ECONOMYNEXT – Sri Lanka signed a Memorandum of Understanding (MoU) with Yunnan Province of China on Friday (23) to boost the trade and increase goods entering China, the island nation’s government said.

The MoU signed under the trade framework of “Three Free and Three Facilitations,” provides Sri Lankan entrepreneurs with a package that includes free warehousing facilities, free permanent exhibition booths, online market access, as well as customs clearance and transport facilities to enter the Chinese market, Sri Lankan government said in a statement.

“This will provide an opportunity for Sri Lankan companies to significantly reduce export-related costs,” the government said in a statement after signing the deal.

The deal was signed at ‘Sri Lanka and Yunnan Province Special Products Promotion Summit and Business Matchmaking Event,’ jointly organized by the Department of Commerce of Sri Lanka under the Ministry of Trade, Commerce, Food Security and Cooperative Development, and the Department of Commerce of Yunnan Province.

An official delegation led by Li Chaowei, Director General of the Department of Commerce of Yunnan Province, China, along with representatives from over 30 leading Chinese business entities arrived in Sri Lanka to participate in this event.

Addressing the summit virtually Vasantha Samarasinghe, Minister of Trade, Commerce, Food Security and Cooperative Development, emphasized the importance of bilateral cooperation between the two countries and highlighted the need to expand the export capacity of Sri Lankan products within the Chinese market.

Sri Lanka also signed a Letter of Intent (LOI), confirming the participation of Sri Lankan companies in the 11th China-South Asia Expo scheduled to be held in 2027.

This will pave the way for major promotion within the Chinese market for Sri Lanka’s leading export sectors, including Ceylon tea, food and beverages, spices, coconut products, seafood, gems and jewelry, and handicrafts, the government said in the statement. (Colombo/October 23/2026)

ECONOMYNEXT – Revenue collected by Sri Lanka Customs in the first 21 days of October accounted for over 79 percent of the month’s target, official data showed, as the island nation has already outperformed the annual target.

The revenue collecting body has also surpassed monthly targets for nine straight months through September.

Customs’ October revenue target has been set at 193.3 billion rupees. But the revenue collecting body has already collected 152.8 billion rupees in the first 21 days of this month, official data showed.

It has already achieved 103.6 percent of this year’s target through October 21, official data showed.

Customs has been accelerating container clearance using digital scanning to reduce corruption and fast-track the clearance process.

Last year, Customs collected a record 2,551 billion rupees in revenues, higher than a revised target of 2,241 billion rupees for the year, achieving 64.2 percent higher revenue than the previous year’s revenue of 1,553 million rupees.

Customs has set a revenue target of 2,207 billion rupees for this year, 13.5 percent less than last year as it expects a significant decline in car imports. However, it has already achieved 2,286.1 billion rupees through October 21.

Sri Lanka Customs’ revenue jump is largely due to stronger enforcement, improved valuation practices, and a rebound in import volumes after years of contraction.

Following the economic crisis of 2022, imports fell sharply as the country imposed restrictions to conserve foreign exchange.

However, with the stabilization of reserves, the relaxation of certain import controls, and a steady recovery in consumer demand, customs collections from import duties, excise, and other levies have risen.

Officials note that tighter monitoring of under-invoicing and misdeclaration of goods has also contributed to boosting state revenue.

The combined effect of increased import activity, currency movements, and stricter enforcement has positioned Customs as one of the top revenue sources for the Treasury in 2025, providing a vital cushion as the state works to meet fiscal targets under the IMF-supported program. (Colombo/October 23/2026)

ECONOMYNEXT – Sri Lanka’s rupee closed at 332.10/20 to the US dollar in the spot market on Friday, stronger from 332.20/35 the previous day, while bond yields closed lower, dealers said.

A bond maturing on 15.09.2029 closed at 11.05/10 percent, down from 11.05/15 percent.

A bond maturing on 01.08.2030 closed at 11.45/55 percent, down from 11.55/60 percent.

