customers. With big data, businesses can analyze both internal and third-party data to come up with a consumer journey that creates the right impression off the bat. The data collected during this experience can also translate into how lenders handle customers throughout the lifetime of their loans, increasing customer retention rates.

Better Assessments

It is quite easy for people with thin credit files to be judged using generic credit scores. In many cases, these people could easily manage to borrow and pay back more than what lenders offer them. Big data can provide insights into the risk profiles of customers who haven’t tapped into enough credit throughout their life. For instance, a good number of millennials might not use credit cards, take out car loans, or even work as salaried employees. This generational behavior makes it unfair to judge such mortgage leads under the generic mortgage models.

However, these people do pay phone bills, own bank accounts, and use a mobile payment app. All of these pieces of data can be significant indicators of their risk profile. This information can produce a more thorough profile that can also apply to underserved communities that lack definitive credit histories.

Detecting Fraud

The mortgage industry is among the most fraud-targeted sectors of the economy. While lenders want to limit fraud as much as possible, they neither want to lose legitimate business nor run afoul with regulators for making aggressive rejections to loan applicants. Luckily, big data analytics can offer the balance for which lenders are looking.

Ideally, big data helps lenders, third-party data suppliers, and FinTech vendors to move past conventional fraud detection methods. These methods involved manual fraud detection processes and siloed data. Proper analysis of big data can limit the number of false positives in fraud detection and identify questionable transactions as soon as they are made. Artificial intelligence can help score the risk profiles of the different transactions against a number of variables. Although these analytics can reduce the cost of relying on conventional detections strategies, they require a complete change in how managers approach risk management.

Increasing Efficiency

Other than controlling costs and improving profit margins, the efficiency at which lenders can handle a loan throughout its entire life will have a significant role to play in how they generate mortgage leads and improve their customer retention rates. Data analytics can have a vital role to play in improving the entire loan application process, enhancing the customer onboarding process, and speeding up loan underwriting. With big data analytics and the consent of the customer, lenders can gain access to consumer data from third-party data providers. These data sources can include banks, employers, and credit bureaus- allowing them to form a better picture of the financials of their mortgage leads.

Machine learning can also be pivotal in preventing last-minute delays in the loan application process by flagging suspicious data points. For instance, if the suspicious activity is that the borrower had made large withdrawals or deposits into their bank account, the system will pick up on this and allow the underwriter or processor to request clarification. The customer can then send their feedback through the analytics application, making it easy to analyze their inherent credit risk.

With this better organized, more comprehensive, and easily searchable data, lenders can rely on the data points to provide high-quality customer credit files. Other than making the underwriting process smooth, these files can provide insights throughout the lifetime of the loan, offering ideas that can improve the experience of a borrower. Lenders can identify ways to improve their loan offerings, respond to customer feedback, and help customers out of tricky situations, all of which can improve their chances of them turning into repeat customers.

Big Data to Generate Mortgage Leads

Big data improves the scope and quality of insights drawn from borrowers’ data. With more emphasis on the analysis of data, lenders can both improve the experience they offer current customers and extend their services beyond the typical client base through the generation of quality mortgage leads. The onus is upon lenders to embrace big data analytics to be part of this remarkable revolution.

Reach out to our team at Insight Financial Marketing today to learn how your business can get started using big data to generate mortgage leads in a way that optimizes the engagement with each customer.

 

 

A new age of technology exists, and things are moving very fast. Because of this, the banking sector has begun to utilize more of the modern technological advancements. Many of these advancements are leading banks to use data and artificial intelligence (AI) for higher levels of personalization and consumer fulfillment. These trends are only going to grow. Here is a look at the role new technology plays in modern banking.

Keeping Up With The Disrupters

While many in the banking sector were trying to maintain the status quo, disrupters turned up with digital banking and financial solutions utilizing modern banking tech and the mobile devices. These developments forced all banks to reevaluate and start to implement changes to how they service their customers. Now, most banks have applications that work fast and provide services people want their banks to provide.

Mobile technology is playing a significant role for banks, and fine tuning those digital offerings is something into which these banking institutions have put a lot of effort. Artificial intelligence (AI), big data, and predictive analytics are becoming the norm in the banking industry for these reasons.

Bringing Core Services Online

Along with the mobile push comes the push to put core banking services online in general. Banking portals of the past contained heavy limits and often did little to improve a customer’s experience.

Forward-thinking banks have started to utilize modern techniques to attract customers to their financial solutions, and allow customers to make banking decisions quickly and without hassle. Responsive design and a focus on turning technology towards customer service have created vast improvements for the banking industry.

Once again, a lot of this comes from investments in analyzing data and AI. This is especially true of online banking services that can help someone in real-time. By anticipating their questions, banks can provide automated and personalized solutions. Banking tech is assisting financial institutions to do more while saving money in the process.

Creating and Fostering Greater Levels of Personalization

People want to feel like their financial institutions know them, care about them, and are looking out for them. People interact with their banks and bank products all the time and with greater frequency. Each of these interactions is an opportunity for a bank to learn more about their customer.

For example, consider someone who regularly loads funds to their favorite coffee store mobile app every week for a year, from their bank account.  This transaction trend reveals one particular behavioral characteristic about the customer that, along with other data points, present your financial institution with information about the customer’s preferences and lifestyle.  Over time, as new transactions and transaction types are analyzed, and the historical amount of data available to analyze increases, new opportunities to cater to specific customer needs will be identified.

In the near future, a financial institution will be able to anticipate a customer’s needs and gain insight into what the bank can further do to retain that person and other people like them.  Advanced data analytic solutions make it easier for banks to identify trends and make individual suggestions for how to engage customers, that work on a more personal level.

AI, along with advanced data analytic capabilities, help banks learn more about their customers and how to take care of them on a personal level.  The fact that data analysis can create a more human experience for customers is one of those areas in which banks are finding a lot of value in, and is one area that will also create a healthy return on investment into the future.

Data Science and data analytics plays a crucial role for banks at every level and in every department. In this way, technology serves to unify many of the disparate banking departments so the bank can create a better, more secure, and personal experience for each of its customers. Financial Institutions who aren’t doing this, or planning to do this, will find themselves left behind. Reach out to our team at Insight Financial Marketing today to learn how your business can get started with the latest innovative solutions that will increase your bank’s ability to engage each customer with a more personalized experience.