Monthly Newsletter | Sep 2020 | Issue 108
Featuring
How to avoid balances being charged off as bad debts
Early warning solution for non-performing debts
Tech Bites
In the News
Major Events
Key Stats
Focus On
How to avoid balances being charged off as Bad Debt
Managing accounts and ensuring on-time repayment are the success mantra of every small business lending. But when it comes to maintaining consistent repayments, most of the time it is a nightmare to lenders. In the lending industry, this comes in the form of delinquency and, ultimately, charge-offs.
Delinquency begins when customers miss their first payment. After a period, the company is required to move the account from delinquency to charge-off status. Most lenders are faced with the fact that a certain percentage of debtors will never pay debts owed. This can inhibit their company’s ability to balance its books and budget for the future. Consequently, companies record the debts as unlikely to be paid and report them to credit reporting bureaus as charge-offs.
This is the model for many businesses, but collections can begin sooner, and account balances can be resolved more quickly to the benefit of everyone. So why can’t lenders plan for an early-stage collection process (pre-charge off) than post charge-off balances?
Pro active strategies to quell charge-offs before it starts
Pre-charged off accounts can involve collecting payments on accounts 1 or 2 days past due. The longer these accounts go unpaid, the longer they harm the creditor’s bottom line and the longer they can accrue interest, late fees, and negative credit reporting for consumers. All customers are not ready to be placed over to third-party collections, and therefore, with early stage collection approach works personally with every customer, reminding them of their obligation to bring their accounts up to date, while concretely maintaining your valued relationships. By using digital methods, proprietary segmentation, structuring, and analytic models, creditors can determine the best method of intervention and best agent to deal with and deploy the collection strategy on every specific case.
Early intervention has many benefits including:
Increased cash flow
Shorter payment periods
Drastic Reduction in accounts that enter delinquency status
Reduced write-offs
customer master record updates
24/7 online accounting tracking, monitoring and status updates
Complete payment processing options and payment updates (direct deposit, check-by-phone, credit card payments, e-payments, money orders or certified checks)
Being chased by debt collection agencies does not improve the situation. Digital Debt Collection enables consumers to self-manage payments and resolves their debts on their own before agents call.
Digital collection-a strategic priority for lenders
Effective risk prediction: Artificial Intelligence (AI) makes risk prediction accurate by analyzing rich data sources and increasing the accuracy of prediction models using machine learning (ML) algorithms.
Customized payment plans: With advanced digital and mobile technologies, mass personalization in debt collection is possible. A customized outreach and collection strategy can help collectors recoup their losses (some, if not all), while also helping customers pay off more of their debt. Personalization of debt collection strategy results in significant benefits – less outstanding debt, higher customer satisfaction and stronger relationships.
ML and Natural Language Processing Technologies : Businesses can aggregate customer data and proactively reach out to customers with alternative debt repayment options and credit counselling in order to mitigate their loss as well as prevent the customer from becoming delinquent
Effective debt recovery plans: AI powered chat bots, by analyzing financial history, can communicate with most likely to default customers, on their preferred channel, at the time convenient to them. Through videos or online content, bots can deliver relevant debt repayment options and recommendations.
There are several things that companies can find themselves with charged-off accounts to consider. First, they need a solid understanding of charge-offs. Second, they need to put in place a strategy for handling them.
To digitize your collection process and to improve resilience against credit losses, Talk to Us
Keep Reading
Early warning solution for non-performing debts
The consumer lending business is centered on the notion of managing the risk of borrower default. Non-performing assets are one of the major challenge lenders face. In this current unprecedented situation with the pandemic, real-time monitoring of transactions in the loan portfolio will provide yet potent ammunition for lenders to keep the risk profile of the credit portfolio, reeling under the impact of the situation, under check. Inconsistent or unreliable approaches to credit analysis expose firms to unnecessary risks. Lenders must be able to assess the risk of default for each customer so that they can decide to whom the offer should be granted, or actions should be taken.
Unfortunately, accurately estimating the credit risk of a borrower is the most challenging task many lenders face. Lenders need a comprehensive approach to non-performing asset management.
Technology intervention in the form of Early Warning Systems help financial institutions to intelligently map and monitor flow of funds and prevent frauds
Need for an early warning solution
A comprehensive early warning framework that included identifying the right customer segment, understanding the data landscape, formulating early warning triggers and creating a risk mitigation plan can help substantially reduce firm’s NPAs.
The lack of due diligence before and after loan disbursal is the single largest contributing factor to the frauds apart from defaults, economic slowdown, and lax lending practices. With the help of disruptive technologies such as artificial intelligence (AI), machine learning (ML) and streaming, data- lenders will be able to “detect suspicious transactions in loan accounts on a real-time/near real-time basis, which will positively contribute to the overall health of the credit portfolio.
