By CPA Robert Mwangi
Impact Of NPLS on Profitability & Liquidity
In credit management, risk refers to the likelihood that a borrower will default on a loan. A bank must devise a risk management strategy as a key part of the credit management cycle. The risk management strategy and the effectiveness and adherence of the credit policy will determine the level of NPLs and loan provisioning by the bank.
While presenting the 2023 audited financial statement, Equity bank CEO, Dr. James Mwangi explained that the bank raised its loan loss provisions late in 2023 to Kes 19.5B after noticing that real estate, manufacturing and transport & logistics sectors were deteriorating among other factors. The increased loan provision saw Equity Bank (Kenya) profit after tax and exceptional items and minority interest reduce from 33.4B recorded in 2022 to 26.7B in 2023. Equity bank (Kenya) loan loss provision stood at Kes 8.5B in 2024, representing 13.6% of the total operating expenses
The same trend was observed in KCB Bank, where loan provision tripled to 25Billion in 2023, eroding shareholders’ value, as profit after tax (PAT) and exceptional items declined from 34.7Billion in 2022 to 25.4Billion in 2023.
These figures underscore the importance of dealing decisively with Non-Performing Loans to increase the lender’s profitability and shareholder value.
To deal with NPLs and reduce expected credit losses (ECL), the credit process and bank credit policy must be fully adhered to. A stringent credit management process, from appraisal to repayment follow-up, is key to reducing overall loan write-offs. Any gap in the process can only lead to increased provisions and, eventually, write-offs.
Credit Appraisal
The credit appraisal process begins with the credit analyst, who obtains relevant information from the client, Credit Bureaus (CRBs), financial statements, public information, and references, and analyses it against the bank’s set policy and the Central Bank of Kenya (CBK) prudential guidelines on lending. Most banks employ the CAMPARI and CCPARTS framework to assess the creditworthiness. CAMPARI measures the character of the borrower, the Ability to repay, the borrower’s capacity to obtain sufficient capital to invest in the business, the purpose of the loan, Repayment sources, and Insurance or collateral to cover the loan in case of default. The credit analyst must follow the established policy to ensure credit is extended to those who can repay the loan, thereby reducing default risk and NPLs.
Credit Approval
The credit analyst escalates the credit appraisal outcome to credit approvals for further review, particularly regarding credit risks and mitigation. After the approvers give the loan a clean bill of health, the credit committee will approve or reject it. The loan is then disbursed.
Importance of appraisal, KYC and adherence to bank lending policy
One of the biggest contributors to the high number of NPLs is poor KYC collection. The proof of residential address, KRA PIN certificate, Business Verification Documents (for corporate accounts), including the incorporation certificate, CR12, business KRA PIN certificate, Memorandum and Articles of Association and most importantly, contact information, tend to be of utmost importance when following up on NPL accounts.
Walking with the customer
Imagine getting a call from your bank account manager after you have taken a business loan to expand your business, not because you have defaulted on an instalment, but just following how the business is progressing. This will definitely make you feel good and valued. For the account manager, even though they have not asked you about the loan repayment, it has subconsciously registered in your mind that your instalment is coming up soon, which greatly reduces the chance of default. In my previous article on the Nov/Dec edition, on ‘Dealing with Trade Receivables’, I explained why it’s important to keep in touch with a credit customer immediately the invoice is sent or goods delivered/services rendered, not to ask for payment, but just to ask if everything is in order. It’s no different from loans.
