How analytics can drive a better onboarding process
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There is no option B - How actionable analytics can drive a better onboarding process

Sudha Bhat

Customer Analytics Leader



As the saying goes, “first impressions are the best impressions." A bad first impression can undermine the perception of a brand, before a relationship has even been formed. At the same time, all banks are scrapping to win over consumers and retain them. Getting that first impression right becomes critical in an increasingly digital world, where consumers are in control – with access to unparalleled sources of information

Banks have to work hard to stay ahead of the race. According to a Forrester report, one third of customers say all banks are basically the same. So it shouldn't come as a surprise that banks are preoccupied with devising innovative ways to woo new customers and keep them happy.

Onboarding is the first step in a customer's lifecycle with a bank. It can also be an onerous task, given the number of actions required of customers (and staff). A poor onboarding experience only creates a pool of dissatisfied and inactive customers. The probability of customer churn in such a scenario is high. A recent study indicated that 43% of customers with low satisfaction scores during an account opening process were highly likely to switch banks. As the market becomes more competitive, there is no room for such failures. In order to stand out as an exceptional bank, a quick, easy, digitally enabled onboarding process is the key. So what can financial institutions do to overcome this challenge? I believe the key to success is to innovate with digital analytics interventions.

Most banks are investing heavily in technology to ensure minimal friction between channels so that customers' journeys will be smooth. However, to succeed technology investments alone will not suffice. An in depth understanding of people, processes and technology is needed.

So how can analytics help banks achieve a great onboarding experience?

Data analytics initiatives need to focus on the customer. It's not about creating data structures and data lakes. It's about being able to visualize relevant data in an actionable form, based on need. Most banks are heavily dependent on last generation systems and to maneuver through this kind of project can be a huge task.

However, analytics is a must. Constantly changing customer preferences are a challenge to identify and the astute use of data to drive personalization is important. Insights can be obtained using both offline and online data along underpinned by machine learning to continuously update the segments that drive persona creation. This can transform a bank's onboarding from a reactive to a proactive, consumer-led function. Machine learning algorithms can also drive tailored decision making for authentication, verification and auto triggers for underwriting exceptions or customer service support. Utilizing constantly updated, relevant data to tailor products and services helps banks to improve end customer experience.

Smart information capturing and processing techniques (natural language processing / natural language generation) can enable banks to scan through unstructured documents submitted during onboarding and derive actionable insights and strategies. The real time identification and analysis of events like exception handling is possible with voice, text or chat analytics. These insights can be used to reduce referrals. All the data gathered can be formed into an internal repository which acts as the power house for the predictive analytics engine. One can think of this as a warehouse consisting of essential details on customer personas, preferences, demographic details etc. The predictive engine has the power to create personalized notifications and offerings during onboarding. This is the critical heart of a personalized onboarding experience.

Delivering an integrated customer experience is all about Who, What, When and How (right micro segment, preferred product and preferred channel).

Listening to the customer is crucial. Don't let your analytics be driven only by the quantitative data but also leverage qualitative views. For example, utilize voice of customer listening initiatives through social media/web/interaction information.

It is critical to get all of this right as the quality of a customer's onboarding experience is going to determine the future relationship. There is no room for an option B for quality onboarding. To fail here is to risk losing customers in an increasingly competitive market.