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How to choose the correct collections chatbot

September 22, 2020 at 10:53 AM

Principa has a wealth of experience in building and deploying chatbots for the financial services industry. Our custom-built solution is flexible and fully customisable which allows your bot to assume your brand’s persona. We can also seamlessly integrate with existing systems. Click here to find out more. 

Why would you choose to use a chatbot?

Here are a few of the main reasons why financial services business should implement a chatbot:

  • Reduced operational costs
  • Reduced inefficiencies
  • Accessible services
  • Smooths path to purchase
  • Improved customer experience
  • Speedy complaint resolution
  • 24/7/365 availability
  • Consistent messaging
  • Your agents are less consumed by mundane tasks
  • Your agents are more engaged in valuable interactions

How to choose the correct collections chatbot

Chatbots have recently grown in popularity and several companies have started to invest heavily in chatbot technology. However, from a consumer perspective, many people have had little interaction with chatbots and those that have had interactions usually note their experience as a negative one.

So, what is holding this technology back from delivering the service platform which these companies ultimately envisaged when designing the bot?

Are-you-choosing-the-correct-Collections-Chatbot-principa-decIsions-02 BLOG

A Debt Collections Environment

The collections environment must be one of the most hostile working environments to find oneself in. Most notably because the debtor in question is either embarrassed or aggressive when receiving a phone call or notification - After all no one “enjoys” receiving a collections call.

As a consumer, if you know that you are in debt you are highly unlikely to answer an unknown number at work, especially when you don’t want other people to know about your personal difficulties. And most people are even less likely to answer an unknown call at home after hours, especially after a long day at work.

This is exactly why many debt collection companies have moved towards using self-service or digital collections capabilities as these technologies give you the opportunity to interact with debtors in a less personal manner, removing the embarrassment and some of the stress in the situation. It has also been found that debtors are more likely to respond to a digital solution than to a human being.

 "If we already know the importance of mobile messaging as a preferred channel, why is it taking so long for companies to adopt to mobile bot capability?"

A consumer-centric approach

Within any customer-centric environment, customer preference plays a pivotal role and within business it is considered best practice to engage with a customer on a platform they prefer and are most active on.

Take a moment to look around you, what is the preferred platform of choice? Yes, mobile phones.

Within a research report titled “Customer Preference for Messaging” (March 2017 - Market Strategies International), it was found that if companies delayed implementing a mobile message strategy “it would be a strategic blunder, because C2B mobile messaging has become a customer service imperative.”

That begs the question: If we already know the importance of mobile messaging as a preferred channel, why is it taking so long for companies to adopt to mobile bot capability/technology?

And do consumers engage more readily with technology companies whose bot solution can meet these requirements?

Industry experience and knowledge is key

Industry experience and knowledge from a service provider can make or break your company’s digital collections strategy.

In terms of customer experience first impressions last, and therefore there is no time for a test-and-learn approach when it comes to rolling out bot solutions. No consumer wants to reengage with a chatbot if their first experience was a negative one!

“When we look at a collection bot, the conversation flow is vital in realising expectation management when debtors engage with bots.”

Chatbot-Originations-LinkedIn-02-Principa-Decisions

Collection bot conversation flow

When we look at a collection bot the conversation flow is vital in realising expectation management when debtors engage with bots.

In Principa’s recent investigations of “failed” bots we found that many of the bots we engaged with failed to inform the user at the onset regarding what they could assist with which ultimately results in the consumer being left to their own devices to ask the bot questions in order to determine the parameters and to be met with “I do not understand your question” replies.

TOP TIP: If a bot informs you of what they can assist you with from the start, the probabilities of that customer getting frustrated will be greatly reduced.

It is therefore vital to have the knowledge and experience of both bot language flows and the collections landscape, or to use a company with the relevant experience.

The need for a live Service Desk

Now even though an automated / AI bot can assist a customer through some of their journey, it does not mean that they will not need the assistance of a human operator at some stage. If a customer does need to talk to a “human” during their bot interaction, then you would want to be able to immediate hand the conversation over to a “human” operator.

In today’s busy life, there is no time for the dreaded “I will have a consultant get in touch with you”, if a customer engages with you now on this platform, he most likely wants to stay on this platform and just engage with a “human”.

TOP TIP: Make sure your chosen bot solution can integrate into service desks, or that it comes with its own service desk.

Solution Integration

Solution integration is key to a successful bot implementation. Make sure that your chosen bot platform can fully integrate with your collection system, or system of record, in order to provide a complete 360degree view of historical customer interaction to agents and for compliance purposes.

Payment platform integration will also “complete” the bot experience where a debtor can not only view his balance or make an arrangement to pay, but is actually capable of making an immediate payment with his debit, credit card or by EFT through a secure payment portal.

Full data integration will also enable communication analytics, which will drive an enhanced communication strategy. There might be debtors who one would prefer to communicate with in person than via a collection’s bot (as per the example in the next point).

Analytical models to drive bot engagement

Within Collections and Recoveries, analytics plays a major strategic role. At Principa we deploy analytical models to inform us who is likely not to pay us (forward roll), the preferred installment amount to negotiate for, if we should offer the debtor a settlement discount, and what discount percentage we should offer etc.

With the availability of bot communication data, we can also build analytical models which can drive the bot engagement strategy:

  • Who can actually use the bot? (eliminating debtors who use the bot to bypass responsibilities)
  • When are these people most likely to use the bot?
  • Timeslots where there is a high demand for service desk assistance?

