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How can financial institutions harness data analytics to boost business during COVID-19 while reducing risk?

When the U.S. Treasury
Department launched its first $349 billion Payment Protection Program (PPP) in April
to help small businesses shore up payrolls during COVID-19,financial
institutions were swamped with demand. The confusing process that ensued to
secure the loans/grantsgenerated such widespread frustration that one third of
small businesses said they would likely switch banks (Greenwich Associates).

While there is a
unique opportunity for financial institutions to gain market share in this
environment,risks abound. Barlow Research Associates predict that 15-35 percent
of small businesses may fail in the aftermath of the pandemic. How do you target
marketing efforts when not all new business may be good business?Clearly, it’s
not enough for banks and credit unions to simply ramp up marketing efforts.

Seizing the

healthy prospects for win-win, profitable business relationships is acomplex
and large-scale challenge, but it’s a crucial step for financial institutions
that want to seize this unique window without exposing themselves to excessive risk.
The solution lies in harnessing data analytics to identify strong business prospects
while weeding out others. To accomplish this, multiple measures of a business’s
health – including geographic location, industry sector andfinancial strength–
need to be analyzed together to score a company’s value and/or risk. With this
kind of evaluation, bankers can make informed decisions for smarter,more targeted
marketing efforts.

This prospecting
strategy can also be turned around and used internally to identify pockets of
existing risk, providing new tools to internal risk management teams. Banks and
credit unions need to analyze their current client portfolios and look for
potential problem areas before they erupt.

To fully realize
the current prospecting opportunities, banks and credit unions will also need
to offerrobust digital capabilitiesto attract and close business. This was
confirmed by theGreenwich study, which found better online service is the top
consideration for businesses when switching financial partners.

interested in harnessing technology to drive theirclient acquisition strategy
while proactively managing risk should incorporate the following elements.

Begin with a multi-sourced
data lake

An effective data
lake is the starting point for an analytics-drivenmarketing approach. It’s comprised
of a huge collection of information with insights aggregated from multiple
general and specialty data providers. Verifying data across sources is vital to
create a comprehensive, 360-degree view of specific businesses.

Typically, data
is fragmented and error-prone,requiring specialized skills to decipher good
sources and pieces of information,and then separate them from those that are
not. Once this is accomplished, you can move forward with accurate audience
data and develop hierarchies using algorithms to prioritize and combine
records. From this, powerful signals emerge to determine which businesses you
want to convert into customers.

Get a look-ahead
with a COVID-19 Index

To address a predicted 250 percent increase in business failures due to
the ongoing impact of the pandemic, it is helpful to create an index that
provides a single risk score based on a multitude of factors. Deluxe, for
example, developed a tool called the COVID Index that uses a specialized data
lake to assess a business’s likelihood to persevere. Financial institutions can then use a
business’s index score to focus marketing efforts on healthy targets, as well
as pull back on promotions to severely distressed businesses in their own

This evaluation tool
determines a business’s viability by combing three layers of data. The first
encompasses business-specific data such as business-level trade credit
assessment, evaluation of accounts in collection, liens, days beyond terms,
deteriorating payment history, credit shopping behavior and signsof distress
pre-pandemic.Next, industry-specific information relative to COVID-19’s impact is
overlaid (e.g., restaurants, retail and hospitality are heavily impacted
sectors). Finally, geographicdata is factored in relative to the pandemic’s effects.

Interpret data
with advanced AI-powered analytics

It’s important to
note that a data lake by itself is not actionable until you understand and
interpret it. Overlaying sophisticated analytics powered by AI enables you to
advance the process of qualifying targets by answering these crucial questions:

  • Financial health: Is a particular business healthy now, and
    will it be around in the future?
  • Size of wallet: Is it worth the time and cost to acquire this
    relationship and will it be a win-win for both the small business client
    and the financial institution?
  • Current relationship status: Would this business consider
    switching financial service providers?

In addition, AI
also providesvaluable product-level revenue projections and propensities for
every marketable small business. Advanced modelshave the added value of
continuously updating the data lake, which enables changes in data to train the
analytics to be increasingly accurate.

Incorporate multi-channel

Another critical
element is multi-channel expertise to factor in a small business owner’s decision-making
journey, which may encompass online, offline, digital and in person channels.
If a business is searching digitally for a new financial services provider, for
example, banks need to inject themselves into the conversation – including traditional
channels like direct mail and email. Being present across multiple channels
allows cumulative touchpoints that add credibility and attract potential
clients. This approach helps fill the communication gap since COVID’s
disruption has made face-to-face discussions less feasible. 

Financial institutions
also need to thinkof business owners as consumers.This is an important reality
as professional and personal lives increasingly overlap and merge, a trend
accelerated by COVID-19. The Amazons and Apples of the world have elevatedconsumers’expectations
of the sales experience, and financial institutions must keep up – especially
since both Amazon and Apple are moving further into financial services.

Measure results
with deep analysis

Many marketing
programs will fall short if the analysis phase does not accurately measure the
success of the campaign by identifying which channels are most effective at
generating new qualified leads. With attribution channel controls, you can determine
the incremental benefit versus the cost for each channel. For example, what is
the added value if you layerdigital touchpoints on top of direct mail, or have
relationship managers make phone calls to a targeted list of businesses?

The analysis
provides not only the number of new relationships acquired, but the
composition, account mix, balances and,most importantly, the return on
investment and profitability of business generated. With this information,
banks can fine tune the marketing program, matching it with the most effective
channels for particular businesses.

Make each
successive campaign “smarter” with sequential optimization

To summarize, we
know the size of adata lake enables greater training of the models and
algorithms, and the attribution element enables a financial institutionto create
greater learning and an enhanced campaign strategy.But how do you build on this
to make each successive campaign better? The answer to making smarter decisions
is to leverage anAI platform to assess how well the campaigned fared and feed
all measurement and attribution results back into the analytics software.This is
critical because, as the world changes, so do businesses and banks. By adjusting
and updating your targeting approach, a business can continue improving its
tool to ensure it reflects the real world.

Using technology
to create sophisticated campaigns with the above attributes enables financial
institutions to fine-tune their marketing efforts and attractquality business
relationships. What follows is winning service for clients along with positive
returns for banks and credit unions. During normal times, this approach may be
considered a “nice-to-have,” but in the wake of a pandemic, it could determine
the post-pandemic’s winners and losers.

Garry Capers is president of Cloud Solutions at Deluxe Corporation and a member of the Executive Leadership team.

Prior to Deluxe, Garry held executive leadership roles with ADP and Equifax. At ADP, he led a business providing comprehensive outsourcing services that drove revenue, profitability and client satisfaction. A proven leader, Capers has led efforts for global technology companies and top-tier global management consultancies, transforming and accelerating revenue growth. While at Equifax, he oversaw B2B marketing units that focused on marketing data services for corporations, small businesses and consumers. His efforts led to significant revenue growth and margin expansion.

Garry holds a Bachelor of Arts in Business Administration from Morehouse College and a Master of Business Administration in Marketing from The Wharton School at the University of Pennsylvania.

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