Monitoring
| TIME IN DAYS | STATUS | ACTION | RESPONSIBLE PARTY | ECL PROVISION |
| 0 – 30 | Current | Check up call/email/Message | Credit Assistants | – |
| 31 – 45 | Early Watch | Follow up call/email/Message | Credit Assistants | 5% |
| 46 – 60 | Watch | Escalation to credit manager | Collections | 5% |
| 61 – 75 | Watch | Review by collection manager. Demand. | Collections | 5% |
| 76 – 90 | Substandard | Follow up by recovery department | Recovery | 5% |
| 91 – 180 | Substandard | Early outsource to Debt Collection Agencies (DCAs) | DCA/Credit Manager | 25% |
| 181 – 360 | Doubtful | Outsource to DCAs | DCA/Credit Manager | 50% |
| OVER 360 | Loss | Outsource to DCAs, Legal | DCA, Legal, CFO | 100% |
Early warning signs/Delinquent Accounts
There are early signs of defaults that, when detected early, can be cured. Monitoring borrowers helps detect these early warning signs and can start as early as 31-45 days, which means the borrower is at least late on the first instalment. Some of the early warning signs are: delayed repayment, even if it is for a day, should be treated with as much interest as multiple defaults. Change in borrower behaviour: When borrowers avoid engagement, become unreachable, or change contacts and/or business/office location, escalations on the account should be initiated immediately. Behavioural changes are signs of distress and should never be ignored. Lenders that invest in early detection record lower NPL ratios.
Debt Collection Agencies (DCAs) and Factoring
In Kenya, there are several DCAs whose sole objective is to recover bad debts and/or to intervene before loans become bad debts. Collection Africa Ltd, the oldest debt collection company in Kenya, has helped multiple financial institutions manage their NPLs by recovering loan defaults for their clients. Banks, SACCOSs, Fintechs, merchandising firms, and manufacturers prefer to use debt collection companies to collect debts on their behalf owing to their expertise in the area, efficiency, and cost, since they are paid on commission based on amounts recovered.
Balancing recovery and customer trust
Effective NPLs management is not only about maximising recoveries but also about preserving customer relationships and institutional reputation. Aggressive recovery tactics may deliver positive short-term results but can damage customer trust, brand image, and future business. Financial institutions must therefore adopt a customer-centred approach that balances firm recovery action with respectful and empathetic engagement.
Lenders must also ensure that internal recovery teams and outsourced Debt Collection Agencies (DCAs) comply with ethical standards and the Data Protection Act, 2019. Harassment, intimidation and unauthorised disclosure of debt information expose institutions to legal and reputational risks. Institutions that prioritise ethical recovery practices are more likely to achieve sustainable recoveries while maintaining long-term customer confidence and loyalty.
Auction
For secured loans, Auctioneering is one of the most powerful tools available to lenders. When a borrower fails to regularise the loans despite restructuring and demand letters, the lender may exercise its statutory power to sell.
Auctioneering is governed by the Auctioneers Act, 1996 and the Land Act for charged properties.
A lender is required by the Act to send a statutory notice, and after the expiry of the notice without remedy, the property/asset is valued by a registered valuer, and a 45-day redemption notice is issued by a licensed auctioneer, and afterwards, the property will be advertised in the dailies for sale.
Pursuing Loans after the Failure of the Auction
The High Court Commercial and Tax division, in its December 2025 judgement in the case of Bank of India v We Hotel and Suites Limited & two others, ruled that unsuccessful auctions of assets linked to loan defaulters do not preclude lenders from enforcing personal guarantees once the principal borrower defaults. This provided a reprieve for banks, especially in cases where the security is insufficient or fails to attract bidders.
Authority to sell assets even after the buyer’s claim of having a buyer
The High Court dismissed a suit by Korara Highlands Tea Factory and two of its directors, who sought to bar KCB Bank Ltd from exercising its statutory power to sell several properties pledged as security. Korara has argued that they had secured a buyer for the assets at USD 10 million (Kes 1.29 billion), which would enable it to settle the loan balance. The court ruled that an anticipated transaction could not override a lender’s accrued right and that the borrower had failed to justify an injunction. This ruling sets a precedent for lenders especially when dealing with borrowers who try to delay the realisation of a security after a loan default.
