What types of decisions are best suited for automated decision-making in BFSI?

IPL is around the corner and if you love watching cricket then you would know the importance of ‘decisions’ made in that game. It can be a boon or a bane for the team, right?

Likewise, decision making in banks is a critical task. Deciding on which loan to approve, Which marketing technique to adapt etc can be path-breaking in their own ways. Non-Performing Assets (like bad loans) in the economy stands at Rs 10.35 lakh crore. About 85% of these NPAs are from loans and advances of public sector banks. 

Humans can go wrong in their judgment to take various critical decisions as our minds are only designed to think in a bordered perspective whereas machines are designed to think and co-relate things that are beyond our scope to decipher.

Automating decisions based on rules and logic is the best way ahead. Automation of business processes can save time and money, drive higher responsiveness, preclude human errors, and lower cost.

It makes customers happy who no longer have to stand in line for an executive to assist them with transactions. Decision automation is just like automating any other business process.

Modern technologies help businesses generate decisions that are consistent and made thousands of times over with the same type of data, such as pricing, loan decisions, fraud detection, dynamic forecasting, risk review, and so on.

However, not every business process is suited to automation, so it is important for organizations, managers, and knowledge workers to determine which processes are a good fit for automation and which ones should be handled by people. How companies select which business process to automate will shape the future performance of their organizations.

For example, companies need to automate a business process that is time-and-resource intensive operationally, which is subject to human error and that can be accelerated with an automated process. Automating business processes should speed products to market, reduce operating costs, and improve revenue collection.

Areas where decision automation can produce great results in BFSI

Decisions that are consistent and must be made frequently are the best fit for automation, provided your data is clean and flowing well between system. For example, most banking services involve decisions and thousands of repetitive decisions need to be made by the organizations each day. For personal loan approval, bankers check the age of an applicant, stable employment, and credit history to determine his eligibility. This type of decision-making can be automated.

Here are the number of business areas where industries including banking, insurance, travel and transportation are using automated decision-making applications effectively to generate useful solutions.

Lending Decisions

“Loan decisioning is an art with human intervention, and it relies on the skills of approving officers,” says LeCorgne. “With an appropriate balance of technology and human oversight of both the decisioning process and final approval, automated technology-based scoring and decisioning tools can provide important benefits to an organization.”

Neill LeCorgne, Sageworks vice president of banking and a former bank president.

Traditionally banks would involve in taking decisions manually. However, this has drastically changed after the emergence of automation.

An automated scoring system can calculate and score quantitative and qualitative risk factors, weighting each factor as needed and then aggregating all of the scores into a final score. Underwriting loans quickly improves the efficiency and TAT for banks and financial institutions.

Automating loan decisions provides flexibility to ramp up or pull back on loan decisions as warranted by business strategy and the business environment

Fraud detection

Fraud has become a troublesome intruder for banks. Credit card companies and government agencies, like the Internal Revenue Service and the U.S. Securities and Exchange Commission, implement automated screening to identify fraud. The fraud detection software automatically alarms the clerk at the desk whenever a potentially suspicious fraud pattern emerges. So that he can immediately lock down the card and call the cardholder.

Segmentation decisions

Banks can improve productivity by employing automated filters for sorting cases or transactions. For example, in response to backlogs, insurance companies are using decision automation to handle the insurance claims of regular customers and the most straightforward insurance claims even with mission information. By adopting this approach, insurers are handling up to 10% more claims without human intervention.  

Corporate and regulatory compliances

Many routine credit decisions, such as assessing whether someone qualifies for a mortgage loan or credit card, can be time-consuming and technical even though the decisions are not difficult to make. Nonetheless, the rules should be mandatorily followed with consistency. Lenders need to able to identify and process loans that meet the RBI guidelines. By executing the process efficiently, lenders can save time and money and avoid a potential default.

Dynamic forecasting

Automation allows dynamic forecasting by adapting to emerging trends with every dada update. So, companies can plan their sales more effectively, with forecast results mapped to the right operational and financial decision-making units. By automating demand forecasting, insurers can optimize sales plans, underwrite policies, and predict and detect frauds. Dynamic forecasting enables companies to design new business models and launch new products in a short span of time.

Solution configuration

Product configuration is one of the earliest applications of automated decision technologies. It allows customers to specify what features they like to have in a product or service.

Automated decision programs don’t provide a simple solution, rather they produce the most appropriate solution based on a set of variables that can be difficult to reconcile manually. For example, a mortgage lender may have different types of home loans to cater to different types of borrowers; the role of the automated program is to find the right type of loan for the specific borrower.

The system can assess the variety of requirements and eligibility of customers in real-time and present an offer that can deliver a huge profit to the company and improve customer satisfaction.

Reasons why automation is good for financial service providers

  1. Competitive advantage: Automation enables businesses to streamline the validation process and make a faster decision. It also precludes the risk of human errors and helps businesses avoid losses.
  • Better customer relationship: Automated decision-making builds better customer relationships. Businesses can target specific customers by using triggers to offer relevant products and services. It can help in customer retention and driving extra sales with innovative customer relationship methodologies, such as rewarding premium customers.

Automation enables digital portals to offer up-to-date balances, the easy application process, relevant marketing offers and transparency of information.    

  • Consistent decision making: Automating core decision points precludes the risk of bias, reducing confusion around decisions and improving fairness. Advanced techniques can also detect bias in the data.  
  • Improves workflow: With fewer manual processes, businesses can streamline workflows. Automating straightforward application process frees up underwriters to focus on more complex and value-added lending activities.
  • Reduces paperwork: Using a data-driven rules engine facilitates a paperless way of working. Digital applications reduce the need for paper and are linked to an underwriting rules engine, which makes sure that all fields are completed. Automated underwriting typically translates into better customer service levels, consistent decision-making, improved margins and improved process flow.

As per a report by Gartner, by 2024, organizations will reduce operational costs by 30% through a combination of next-gen digital technologies and redesigned operational processes.

That said, automating business processes should not be about saving resources for the sake of it. Not each business process is ideal for automation. Processes that involve profound, judgment-based decision-making should be left to mangers that make decisions by analyzing the data themselves.

Humans can stand to benefit from the advent of modern technology only if it is implemented judiciously and transparently, with the expertise of subject matter specialists at its core.

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