How technology can optimize risk controls, improve operational efficiency for banking, finance

How technology can optimize risk controls, improve operational efficiency for banking, finance

Considering the heavy dependence of banks and financial institutions on paperwork, their first step towards digital transformation

Asif BhatUpdated: Saturday, April 30, 2022, 10:25 PM IST
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With interest rates at record lows and rising talent and compliance costs, the banking and finance sector must elevate operational efficiency to reduce costs, risks and failures. / Representational image |

As we advance further in this digital-first world, the lines between humans and technology are blurring. The addition of the suffix ‘tech’ to industries like finance, insurance, human resources and even education has ushered in a paradigm shift. Additionally, the global pandemic has accelerated the tech tidal wave across industries and verticals. The banking and finance sectors are scrambling to maintain operational efficiency against digital disruptions, evolving customer demands, and rising risks.

With interest rates at record lows and rising talent and compliance costs, the banking and finance sector must elevate operational efficiency to reduce costs, risks and failures. At a time like this, financial institutions are leaning towards modern technologies like AI, ML, automation and data analytics to improve operational efficiency, attract more customers andreduce risk. And while the industry has made great strides in the past few years, sweeping technological transformation can unlock its true potential.

Digitising data extraction process

Considering the heavy dependence of banks and financial institutions on paperwork, their first step towards digital transformation should be converting all data to digital format.

However, a manual approach to data conversion can be extremely costly, time-consuming and error-prone. The market is rife with document conversion services and smart scanning solutions that leverage AI and ML to digitise the data extraction process. Conversion of financial data into digital format will enable customer data monitoring, evaluation and analysis that can improve performance and profitability as well as reduce inefficiencies in the system.

Eliminating grunt work with AI

By deploying AI-based solutions, the banking and finance sector can delegate all of their time-consuming, low value and data-intensive tasks. AI can generate real-time insights into customer behaviour and internal performance more accurately and faster. AI can shed light on critical insights such as customer behaviour, future trends, current performance, etc., that will help banks and financial institutions to maximize their operational efficiency.

Consequently, employees will be able to move beyond time-consuming tasks and zero in on the areas that can finetune the operating efficiency of the industry.

Improving compliance and capabilities

Heaps of documents containing confidential and vital information pass through banking and finance officials every day. For instance, loan officers process loan applications containing sensitive financial information. To ensure regulatory compliance and accelerate processing capabilities, financial institutions should automate and digitalise their document collection and file management process. Technology can curb the exploitation of sensitive information, thereby ensuring compliance. It will also enable the banking and finance sector to operate at a faster speed and reduce the workload of employees.

Reducing redundancies & risks with automation

Banking and finance associates spend a major chunk of their time on redundant tasks like customer onboarding, KYC, loan process application, etc. Verifying vital information manually is time-consuming, error-prone and can increase fraud risk. Instead, the banking and finance sector can automate processes like customer identification, due diligence and loan application to reduce processing time, mitigate risks and build a secure ecosystem.

According to a recent report, robotic process automation (RPA) can reduce data entry costs by up to 70 percent. Consequently, the banking and finance sector can improve their operational efficiency as well as reduce risks.

Leveraging ML for risk management

Banks and financial institutions are prone to a high percentage of credit risk, but technologies like ML and data analytics can bring down this risk percentage. ML can help financial institutions calculate credit default risk and data analytics can peel through layers of credit risk projections, thereby offering greater insights and improving accuracy. With the ability to gather and break down extensive data, banks and financial institutions can manage risk assessment, predict overall risk and make informed decisions to reduce such risk.

Wrapping Up

As banks and financial institutions grow eager to reap the benefits of technology, it is essential to remember that technological transformation is a journey. In the face of growing uncertainties, fierce competition and evolving customer demands, technology can help the banking and finance industry to operate more accurately, efficiently and cost-effectively than ever before. Technology can be the key to optimising risk controls and improving operational efficiency for the sector.

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