A bond maturing on 01.02.2031 closed at 11.70/75 percent, down from 11.73/78 percent.

A bond maturing on 01.12.2031 closed at 11.80/90 percent, down from 11.90/12.00 percent.

A bond maturing on 15.01.2033 closed at 11.90/12.05 percent, down from 12.20/25 percent.

A bond maturing on 15.10.2034 closed at 12.35/45 percent, down from 12.40/50 percent. (Colombo/Oct23/2026)

ECONOMYNEXT – Central banks must adopt artificial intelligence with strict governance and human oversight to prevent emerging technologies from eroding public trust in financial systems, International Monetary Fund (IMF) Chief Information Officer Shirin Hamid said.

Delivering the 76th Anniversary Oration of the Central Bank of Sri Lanka (CBSL) in Colombo on Friday, Hamid warned that rapid AI adoption brings serious vulnerabilities, including voice cloning, deepfake fraud, and autonomous machine-speed cyberattacks.

“The intelligent central bank is not the bank with the most AI, It is the bank whose AI can be trusted, and can ensure that any AI that touches the financial system is explainable, governed, secure, ethical, and human-supervised,” Hamid said.

Hamid highlighted three major AI threats confronting financial institutions worldwide: impersonated humans using cloned audio and video, autonomous AI swarms executing attacks at machine speed, and indirect breaches that manipulate internal AI assistants already inside bank firewalls.

She noted that as little as three seconds of recorded voice is now enough for AI to produce an indistinguishable clone.

She also warned of data risks, revealing that when the IMF tested commercial generative AI on economic figures, tools like ChatGPT returned inaccurate GDP figures up to two-thirds of the time.

Because plausibly wrong numbers threaten institutional credibility, the IMF developed its own system, StatGPT, to run queries directly against verified data rather than letting models guess.

Hamid urged monetary authorities to ground their technological transitions in four pillars: dependable data, trustworthy systems, operational resilience, and adaptive governance.

Hamid emphasized that institutions must never treat AI simply as an IT department project, pointing out that human judgment remains the scarcest and most vital resource.

“For every AI-influenced decision, we need a named human who is answerable,” Hamid said. “We should aim to augment judgment first, and grant autonomy only where it has been earned,” Hamid said.

Hamid concluded that while financial tools will continue to evolve, the primary mission of an intelligent central bank remains unchanged: safeguarding public confidence from the vault to the algorithm. (Colombo/Oct23/2026)

ECONOMYNEXT – Sri Lanka’s Colombo Stock Exchange concluded the week in negative territory after experiencing five consecutive days of declines, CSE data showed.

The benchmark All Share Price Index was down 0.15 percent, or 29.15 points at 19,688, while the more liquid S&P SL20 was up 0.15 percent, or 8.70 points, at 5,627.

The ASPI has dropped by 497.05 points since last Friday.

The benchmark index has fallen 2.46 percent from its previous Friday close of 20,185.05 points to conclude this week at 19,688.00 points.

Positive contributors to the ASPI were Distilleries Company (up 1 rupee at 51.90), Sunshine Holdings (up 50 cents at 27.50 rupees), LOLC Holdings (up 3.25 rupees at 396.50), Singer (up 0.60 cents at 68.80 rupees), and Haycarb (up 2.25 cents at 199.75 rupees).

Dialog Axiata (down 30 cents at 42.10 rupees), Panasian Power (down 1.60 rupees at 10.10 rupees), Hayleys, Colombo Dockyard (down 3.75 rupees at 100.00) and Ceylon Cold Stores (down 1 rupee at 119.00) were top negative contributors.

Market turnover was 825 million rupees.

Turnover throughout the week reflected muted investor enthusiasm, hovering under the billion mark on most days, except for Thursday when it recorded 1.1 billion rupees.

The CSE has issued a letter of warning to Softlogic Life Insurance PLC for delaying a mandatory disclosure regarding an acquisition of its shares by Asiri Hospital Holdings PLC, a transaction in which Softlogic’s Chairman and a Non-Executive Director hold relevant interests.