The correct solution is key

As important as it is to have a digital collections capability, it is just as important, if not more important to implement the correct solution with the correct technology partner. Principa’s Atura is a powerful artificial intelligence chat solution that uses cloud technology to deliver the right answers to your customers via any device, albeit mobile, desktop or tablet. Chat to us to schedule a demo. 

Contact us further in order for us to understand how better we can meet your needs.

Contact Us to Discuss Your data analytics Business Requirements

Perry de Jager
Perry de Jager
Perry has been involved in Collections and Recoveries for the past 12 years, spending time in different market segments ranging from law firms to investment companies. At Principa, Perry has worked on extended projects within both South Africa and the Middle East with some of the largest financial organisation, providing on-site consulting within the collections and recoveries space covering strategy, process, people and technology.

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The 7 types of credit risk in SME lending

  It is common knowledge in the industry that the credit risk assessment of a consumer applying for credit is far less complex than that of a business that is applying for credit. Why is this the case? Simply put, consumers are usually very similar in their requirements and risks (homogenous) whilst businesses have far more varying risk elements (heterogenous). In this blog we will look at all the different risk elements within a business (here SME) credit application. These are: Risk of proprietors Risk of business Reason for loan Financial ratios Size of loan Risk industry Risk of region Before we delve into this list, it is worth noting that all of these factors need to be deployable as assessment tools within your originations system so it is key that you ensure your system can manage them. If you are on the look out for a loans origination system, then look no further than Principa’s AppSmart. If you are looking for a decision engine to manage your scorecards, policy rules and terms of business then take a look at our DecisionSmart business rules engine. AppSmart and DecisionSmart are part of Principa’s FinSmart Universe allowing for effective credit management across the customer life-cycle.  The different risk elements within a business credit application 1) Risk of proprietors For smaller organisations the risk of the business is inextricably linked to the financial well-being of the proprietors. How small is small? The rule of thumb is companies with up to two to three proprietors should have their proprietors assessed for risk too. This fits in with the SME segment. What data should be looked at? Generally in countries with mature credit bureaux, credit data is looked at including the score (there is normally a score cut-off) and then negative information such as the existence of judgements or defaults; these are typically used within policy rules. Those businesses with proprietors with excessive numbers of “negatives” may be disqualified from the loan application. Some credit bureaux offer a score of an individual based on the performance of all the businesses with which they are associated. This can also be useful in the credit risk assessment process. Another innovation being adopted internationally is the use of psychometrics in credit evaluation of the proprietors. To find out more about adopting credit scoring, read our blog on how to adopt credit scoring.   2) Risk of business The risk of the business should be managed through both scores and policy rules. Lenders will look at information such as the age of company, the experience of directors and the size of company etc. within a score. Alternatively, many lenders utilise the business score offered by credit bureaux. These scores are typically not as strong as consumer scores as the underlying data is limited and sometimes problematic. For example, large successful organisations may have judgements registered against their name which, unlike for consumers, is not necessarily a direct indication of the inability to service debt.   3) Reason for loan The reason for a loan is used more widely in business lending as opposed to unsecured consumer lending. Venture capital, working capital, invoice discounting and bridging finance are just some of many types of loan/facilities available and lenders need to equip themselves with the ability to manage each of these customer types whether it is within originations or collections. Prudent lenders venturing into the SME space for the first time often focus on one or two of these loan types and then expand later – as the operational implication for each type of loan is complex. 4) Financial ratios Financial ratios are core to commercial credit risk assessment. The main challenge here is to ensure that reliable financials are available from the customer. Small businesses may not be audited and thus the financials may be less trustworthy.   Financial ratios can be divided into four categories: Profitability Leverage Coverage Liquidity Profitability can be further divided into margin ratios and return ratios. Lenders are frequently interested in gross profit margins; this is normally explicit on the income statement. The EBIDTA margin and operating profit margins are also used as well as return ratios such as return on assets, return on equity and risk-adjusted-returns. Leverage ratios are useful to lenders as they reflect the portion of the business that is financed by debt. Lower leverage ratios indicate stability. Leverage ratios assessed often incorporate debt-to-asset, debt-to-equity and asset-to-equity. Coverage ratios indicate the coverage that income or assets provide for the servicing of debt or interest expenses. The higher the coverage ratio the better it is for the lender. Coverage ratios are worked out considering the loan/facility that is being applied for. Finally, liquidity ratios indicate the ability for a company to convert its assets into cash. There are a variety of ratios used here. The current ratio is simply the ratio of assets to liabilities. The quick ratio is the ability for the business to pay its current debts off with readily available assets. The higher the liquidity ratios the better. Ratios are used both within credit scorecards as well as within policy rules. You can read more about these ratios here. 5) Size of loan When assessing credit risk for a consumer, the risk of the consumer does not normally change with the change of loan amount or facility (subject to the consumer passing affordability criteria). With business loans, loan amounts can range quite dramatically, and the risk of the applicant is normally tied to the loan amount requested. 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In the graph below the performance of an industry is tracked for two years and then projected over the next 6 months; this is then compared to the country’s GDP. As the industry appears to track above the projected GDP, a positive outlook is given to this applicant and this may affect them favourably in the credit application.                   7) Risk of Region   The last area of assessment is risk of region. Of the seven, this one is used the least. Here businesses,  either on book or on the bureau, are assessed against their geo-code. Each geo-code is clustered, and the projected outlook is given as positive, static or negative. As with industry this can be used within the assessment process as a policy rule or within a scorecard.   Bringing the seven risk categories together in a risk assessment These seven risk assessment categories are all important in the risk assessment process. How you bring it all together is critical. If you would like to discuss your SME evaluation challenges or find out more about what we offer in credit management software (like AppSmart and DecisionSmart), get in touch with us here.

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