Innovative Tools – Quantify qualitative Information, use the available Knowledge

This is the sixth article in a series of blog posts in which we introduce the concepts of knowledge-based lending for SME business. In this article, we present several innovative tools provided through Q-Lana Those tools will simplify the information collection process and take advantage of the ability to analyze and benchmark information on the spot.

We believe that each of these tools provides significant value added and will lift the institution higher in the approach to knowledge-based lending. For more information about Q-Lana, please read below and contact us

A major challenge in the risk assessment of SME borrowers is the largely unstructured and of qualitative nature of information. Financial Institutions find it difficult to approach the assessment this information which often includes only rudimentary and unaudited financial statements. Mass market retail loans are easier to evaluate because of the larger share of quantifiable information which can serve as a better input for a quantitative scoring module.

 

Don’t underestimate the importance of monitoring of SME loans!

We see a fundamental difference in the focus of assessment and monitoring of retail/microfinance loans versus larger SME loans. A retail loan approval can be compared to a bet on the client’s ability and willingness to repay the loan, based on the best possible information. The performance of an SME loan can be influenced through active monitoring and guidance of the borrower over the lifespan of the loan.

For this reason, we consider providing financial services to SMEs as one of the more interesting and challenging business areas for financial institutions. SME clients require specific understanding of their way to conduct business, the entrepreneur’s personality, strengths and weaknesses. We have developed several tools within Q-Lana that help dealing with this specific nature of information and supporting banks to assess the information better. In the following, we will explain a few of them.

Networking

SMEs operate within the business community of a country/region. A close tie with other companies is very common, as entrepreneurs know and trust each other, and employees move between companies of the same sector. Often there are close business ties with suppliers or exporters. It is also typical for entrepreneurs in developing countries to own a conglomerate of companies across different sectors, managed by family members. For the analysis of risk, identification of early warning signals and crisis management in case of a payment default, the knowledge of those ties is important. Q-Lana allows to link companies and individuals based on several criteria, including: family relationships, company ownership, employment, supplier or customer relationship.

Through building those relationships on the Q-Lana platform, it becomes easier to understand the risk relationships. Such an understanding helps the Financial Institution in the monitoring. Critical exposures can be placed on a watch list which requires a closer monitoring until the nature of the risk is assessed. For example, in the case of delivery problems of a supplier, the Financial Institution can assess immediately which other borrowers are affected or can recommend alternative suppliers. In case of financial difficulties of a client, the risk profile of its employees, related companies or business partners can be assessed.  Q-Lana makes such analysis easy to execute

Start Rating of Qualitative Information

The Q-Lana platform is set up to facilitate the qualitative monitoring of clients and exposures. The monitoring happens largely through interaction with clients. A post disbursement visit and the quarterly/annually review our scheduled ways of monitoring activities. In addition, there can be ad hoc visits of the client’s facilities or other observations, resulting for example from communication with other clients. Q-Lana allows to track all those observations in structured visit/observation reports. Each report can be classified with five-star grading. An observation rated with five stars represents very positive news for the client. While each observation is subjective, the accumulation of observations within the institution will create objectivity. The financial institution can analyze the grading trends for all observations across the portfolio, sectors, and individual clients. This trend analysis helps the financial institution to identify specific trends early on.

Rating Tools

Rating tools are another way to summarize the assessment of client observations. As explained in the third blog entry, Q-Lana has a rating widget which can be applied at several stages of the lending process, including the pre-disbursement assessment as well as the post disbursement early warning monitoring. The rating methodology can be based on statistical as well as heuristic concepts. When developing Q-Lana we recognize that the calibration of such models will always happen in a separate exercise, as most institution like the necessary number of transactions, to apply technologies such as machine learning.

Active Monitoring

To facilitate the active monitoring of exposures, Q-Lana provides a number derived from Customer Relationship Management. At any stage, the user can add tasks with specific deadlines for other employees as well as himself, as reminders about follow-ups with clients, deadlines, maturity dates of collateral and other purposes. Those tasks can be tracked on the user’s front page (Dashboard). Q-Lana also integrates social media feeds. In case the client actively maintains a presence on social media sites such as LinkedIn, Facebook, or Twitter, updates are fed into the touch point trigger.

Watch List

In many countries, regulatory authorities define a classification for loans, in which the first category of risky loans are defined as “watch”. Q-Lana expands the expression of a watch list to clients which are still performing but show early warning signals of risk. For any financial institution, the riskiest clients are not those which are 30 or more days in areas, but those which are still performing today, yet are at risk to miss a payment in the future. Clients in arrears are certainly problem loans, but there is reduced uncertainty about the credit quality, since they already failed on a payment. Q-Lana’s watchlist is a simple methodology to identify risky exposures and place them on a list. Consequently, the relationship manager is required to comment on the riskiness of the exposure, implement ways to mitigate the risk, or define the risk as minor. Clients remain on the watchlist, until solutions are found for the mitigation of risk.

