Month: May 2022

The coronavirus crisis has escalated the need for financial institutions to digitise their processes. The digitalisation of a financial institution’s lending process is no longer an option, but a requirement in this current economic climate. Firms must consider the compelling benefits of artificial intelligence (AI) when digitalising their credit process to overcome the COVID-19 economic crisis and stay ahead of competition.

Covid-19 impact and how to emerge stronger with digitalization

 

Lending is one of the areas that has significantly been affected by the pandemic. In response to the pandemic, businesses must focus on digitalization.

 

Using new data and AI to improve business: Companies need to incorporate new data and create new models to enable real-time decision- making. Accelerate process automation

 

Refocus digital efforts towards customer expectation: Align the organization to new digital priorities. Launch new digital offering channels.

Selectively modernize technology capabilities: Begin strengthening technology talent bench. Set up a cloud-based data platform and automate the software delivery pipeline.

 

Upskill organization for accelerated digital efforts: Deploy new models leveraging agile and remote.

 

Lend more and smarter using ML & AI

 

Digital transformation was never just about technology. With digitization, businesses can drastically lower the operational costs, increase efficiency and speed of decisions. Automating the processes can reduce risks by employing advanced scoring techniques to supplement the traditional approaches and data sources.

 

Using AI in lending shows up in several productivity-enhancing aspects, including

 

Forecast cash-flow: Cash flow is likely to continue to be a serious concern for smaller businesses as revenue streams dry up. Multiple AI and Machine Learning algorithms can process datasets including inflows/outflows, sales orders/customers invoices, purchase orders/vendor invoices and expense reimbursements for comprehensive as well as accurate cash flow forecasts.

 

Predict future losses: COVID-19 has brought about a stressed financial environment that affected credit quality and credit losses. An AI dashboard uses various criteria points that can help in predicting and preparing for these losses by highlighting patterns and trends—right down to the loan type, region, branch location, etc.

 

Sales prioritization: With AI, the algorithm can compile historical information about a client, along with social media postings and the salesperson’s customer interaction history (e.g., emails sent, voicemails left, text messages sent, etc.) and rank the opportunities or leads in the pipeline according to their chances of closing successfully.

 

Agile risk management: AI can complement the internal controls and early warning systems already in place around loan approvals, disbursement, and monitoring. A strong AI dashboard can also provide regular insights on the overall health and status of your loan portfolio in real-time, allowing you to make more accurate risk assessments and pivot as necessary.

 

Enhanced decision-making: In a post-COVID-19 world, lenders will likely exercise greater caution when it comes to credit risk. AI can help flag potential problems and potential biases at the loan authorization stage. It can provide managers with greater visibility and access to data, to make decisions that align with the organization’s risk appetite and policies.

 

Back office tasks: AI-powered cognitive assistants can perform a company’s back-office tasks effectively

 

AI- an evolving technology

 

Artificial Intelligence is the future. Sure enough, the technology is young and has its drawbacks. It requires high costs, and its implementation is both time and effort consuming. But unrealistic expectations that used to generate fuss around these technologies have turned into real business scenarios. It is especially noticeable in the field of finance. Embracing Digital Transformation driven by digital technologies can help lenders grow their loan book and acquire more customers. 

 

Specifically, under the larger umbrella of digital technologies, Artificial Intelligence (AI) is the differentiator. AI can unearth and learn customer-behaviour patterns that help lenders differentiate themselves from the competition. Let’s look at a couple of high-impact areas that AI can influence significantly in terms of transformation, and help lenders improve their loan books.

 

If you, are you looking for ways to harness the power of machine learning and AI for your business, or would just like to know more, Contact Us.

During the COVID-19 crisis, buy-now-pay-later (BNPL) emerged as a hot segment within consumer lending when a large portion of consumer spending moved online. By venturing into BNPL space, financial firms can create a niche by transforming into two-sided marketplaces where they not only facilitate transactions but also provide a marketplace for discovery of new products. This enables access to granular customer data that can be used for credit assessment.

 

How lenders can enter the BNPL space

 

Participating in the BNPL space will require financial institutions to invest significantly in technology capabilities as well as marketing initiatives. Lenders who want to take advantage of the opportunity in BNPL can try few different approaches and increase their chances of success in the BNPL space.

 

Customer Affordability as a Service: As economic activity rebounds, people are facing elevated levels of inflation with potential increases in interest rates forecast in early 2022. To meet the increasing regulatory requirements and to ensure good customer outcomes, firms need to work towards more customer-centric affordability assessments. The introduction of consistent modelling for income and outgoings across all areas of the business will give lenders increased control, consistency, and agility to react to regulatory changes.

 

Purpose driven: Lenders can determine what each customer can afford, educate them, and help them avoid overspending by managing their overall limit and exposure.

 

Holistic approach : Firms can manage the merchant acquirer and card issuer businesses holistically, which will enable them to run connected campaigns and manage a combined P&L for the two businesses.