An early warning solution can help firms:
Reduce the new NPA flows( and the resulting reduction of NPA in stocks)
Maximise the recovered value and reduce the exposure at defaults with timely alerts
Better utilize capital
Best foot forward
Today’s early warning systems are more effective in not just monitoring and detecting red flags, but also putting firm’s interests ahead of individual interests by measuring and monitoring risks, placing banks back in control of their data and decisions.
So, how do they work? Early Warning Systems rely on multiple data sources to measure and monitor risks. There are four distinct transformative components to the whole system of extracting actionable insights from disparate data:
Collating data from multiple touch points
Cleansing, validating, and restructuring data into valuable information
Algorithmic processing using next-generation technologies and data modelling to generate insightful early warning signals/alerts
Case management by channeling
Early Warning Systems that mine and understand credit-related data – both transactional and external touch points – could have detected and flagged anomalies ahead of time. This gives firms an inkling of inadequate governance in their hierarchies, transactions and customer accounts, before it becomes too late or too difficult to launch a recovery.
Now not only are lenders and financial institutions taking an active interest in governance and monitoring, they are going the extra mile by ensuring that the system is functional and advising additional measures from a regulatory perspective.
To know more, Contact Us
Tech Bites
AUTOMATION! It’s just an alternative!
Have you ever noticed the look on a child’s face when he gets a new toy? It is priceless and he is like at the top of the world. But if we notice, he will lose interest in the toy after a few days and there will be a time where he does not even look at the toy, which once he held as a treasure.
Like this scenario, there are multiple examples that we would be able to see in industries where people embrace new technology with open arms and excitement with the passion of learning and deploying something new, face many trials and hardships in implementing them.
Automation Testing is something promising, that most of the companies now look forward with lots of interest as it would ease tester’s time and do fast execution checks before deployment. This would help the team to deploy projects with confidence. But as the project expands through many iterations, the initial euphoria will lessen, and the team’s confidence will start to lose as scripting and maintaining the automation seems to be less effective and many switches back to Manual Testing.
What causes Test Automation to start positively and slowly deteriorate, what makes the tester feels it is easy to perform manual testing than maintain and test automation scripts.
It takes hard work and continuous improvement to bring forth a good test script.
Here are 5 steps to building a good automation test script
Code simplification: One of the main issues is that the organization of the teams spend less time in simplifying the code/optimizing it. The team entirely focuses on completing the tasks and finishing it in the deadline and they skip the most important part of -making it simple. The simpler the code, the better the performance and efficiency of the test. If code simplification is not done, as the project expands, the harder it will become to maintain the scripts and because of this behaviour, they end up spending more time in code analysis.
Code Review: There are many developers with their own style of coding based on their skill level and experience in the industry. It is highly recommendable to review their script before testing. Let’s say that person A has written a function, but this is unaware to person B as he could use that same function which could be helpful to him in both saving time and testing, as that was already tested and proved functional by Person A. The person reviewing the code should be aware of the codes and would need to maintain an index of common methods which could be helpful to his team.
Testing the scripts: Always test your test scripts. If your script hasn’t failed even once, then do not trust it. If it fails, make sure it has failed for the right reason.
Refactoring the code: Automation engineers should always refactor their scripts from time to time as they need to ask this question — is this code still reliable and valuable (in the sense that it saves time.) Analyze the scripts done 6 months ago to see that this is still reliable and is there a better way to do this. Remove codes that are not needed. This plays a huge role in the testing.
Planning:
a) Choosing the right tool.
b) What all needs to be automated, and whatnot.
c) Identifying a good design and a good process regarding test data and its environment
Automation engineers should always bring some interesting techniques occasionally into the test scripts to keep the passion alive.
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UK fintech Funding Xchange lands $10m in Series A funding round
Funding Xchange (FXE), the UK-based business loan and funding marketplace, has landed $10 million in Series A funding. Its decisioning platform, which powers Monzo, Experian and MoneySuperMarket, last raised funds in November 2019. The round was led by existing backers Downing Ventures and Gresham House Ventures, with participation from new investor Hambledon Capital
The FXE background
Former dairy farmer Katrin Herrling set up FXE in 2014 after the financial crisis saw her farm’s borrowing rates rocket. Former Experian exec Max Firth joined FXE’s in 2018, followed in early 2019 by another Experian alum in Paul Henry. The two pushed FXE towards providing decisioning solutions to banks and lenders, as well as improving the delivery of data analytics. FXE’s white label lending solution digitises steps in the underwriting process for firms trying to serve a wider SME market.The fintech promises SMEs quotes in three minutes, decisions in five minutes, and funds in the bank in ten minutes.