Risk Advisory

Q-Lana is also preparing the launching of a Risk Advisory function. This will consist of a team of in-house experts and consultants who support the client financial institutions in the assessment of the risk profile, improvement of the risk management process, and implementation of solutions for specific risk situation. Any client of Q-Lana can sign up for the services of the Risk Advisory and can receive support in a defined manner. One of the benefits of such a risk advisory is the ability to share information about trends. A financial institution which is prepared to share certain performance information of its portfolio (within the framework of protection of confidentiality), will receive aggregated industry information about the risk trends, performance issues and other observations made across the universe of Q-Lana clients.

Each of the tools presented in this text provides a unique and if it for the financial institution in the process of managing the credit risk of its loan portfolio. Client of Q-Lana can use those tools at their discretion. We also expect to develop additional tools and methodologies as we are collecting information from the financial institutions.

About the author:

Christian Ruehmer is the Co-Founder and CEO of Q-Lana. Christian has over 25 years of experience in finance working for several large international banks in the areas or Risk Management, Credit Portfolio Management, and Investment Management. Christian has been an advisor in this sector, working with over 75 MFIs, banks, and international organizations, primarily in developing countries. He is the head of Risk and Compliance at Bamboo Capital Partners and sits on the board of several companies in the finance sector

About Q-Lana:

Q-Lana provides a digital platform to transform traditional lending into a knowledge-based, risk focused process. By digitizing the initial assessment, application and approval, monitoring and portfolio management process, as well as the collection, the financial institution generates significant knowledge about the performance and the credit quality of the target clients. This can be used to improve lending decisions, avoid losses and provide advanced support to the clients. Q-Lana replicates the existing lending process and allows for modifications to apply best practice. In addition, Q-Lana provides intelligent reporting and customized risk advisory. Q-Lana is based on a SaaS model that integrates well with existing core banking software and can be implemented within a 3-4 month timeframe. 

Contact:

christian@q-lana.com

Monitoring and Early Warning System – Identify Trends before they become Problems

This is the fifth article in a series of blog posts in which we introduce the concepts of knowledge-based lending for SME business. In this article, we introduce the monitoring process and the early Warning System. Those process steps are essential for the successful execution of SME lending. While each financial institution needs to conduct a thorough risk assessment and approval, the actual monitoring of the exposure it is equally if not more important. Clients will experience challenging situations over the life of a transaction and are in need for support from their financial institution.

We have integrated a detailed monitoring process into the development of Q-Lana, the digitization platform for knowledge-based lending. This allows the early discovery of problems developing with lending exposures, far before an actual payment default. We have developed Q-Lana as a comprehensive, fully customizable and intuitive, filled with smart tools and analytics to support financial institutions. For more information about Q-Lana, please read below and contact us

Q-Lana enables financial institutions to develop sound credit-monitoring and risk-mitigation capabilities. The earlier a financial institution identifies and responds to deterioration of credit risk, the better is the possibility to avoid problems, including defaults. Q-Lana identifies risky customers and exposures far before they experience payment problems and can easily differentiate between inability and unwillingness to service a loan. Critical customers can be placed on an internal watch list, to allow a more thorough monitoring of the relationship and the early development of mitigating solutions. This also helps financial institutions to support its clients during critical phases where they are in urgent need for such support.

 

Monitoring Process

A financial institution shall focus on the monitoring of the borrowers right after the disbursement. This relates to the process of regular monitoring of performing loans. The key steps of the regular monitoring are summarized in the following picture

 

There is high importance for the monitoring, especially of long-term exposures. It is quite common that clients will experience financial or operational difficulties over the course of a longer credit exposure. Q-Lana has developed a structured process for the monitoring of exposures after disbursement. The specific process can be adjusted for the requirements of a financial institution. An example of the necessary steps is provided in the following table:

Initial Supervision Report: A financial institution requires the loan officer to conduct a follow-up visit within a certain number of days after the disbursement of the loan. This is primarily serves the purpose to verify the actual use of funds and to assess the project performance with the newly injected funds. The loan officer is required to comment on any observation be it positive or negative and to verify whether the conditions that were used to justify the approval are still valid. The form provided through Q-Lana has space for suggested follow-up items. Q-Lana will define internal tasks for each of those follow-up items to ensure that they are timely addressed. The exposure can be moved to watch-list.

Monitoring – Ongoing Monitoring: subsequent to the initial visit a regular monitoring process is started the by the loan officer. The rules of the specific institution define the frequency of such monitoring visits. For borrowers of weaker credit quality, such meetings shall happen on a more frequent basis. In each of these visits, the client’s performance is assessed and compared to the information given here in the initial loan application. Any comments or observations are noted in a report. Specific follow-up items can be set and tracked. In addition, the loan officer needs to suggest the time for the next follow-up visits and comments on the need to move the borrower to the internal watch-list.

Monitoring – Other Observation: in addition to the regular reporting’s, there is the possibility to submit “Other Observations”. This can include informal visits, observations or comments made “on the street”, reference to products, news or any other relevant information.