 

Loyalty and personalization: Lenders can proactively create offers and manage real-time personalization of both in-store and e-commerce purchases. When there are multiple offers at the checkout, customers will choose the most personalized and relevant option. Banks will be forced to be contextual and relevant at the moment of purchase.

 

Charging into to the BNPL battle 

 

Traditional card issuers and consumer lenders can’t afford to ignore the BNPL trend-some have already launched and others are working on their own variation.  In its simplest form, BNPL is not a new proposition, and usually involves offering customers the facility to break payments for goods and services into multiple installments.

 

Lenders can increase customer engagement, wallet share, and loyalty by offering seamless, convenient shopping experiences. BNPL can benefit incumbent banks that can use existing strengths, such as better loan term and condition flexibility and increased capital utilization owing to quicker loan turnover and lower regulatory capital requirements. BNPL also provides cross-selling opportunities to bank and non-bank customers who are likely to be more engaged.

 

As far as customers are concerned, even though they pay in installments, they gain full ownership of the product. The fixed payments help them budget their expenses. Customers also tend to prefer BNPL for purchases under a threshold such as $500, and anything over that, they prefer instalment plans that can stretch up to a year.

 

Key takeaways

 
  • Buy now, pay later arrangements are point-of-sale installment loans that allow consumers to make purchases and pay for them at a future date.
  • Consumers typically make an upfront payment toward the purchase, then pay the remainder off in a predetermined number of installments.
  • Buy now, pay later plans often don’t charge interest and are often easier to get approved for than traditional credit cards or lines of credit are.
  • Normally, BNPL doesn’t affect your credit score; however, late payments or failing to pay can damage your credit score.

 

Road ahead

 

BNPL has suddenly emerged as a disruptive force in the payments and consumer finance industry. It needs to be seen as not just a new twist to merchant payments, but as a paradigm shift in how banks can engage with their customers and increase revenue. Existing and emerging digital payments require embracing technology and innovation along with a safer digital experience to win the trust of customers. 

 

In the tech-driven payments space, open banking and real-time payments infrastructure is expected to create innovative payment solutions for customers, and new pathways to accept payments for merchants and corporates. To retain customer base and a competitive edge, Lenders must quickly foray into this segment. Accomplishing this, however, may require them to partner with a service provider with the necessary contextual knowledge and technology expertise after a comprehensive market analysis.

 

Contact Us

Monthly Newsletter | May 2022 | Issue 118

Featuring 

  • Is ‘Buy Now Pay Later’, the next payment disruption in consumer lending?
  • Lending digitalization & AI beyond hype.
  • In the News
  • Major Events

Focus On

 

BUY NOW PAY LATER

 

Is “Buy Now Pay Later’, the next payment disruption in consumer lending? 

During the COVID-19 crisis, buy now pay later (BNPL) emerged as a hot segment within consumer lending when a large portion of consumer spending moved online. By venturing into BNPL space, financial firms can create a niche by transforming into two-sided marketplaces where they not only facilitate transactions but also provide a marketplace for discovery of new products. This enables access to granular customer data that can be used for credit assessment.

 

How lenders can enter the Buy Now Pay Later space

 

Participating in the BNPL space will require banks to invest significantly in technology capabilities as well as marketing initiatives. Lenders that want to take advantage of the opportunity in buy now pay later can try few different approaches and increase their chances of success in the BNPL space.

Customer Affordability as a Service: As economic activity rebounds, people are facing elevated levels of inflation with potential increases in interest rates forecast in early 2022. To meet the increasing regulatory requirements and to ensure good customer outcomes, firms need to work towards more customer-centric affordability assessments. The introduction of consistent modeling for income and outgoings across all areas of the business will give lenders increased control, consistency, and agility to react to regulatory changes.

Purpose driven: Lenders can determine what each customer can afford, educate them, and help them avoid overspending by managing their overall limit and exposure.

Holistic approach: Firms can manage the merchant acquirer and card issuer businesses holistically, which will enable them to run connected campaigns and manage a combined P&L for the two businesses.

Loyalty and personalization: Lenders can proactively create offers and manage real-time personalization of both in-store and e-commerce purchases. When there are multiple offers at the checkout, customers will choose the most personalized and relevant option. Banks will be forced to be contextual and relevant at the moment of purchase.

How lenders can benefit from Buy Now Pay Later

Lenders and other financial firms ignored BNPL thinking of it as yet another variation of installment-based payments, a segment they are already present in through credit card-based installment programs. In its simplest form, BNPL is not a new proposition, and usually involves offering customers the facility to break payments for goods and services into multiple installments.

Lenders can increase customer engagement, wallet share, and loyalty by offering seamless, convenient shopping experiences. BNPL can benefit incumbent banks that can use existing strengths, such as better loan term and condition flexibility and increased capital utilization owing to quicker loan turnover and lower regulatory capital requirements. BNPL also provides cross-selling opportunities to bank and non-bank customers who are likely to be more engaged.