Lending in COVID-19
The pandemic has highlighted a need for easier lending processes for SMEs. “Investors are seeing the significant opportunity to transform SME lending to make funding more accessible, more affordable and more sustainable,” says Herrling in a statement. In the UK, there have been numerous calls from SME lenders for faster accreditation under government schemes, and easier access to capital. Investor Daniel Cheung of Downing Ventures adds that new technologies “are critical to help SMEs access finance at speed and at scale”.
COOs and BCR funds
FXE has been busy this year. The funding follows the appointment of a new chief commercial officer. Ben Sher spent more than 10 years at US financial software firm FIS. He then moved to Q2-acquired Cloud Lending Solutions as its managing director. Sher’s appointment came a month after FXE landed a £5 million allocation from the British Competitions Remedies’ (BCR) Pool E fund. It acquired the new cash in partnership with Shawbrook Bank, Enterprise Nation and the National Association of Finance Brokers. The allocation is designed to give SMEs more access to alternative funding options.The fintech launched a new online portal in April. It helps businesses check eligibility for different types of finance during the pandemic with Experian.The portal, which covers the government scheme loans, allows businesses to check eligibility across a whole 40 lenders.
Black knight launches digital origination suite
Black Knight has launched two new digital tools aimed at accelerating the loan application and approval processes for both consumers and loan officers.The firm has added Borrower Digital and LO Digital to its suite of origination software. Borrower Digital was designed to streamline the loan application process. It harnesses Black Knight’s artificial intelligence capabilities to guide the homebuyer through the pre-qualification, pre-approval, and refinance process.
“The past six months have clearly demonstrated the need to be able to work from anywhere. LO Digital now brings that ability to loan officers everywhere,” said Rich Gagliano, president of Black Knight Origination Technologies. “Combined with the intuitive functionality, the Borrower Digital application brings to the customer experience, Black Knight has further transformed, streamlined and simplified the loan prequalification and application process for everyone involved.”
LO Digital enables loan officers to manage the details of each application. Through a single application, they can access loan products, pricing, pipeline, rate-locking, loan status and automated third-party service orders. “Black Knight is leveraging the power of innovative and integrated technologies to not only simplify the mortgage application and approval process but to improve upon it for both the consumer and the loan officer,” Gagliano said. “By bringing anytime-anywhere functionality to loan officers and giving them a real-time view into the consumer’s application process, our digital originations suite can help our clients gain a competitive edge by providing extraordinary customer service and superior mortgage experience.”
GAO scorches SBA on PPP forgiveness process
The Small Business Administration’s guidance concerning the role of lenders in the Paycheck Protection Program’s loan forgiveness process remains unclear and incomplete, as per the Government Accountability Office.
“Representatives of two [financial services] associations commented that the resource demands and the lack of clarity surrounding the application and forgiveness processes have led to lender fatigue with the program,” the GAO said in a lengthy review of the federal government’s overall response to the coronavirus crisis.
Representatives of the trade groups noted that lender fatigue could result in lenders being less likely to participate in future rounds of the program. Trade groups representing the financial services industry have been pushing Congress to provide automatic loan forgiveness for loans under $150,000.
In the report, the GAO said that gaps in data in myriad areas make measuring the federal response to the pandemic difficult. For example, the GAO again said that the SBA’s failure to collect demographic information about PPP recipients confounds efforts to measure how well the program has responded to the needs of small business.
The GAO noted that lending in the PPP program has stopped and that the loan forgiveness process has begun“. But uncertainty about the lender’s role in the process and the complexity of the process could result in additional difficulties and delays for borrowers in obtaining loan forgiveness,” the GAO said.
The GAO added, “In part because the CARES Act includes specific requirements for loan forgiveness, applying for loan forgiveness is more time consuming than applying for the PPP loan itself and requires more lender review.”
The SBA issued guidance about loan forgiveness in July and August, but representatives of two lender associations said they still were not clear about the level of review that was required or the extent to which lenders could simply rely on borrower certifications and calculations.
SBA officials said they intend to put all lender decisions granting full or partial loan forgiveness through an automated process, but as of Aug. 14, well after the forgiveness process began, the agency was still developing its review process.
Representatives of one lender association told the GAO that it was a conflict of interest for lenders to be heavily involved in the loan forgives process because it was in their best interest for loans to be forgiven.
Events
LENDIT FINTECH USA 2020
Sep 29-Oct 1, 2020, New York, United States
Key Stats
Central Bank Interest Rates and Current Libor Rates
| GBP Libor (overnight) | Interest |
(23-09-2020)Central BanksInterest RatesEuro Libor-0.58243%American Interest rate (FED)0.25%USD Libor0.08038%Australian Interest rate (RBA)0.25%CHF Libor-0.78900%British Interest Rate (BoE)0.10%JPY Libor-0.12117%Canadian Interest Rate (BOC)0.25%GBP Libor 0.05263 %Japanese Interest Rate (BoJ)-0.10%