Early Warning System: With an effective Early-Warning System (EWS), credit losses as well as capital requirements can be reduced through de-risking. This will improve the institution’s capacity to take risk, increase returns and improve the capital productivity. For the client, the benefits include lower pricing as well as the active support from a qualified expert in the management of critical situations. The EWS is well integrated into the monitoring process of Q-Lana

Q-Lana has integrated the EWS into the standard procedures and allows the institution to identify borrowers at risk through a structured monitoring process and the integration of warning signals. The Q-Lana EWS is built on several categories of indicators, allowing the identification of critical exposures based on electronic information/automated triggers, expert knowledge about the exposure, as well as external information. The categories are:

  • Quantitative Criteria – the EWS analyzes the utilization of credit lines by borrowers, borrowing activities, cumulated arrears days and other indicators. Early warning indicators are triggered if certain patterns are discovered. For example, as soon as the utilization reaches certain limits and remains at that level, the exposure is flagged as riskier.
  • Covenant Monitoring – the loan documentation might include affirmative and negative covenants, representations and warranties and other requirements. The monitoring of the compliance with these covenants is part of the EWS. Here, not only the breach of certain covenants is monitored but also the absolute value of quantifiable covenants. In this way, trends can be assessed allowing to identify weakening credit quality at early stages.
  • Financial Analysis – on a regular basis, the institution receives financial information from clients. This financial information is tracked within Q-Lana and assessed through the review of certain ratios. At the same time, the institution can update the internal rating system with the new financial data, allowing the calculation of new rating values and incorporating the trends of the rating development into the EWS
  • Early Warning Questions – Q-Lana has developed an early warning questionnaire which is part of the monitoring package. Loan officers can apply this questionnaire during the regular monitoring visits or when a visit is requested through the placement on watch-list. Details about the assessment questionnaire can be found in the attachment.
  • Early Warning Monitor – all observations of the EWS are summarized in a dash dashboard which visualizes the specific monitoring results categorized along the line of the above-mentioned criteria

Internal Watch List – Special Monitoring:  if an exposure is identified through the monitoring process as deteriorating or critical, it is placed on the internal watch-list. The number of days this exposure is placed on watch-list is tracked. It is required to prepare a special assessment of the exposure considering the reasons for placing it on watch list. Based on this initial assessment, the next steps are defined, which can include (in order of severity):

  • Removal of the client from the list as the identified issues have been deemed mitigated
  • Keeping the client on watch list for a more frequent monitoring procedure
  • Developing measures for risk mitigation in order to improve the risk profile of the exposure and/or support the client in the recovery from a current problem
  • Moving the clients to special servicing/recovery, in case the client is in default and issues have been too severe for a return to normal conditions in the future

Loan Collection Process – Defaulted Loans Once a client is in default, the financial institution applies a strict procedure to collect the funds or to start additional measures quickly in case the collection seems difficult or impossible. The specific steps for the collection process depend on the financial institution. A sample process is described in the following table

Post Mortem Analysis – by closely analyzing defaulted loans and discovering the patterns behind defaults or the reasons, a financial institution can gain valuable information to improve the risk assessment of individual loans in the future. Reasons for defaults can be “avoidable mistakes” such as improper credit analysis and reliance on non-verified information, or “unavoidable reasons” such as sudden health issues for the borrower or natural disasters. [60] days after the default, the loan officer is required to fill the Post Mortem Questionnaire.

The Post Mortem Questionnaire are available to those loan officers who have loans with payments in arrears above 60 days. The loan officers have 5 business days to fill and return the questionnaires. The information is analyzed, aggregated and provided to the team as a training measure.

We believe in the high importance of a structured monitoring process, specifically in SME lending. While the initial analysis is important, the monitoring is even more relevant for the performance of the loan portfolio. Q-Lana takes this into consideration through the list of tools and instruments provided to the financial institution. Here even more the importance of knowledge-based credit risk management becomes obvious. The borrowing clients will appreciate the sophisticated approach to monitoring as this clearly positions the financial institution as partner to the business

About the author:

Christian Ruehmer is the Co-Founder and CEO of Q-Lana. Christian has over 25 years of experience in finance working for several large international banks in the areas or Risk Management, Credit Portfolio Management, and Investment Management. Christian has been an advisor in this sector, working with over 75 MFIs, banks, and international organizations, primarily in developing countries. He is the head of Risk and Compliance at Bamboo Capital Partners and sits on the board of several companies in the finance sector

About Q-Lana:

Q-Lana provides a digital platform to transform traditional lending into a knowledge-based, risk focused process. By digitizing the initial assessment, application and approval, monitoring and portfolio management process, as well as the collection, the financial institution generates significant knowledge about the performance and the credit quality of the target clients. This can be used to improve lending decisions, avoid losses and provide advanced support to the clients. Q-Lana replicates the existing lending process and allows for modifications to apply best practice. In addition, Q-Lana provides intelligent reporting and customized risk advisory. Q-Lana is based on a SaaS model that integrates well with existing core banking software and can be implemented within a 3-4 month timeframe. 

Contact:

christian@q-lana.com