As far as customers are concerned, even though they pay in instalments, they gain full ownership of the product. The fixed payments help them budget their expenses. Customers also tend to prefer BNPL for purchases under a threshold such as $500, and anything over that, they prefer instalment plans that can stretch up to a year.

Key takeaways

  • Buy now, pay later arrangements are point-of-sale installment loans that allow consumers to make purchases and pay for them at a future date.
  • Consumers typically make an upfront payment toward the purchase, then pay the remainder off in a predetermined number of installments.
  • Buy now, pay later plans often don’t charge interest and are often easier to get approved for than traditional credit cards or lines of credit are.
  • Normally, BNPL doesn’t affect your credit score; however, late payments or failing to pay can damage your credit score.

Conclusion

 

BNPL has suddenly emerged as a disruptive force in the payments and consumer finance industry. It needs to be seen as not just a new twist to merchant payments, but as a paradigm shift in how banks can engage with their customers and increase revenue. To retain customer base and a competitive edge, Lenders must quickly foray into this segment. Accomplishing this, however, may require them to partner with a service provider with the necessary contextual knowledge and technology expertise after a comprehensive market analysis.

 

Keep Reading 

 

Lending digitalization and AI: beyond hype. The coronavirus crisis has escalated the need for financial institutions to digitise their processes. The digitalisation of a financial institution’s lending process is no longer an option, but a requirement in this current economic climate. Firms must consider the compelling benefits of artificial intelligence (AI) when digitalising their credit process to overcome the COVID-19 economic crisis and stay ahead of competition.

Covid-19 impact and how to emerge stronger when digitizing lending processes

Lending is one of the areas that has significantly been affected by the pandemic. In response to the pandemic, businesses must focus on digitalization.

Using new data and AI to improve business: Companies need to incorporate new data and create new models to enable real-time decision- making. Accelerate process automation

Refocus digital efforts towards customer expectation: Align the organization to new digital priorities. Launch new digital offering channels.

Selectively modernize technology capabilities: Begin strengthening technology talent bench. Set up a cloud-based data platform and automate the software delivery pipeline.

Upskill organization for accelerated digital efforts: Deploy new models leveraging agile and remote.

Lend more and smarter using ML&AI

Digital transformation was never just about technology. With digitization, businesses can drastically lower the operational costs, increase efficiency and speed of decisions. Automating the processes can reduce risks by employing advanced scoring techniques to supplement the traditional approaches and data sources.

Using AI in lending shows up in several productivity-enhancing aspects, including

Forecast cash-flow: Cash flow is likely to continue to be a serious concern for smaller businesses as revenue streams dry up. Multiple AI and Machine Learning algorithms can process datasets including inflows/outflows, sales orders/customers invoices, purchase orders/vendor invoices and expense reimbursements for comprehensive as well as accurate cash flow forecasts.

Predict future losses: COVID-19 has brought about a stressed financial environment that affected credit quality and credit losses. An AI dashboard uses various criteria points that can help in predicting and preparing for these losses by highlighting patterns and trends—right down to the loan type, region, branch location, etc.

Sales prioritization: With AI, the algorithm can compile historical information about a client, along with social media postings and the salesperson’s customer interaction history (e.g., emails sent, voicemails left, text messages sent, etc.) and rank the opportunities or leads in the pipeline according to their chances of closing successfully.

Agile risk management: AI can complement the internal controls and early warning systems already in place around loan approvals, disbursement, and monitoring. A strong AI dashboard can also provide regular insights on the overall health and status of your loan portfolio in real-time, allowing you to make more accurate risk assessments and pivot as necessary.

Enhanced decision-making: In a post-COVID-19 world, lenders will likely exercise greater caution when it comes to credit risk. AI can help flag potential problems and potential biases at the loan authorization stage. It can provide managers with greater visibility and access to data, to make decisions that align with the organization’s risk appetite and policies.

Back office tasks: AI-powered cognitive assistants can perform a company’s back-office tasks effectively

AI- an evolving technology

Artificial Intelligence is the future. Sure enough, the technology is young and has its drawbacks. It requires high costs, and its implementation is both time and effort consuming. But unrealistic expectations that used to generate fuss around these technologies have turned into real business scenarios. It is especially noticeable in the field of finance. Embracing Digital Transformation driven by digital technologies can help lenders grow their loan book and acquire more customers. Specifically, under the larger umbrella of digital technologies, Artificial Intelligence (AI) is the differentiator. AI can unearth and learn customer-behaviour patterns that help lenders differentiate themselves from the competition. Let’s look at a couple of high-impact areas that AI can influence significantly in terms of transformation, and help lenders improve their loan books.

If you, are you looking for ways to harness the power of machine learning and AI for your business, or would just like to know more, Contact Us.

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