The share closed up 1 rupee at 71.20.

Sampath Bank PLC said its 7 billion rupee Basel III compliant debenture issue was oversubscribed, drawing over 12.26 billion rupees in total applications across Type A and Type B tranches.

The share closed up 50 cents at 138.50 rupees. (Colombo/Oct23/2026)

Fitch Ratings-London/New York – Artificial intelligence-related business disruption poses moderate risk to financial institutions (FIs) over the coming five years, Fitch Ratings says.

Mitigants include barriers to entry from regulation (including capital requirements) and solid franchises underpinned by client relationships and diversification. Incumbents may be able to use proprietary data to build out their own AI-based operations.

Our Artificial Intelligence Stress Test scored credit exposure over a five-year horizon across the Corporate, FI, Infrastructure and Structured Finance sectors under three adverse scenarios: over-investment, asset-impairment, and disruption. We assigned sector and sub-sector scores between 0 and 100, with 100 representing the most severe potential negative ratings impact for an average issuer in an adverse scenario.

Potential business disruption risk would arise mainly through increased technological competition on processes and products. This would have the greatest effect on FIs catering to households and SMEs, and whose financial products are mostly standardized, high volume, and easily replicable. However, the impact would depend on how quickly customers adapted their preference for new, AI-led service models.

We assigned sector scores of ‘40’ to Retail Banks and to Private Banks and Wealth Management (PB&WM), signalling the potential for a Negative Outlook and possible one-notch downgrade for a typical company under the adverse scenario.

Retail banks’ mass-market focus could allow AI-enabled fintechs, digital platforms and technology firms to use superior analytics, lower-cost servicing models and more personalized offerings to compete in areas such as unsecured consumer lending, payments, deposits, basic wealth advice and customer onboarding.

The adverse scenario could put moderate pressure on retail banks’ credit profiles through business model disruption, particularly loss of deposits, affecting funding costs and ultimately profitability, and more generally from loss of business that could weaken franchises. The extent of these effects, combined with potential reputational damage and/or regulatory fines, would vary across banks.

AI will likely affect wealth management more than private banking, as the latter will likely remain ‘high-touch’, with AI augmenting client relationships. Wealth management could face greater disruption from commoditization of advice and entry of new competitors, increasing fee pressure.

We do not anticipate AI driving sector-wide rating actions over the next five years for PB&WM issuers, which are likely to moderate AI’s competitive impact through greater scale and lower cost to service.

We also assigned a score of ‘40’ to Wealth Managers and Advisory Firms, predominantly due to elevated business-model disruption risk. AI-enabled tools could automate or reduce the cost of investment advice, portfolio construction, and research support and advisory execution. However, fiduciary and regulatory obligations require human accountability for advice, limiting full AI substitution.

Corporate and Investment Banks (CIBs) scored ‘20’. Business model-disruption risk appears limited over the next five years, as leading CIBs’ broad product mix, high barriers to entry from regulation, and the critical role of bespoke human judgment in advisory, origination, structuring and underwriting businesses offer substantial protection against non-bank competition. Leading CIBs’ ample financial and technical resources to develop AI-based solutions can also protect their competitiveness, although robust controls would be needed to prevent over-reliance.

All insurance sub-sectors have scores of ‘20’. Business-disruption risk mitigants are generally substantial and may include proprietary policyholder data, established distribution relationships, product complexity, and significant regulatory and capital barriers to entry. Retail business is more exposed than commercial, due to greater standardization and changing consumer preferences.

Reinsurers are less exposed than primary insurers to AI-driven distribution disintermediation, although AI challenges the core reinsurance function of risk modelling. New and evolving correlation patterns, especially in accumulation-sensitive lines, may be less visible in historical data and harder to capture in traditional frameworks, which could result in improper pricing, weaker reserving and unwanted exposure accumulation.