Legal
After all collections and recovery measures have been exhausted, including outsourcing to DCAs, the bank may proceed with legal action. A formal demand letter must be sent before the bank takes legal action.
The Small Claims Court Act, 2016, operationalised the Small Claims Courts (SCCs) to facilitate the quick and efficient resolution of small claims, with a limit of Kes 1,000,000.00.
IFRS 9, Financial Instruments. Expected Credit Loss (ECL)
IFRS 9 was introduced for annual periods beginning 1st January 2018 to replace IAS 39. The standard introduced the ECL.
CBK issued a guidance note to banks on the implementation of IFRS 9. All provisions under the ECL model should be charged to the income statement; however, provisions relating to performing loans should be added back over a five-year period. All provisions under the ECL for loans issued after 2018 shall be accounted for in accordance with IFRS 9. The banks were given a five-year transition period beginning in January 2018 to fully comply with IFRS 9 in calculating regulatory capital.
Compliance with the Data Protection Act, 2019.
The Data Protection Act, 2019, which gave effect to Article 31 (c) and (d) established the Office of the Data Protection Commissioner (ODPC) to make provision for the regulation of data controllers and processors. This meant that traditional debt collection strategies that violated customers’ data privacy had to be shelved in favour of more consumer-friendly practices.
Over the last few years, the ODPC has highlighted several issues that contradict the standard use of data and data handling practices,
- Calling or messaging third parties without prior authorisation.
- Sending demand letters that reveal contents to unauthorised third parties.
- Purpose limitation of data. One of the data protection principles is purpose limitation, which requires that personal data be collected and processed only for an explicit, specific, and legitimate purpose determined at the time of collection.
- Retaining data longer than necessary. The principle of storage limitation provides that personal data should be reviewed periodically and erased or anonymised when it is no longer needed.
Processors and handlers of data in the credit management realm, be it in lenders’ recovery departments or debt collection agencies, must use appropriate data handling techniques, which include the following,
- Ethical communication. Collectors should refrain from sending messages outside working hours and from sending demand letters that expose private debt information without secure addressing.
- Third-party communication. Debt information should not be divulged to third parties, including spouses, employers, friends, etc.
- Relevance. Only information relevant to debt recovery should be used to recover the debt, and any irrelevant data should not be collected.
- Discard all data when the purpose ends. Once the debt is recovered, all data relating to the customer or the debt should be archived or deleted where necessary.
In the case of Abdul Karim Osiche (complainant) vs Fin Africa t/a trustgro sca limited (respondent), the complainant purported that the respondent, through their staff member, unlawfully shared his personal data and sensitive personal data with a third party’s general contact address. The ODPC found the respondent liable and ordered them to pay the complainant Kes 150,000 as compensation.
Artificial Intelligence (AI) in Customer Scoring and Debt Collection
AI is increasingly transforming credit management by enabling lenders to make faster, more accurate and data-driven decisions. AI-powered systems can analyse large volumes of customer data, including transaction patterns, repayment behaviour, and alternative financial data, to assess creditworthiness and predict the probability of default more effectively than traditional methods.
AI and machine learning models also help lenders identify early warning signs of delinquency before loans become non-performing. This allows financial institutions to intervene early through reminders, restructuring discussions or proactive follow-up. In debt collection, AI can segment borrowers by risk profile and recommend tailored recovery strategies, improving recovery efficiency and reducing operational costs.
However, financial institutions must ensure that AI systems comply with the Data Protection Act, 2019 and CBK regulations by maintaining transparency, protecting customer data and avoiding discriminatory or biased decision-making. Responsible use of AI can significantly reduce NPLs while improving customer experience and overall credit risk management.
The author is the Finance Manager at Collection Africa Limited, a professional credit management (debt collection) firm.
He holds a Master of Science in Finance from UON and a Bachelor of Commerce (Finance) degree from KCAU. He has over eight years of progressive experience in finance, accounting and credit management,
Group Finance Manager, Collection Africa Limited.
