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Financial institutions make better decisions with the power of automation

The financial institutions winning the customer service game earn more trust and ultimately make more money. But how? It all comes down to information. Better information means better customer management strategies. Automation unlocks the superior information that financial institutions need to win customers and keep them happy.

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The saying goes, “Money is power.” For financial institutions, this is certainly true. However, there’s another entity of equal or greater importance: Information. 

In general, the scope of work for banks, lenders, and financial institutions doesn’t differ wildly from one organization to the next. From receiving deposits to making loans to managing wealth, the work is similar across the industry. 

So, what makes someone bank with one organization over another? The main differentiator is customer service. Financial institutions with standout customer experience gain more trust and ultimately, win more business. 

And how do the best financial institutions build customer trust? Again, with information — information that’s current, informative, and deadly-accurate. Through automation, banks and lenders can make split-second decisions that serve their clients’ needs as well as their own. Automation is the secret weapon in a financial institution’s arsenal.

What does automation look like for financial institutions? 

With the onset of virtual banking and evolving technology, the financial sector faces stiff competition in a saturated market. The pressure is on to optimize personnel, outwit competitors, increase efficiency, and delight customers.  

Customer experience differentiators 

Automation may be the differentiator that sends one institution into the stratosphere of success, leaving competitors behind. Automation for financial institutions has the following impacts on customers: 

  • Risk mitigation
  • Reduced costs
  • Reduced human error 
  • Faster service 
  • Better customer intelligence 
  1. Risk mitigation — A large part of the lending process entails background checks and regulatory compliance. Automation helps banks generate faster audit trails and more accurate risk assessments. Not only are you getting back to customers faster regarding their credit and lending inquiries. You’re reducing their business risk as well as your own. 
  2. Reduced costs — Automation reduces the spend on manual tasks and re-allocates that spend toward the customer experience. From automated report generation to background checks and increased personnel, the entire customer experience grows more personalized and friendly with better budget allocation. 
  3. Reduced human error — “More data, less entry.” That’s the goal for financial institutions looking to avoid the human errors associated with manual data entry. Manual data entry is time-consuming and prone to error. With automation, financial institutions can devote numerous employee hours toward other points of focus, like providing individualized customer attention. 
  4. Faster service — Better information means faster answers and quicker customer processing. Maybe customers are serviced without ever stepping foot inside the bank or lending office. Maybe, automation has helped queues dwindle, while speeding up credit assessment turnaround times. Plus, better information frees up the work week for financial institution employees. According to Forbes, 53% of employees save around two work hours a day through automation, and 78% of business leaders believe automation frees up three work hours a day. 
  5. Better customer intelligence — Highly accurate customer intelligence informs service. Automation can kick off a broader scope of customer data collection. Sharper insights follow. For example, maybe your customers want to move as much of their interaction online as possible. Perhaps they want a telephone line manned by a customer service representative, available 24 hours a day. Through automation, you can collect survey results and insights that aren’t possible through manual means. Then, you can reform your customer service approach accordingly.

Automation use cases in finance

Automation is happening on a large scale across a wide swathe of business projects, but in the financial sector, there are numerous well-defined use cases with proven outcomes. Intelligent Document Processing (IDP) — the process of capturing, extracting, and processing data from a variety of documentation — is an important piece of the automation puzzle. Here are some important financial sector use cases where automation and IDP play a significant role. In all of these cases, new efficiencies translate directly into a better experience for the end user: The customer. 

  1. Customer onboarding — Until recently, consumer lending took a “better safe than sorry” approach to giving lines of credit, taking risks, and analyzing customer information. At many stages of the process, manual verification has been required. With automation and machine-learning, there’s no need to hedge or take weeks to pass manual check points. IDP makes the process faster through things like optical character recognition between compliance documents and customer-supplied information. The onboarding process becomes faster and more accurate.
  2. Lending — From loan processing to disbursement and management, automation can positively impact several facets of the lending process. Documents for loan appraisal come from many disparate places: Emails, PDFs, or hand-written documents, to name a few. IDP capabilities can extract important data and automate a range of manual tasks. With better loan initiations, document analysis, and quality control, the entire lending process is streamlined from start to finish. 
  3. Account opening and closing — Through automation, opening and closing accounts becomes quicker and more efficient. For example, automation can eliminate data transcription errors and inconsistencies between documents. When it comes to account closures, automation can update system data, check for document availability in bank records, and communicate with branch managers and other stakeholders. 
  4. Know Your Customer (KYC) / Anti-Money Laundering (AML) — KYC and AML compliance checks are often highly manual. They involve delving into an individual or company’s background, searching for anything suspicious, and collecting data from a variety of sources. While some of this process is devoted to analysis, a report by Booz Allen Hamilton notes that AML analysts typically spend only 10% of their time on analysis, and the other 90% on data collection and data entry and organization. Repetitive tasks and rule-based data entry can be easily automated through IDP, catalyzing a drastic reduction in the turnaround time of a KYC/AML report. 
  5. Report and statement generation — A great deal of reporting goes into both banking and lending. There are fraud detection reports, suspicious activity reports, profit and loss charts, routine bank statement issuances, and a variety of compliance reports. The structure of the financial sector is held up based on the assumption that regular, accurate reporting occurs. Traditionally, these reports were completed by financial officers manually filling in the requisite forms. Now, with IDP and automation, accurate data is extracted from lengthy collections of documents. 

Automation in action: Johnstone Brokerage Services combats risk and boosts client service through machine learning

Johnstone Brokerage Services (JBS) provides financial guidance to clients. That means staying one step ahead of financial risk-taking on behalf of their clients. 

The organization wanted to identify potential risks and blockers in order to anticipate events that may impact customer portfolios. They needed the right data to do so, but they quickly realized that poring over numerous reports, charts, and analyses would be time-consuming. Plus, given the manual and piecemeal nature of that work, they may not be able to see the complete picture or draw the right conclusions. 

JBS receives quarterly statements from insurance and annuity providers. Using Impira, a machine-learning solution, they started processing and organizing all of these quarterly reports to make quick sense of the numbers. They could then translate those numbers into action, comparing quarter-over-quarter values to analyze things like where death benefits exceed the current value by a predetermined dollar amount, for example. Processing this data took JBS just a few minutes, versus the manual hours it would have taken without Impira. 

JBS’s most important asset is its clients. With Impira, JBS identified specific, actionable measures for clients. They took a more informed advisory approach, using better data and faster turnarounds. At the end of the day, this automation translated directly into a better customer experience for JBS clients.

Implementing automation

For banking and financial institutions, lengthy manual processes have always hampered overall productivity and customer satisfaction. 

To implement automation that drastically improves customer satisfaction, we’ve identified these steps:

  1. Conduct an assessment of the operational and customer-facing issues that can be aided with automation. Create your list of where it’s feasible to introduce automation, and what the impact might be. 
  2. Calculate the investment versus the potential gains to make the business case for automation. That business case should consider dollars and cents, but also metrics like time, efficiency, and resource allocation. Where will you see short-term and long-term cost savings? 
  3. Identify the stakeholders and timelines associated with automation implementation. Who is involved, who signs off, and who should be informed? Plot how long it will take these stakeholders to move through the implementation phase. 
  4. Choose the right tools and automation partners. Your organization will have compliance requirements, vendor guidelines, and preferred tools and partners. Educated stakeholders on the comprehensive suite of tools and partners needed for planning, execution, support, and follow-up. 

The best customer experience comes from personalized, individualized attention. The right automations can clear up confusion, provide informative communication, and meet customers exactly where they are. 

That key differentiator — information — is the key to unlocking that standout customer experience, but not all information is equal. The best information comes from accurate data at scale. With the right information, even a large institution can provide white-glove, boutique customer support. It just takes a strategic approach to automation to get there. 


Start winning today.